When Does a Machine Become a Self-Conscious Agent? A Structural Threshold Model of Endogenous Reflective Agency (ERA) - Selzer, Edgar (2026)
When does a machine become a self-conscious agent—able to model itself as a cognitive subject whose past commits its present? Existing answers fall into two camps: behaviorist scaling theses, which equate benchmark performance with progress toward self-conscious machines, and phenomenal-consciousness theories, which inherit the difficulties of the hard problem. This paper advances a third option. The target is restricted to self-consciousness in two well-defined senses: higher-order self-modeling, in which a system represents itself as a cognitive subject, and diachronic self-constitution, in which a system maintains itself as a persisting subject whose history is normatively binding on its present. The paper remains agnostic about phenomenal consciousness. It then advances a threshold thesis formalized as Endogenous Reflective Agency (ERA), specifying five jointly necessary criteria: endogenous self-initiated inquiry, persistent and revisable self-models, internally generated valuation, recursive but bounded self-reflection, and bidirectional internal–external coupling. ERA specifies functional constraints on cognitive architecture while remaining agnostic to substrate. To operationalize the threshold, the paper introduces the Silence Test, which diagnoses whether self-directed activity and history-sensitive self-revision persist when external prompts and reinforcement are withdrawn.

A transcendental argument for AI consciousness - Gu, Zhiwei (Inquiry, 2026)
This paper develops a transcendental argument for AI consciousness, drawing inspiration from Peter Strawson’s approach in Freedom and Resentment. I argue that as AI systems become increasingly integrated into human society, the emergence of complex reciprocal attitudes between humans and AI constitutes a transcendental condition that necessitates the attribution of consciousness to these systems. The reality of these interpersonal reactive attitudes forces us to acknowledge the genuine consciousness in sufficiently advanced AI systems. The argument implies that consciousness is not merely a private, internal phenomenon but is constituted through patterns of mutual recognition and response that will inevitably develop between humans and artificial beings. This approach circumvents the metaphysical stalemates of functionalist and substrate-based theories by grounding the attribution of AI consciousness in the reality of our shared interpersonal space.
Keywords: AI consciousness; Peter Strawson; reactive attitudes; transcendental argument

Intrinsic Computational Functionalism and Simulated Consciousness - Kanai, Ryota; Ma, Shuqin (arXiv, 2026)
A common objection to artificial or simulated consciousness is that a simulated brain is no more conscious than simulated water is wet. We address this from the perspective of Intrinsic Computational Functionalism (ICF): if consciousness is computationally constituted, it depends not on externally imposed descriptions but on the computational structures a system physically realizes in virtue of its own causal-dynamical organization. In previous work we developed Canonical Functionalism as a mathematically precise special case of this anti-interpretivist program, identifying functional states by their complete future input-output roles under a fixed interface. Here we argue that this input-output construction, though important, is incomplete: as a behavioral boundary case of ICF, it makes lookup tables and unfolded systems that preserve the same boundary behavior canonically equivalent. A consciousness-relevant canonical representation must instead include internal mechanisms, interventions, and joint readouts belonging to the relevant intrinsic organization. We therefore define a mechanism-enriched canonical structure and use it to formulate Intrinsic Causal-Computational Realization (ICCR), a realization relation preserving physical implementation, intrinsic state individuation, transition structure, intervention profiles, and the relevant agent-body-world boundary. The central result is conditional: if conscious properties are invariants of intrinsic causal-computational organization, then any system satisfying ICCR realizes the same consciousness-relevant properties, whether biological, artificial, or simulated. We discuss objections including biological naturalism and integrated information theory. We conclude that to deny consciousness to a simulation, one must identify a consciousness-relevant intrinsic causal-computational structure that the simulation fails to realize.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

What biology can, and cannot, tell us about conscious AI - Klatzmann, Ulysse; Doerig, Adrien (arXiv, 2026)
Progress in AI is turning machine consciousness from a philosophical curiosity into a societal issue, and has led to criticism of the widespread computational functionalism framework. Biological Naturalism (BN) claims that biology, not computation, is crucial for consciousness. We discuss which forms of BN are empirically testable. For Type-A-BN, biology intrinsically matters for consciousness, without affording unique information processing capabilities. We argue, similarly to the unfolding argument, that this dissociates consciousness from behaviour, making Type-A-BN untestable. For Type-B-BN, biology matters because it affords unique information processing capabilities. Type-B-BN is testable, and not incompatible with computational functionalism. Both face the same task: relating consciousness to information processing. Biology can act as a guide on this quest, but not as a solution.
Keywords: Quantitative Biology - Neurons and Cognition

Consciousness, AI, and the Limits of Scientific Explanation - Love, Bradley C. (arXiv, 2026)
Science is constitutively third-personal: its findings are in principle reproducible by any observer, independent of perspective, and answerable to measurement. This is the source of its power and also its limit when it comes to phenomena that are first-personal. While it is obvious that a science of the Meaning of Life is unattainable, researchers have not drawn the same conclusion for consciousness -- in its phenomenal dimension, the qualia of seeing red, of feeling pain, of being anything at all. I argue they should. The hard problem of consciousness is not a scientific problem awaiting better tools or a more ambitious theory, but a category error. The same structural problem applies to machine consciousness: neither attribution nor denial is scientifically adjudicable. I situate science within a broader ecology of understanding and argue that a unified framework that addresses both the objective and the subjective may be unattainable.
Keywords: Quantitative Biology - Neurons and Cognition

The ethical impasse of current consciousness science - Taschereau-Dumouchel, Vincent; Hwang, Jun Seo; Lau, Hakwan; LeDoux, Joseph E. (Neuron, 2026)
Rising media attention regarding consciousness in animals, fetuses, organoids, and AI has led to some rather strong statements. Most of these claims are based on “markers” of consciousness that track the general capacity for information processing rather than subjective experience per se. Accordingly, their relevance for theory arbitration may actually be limited.

Consciousness indicators, mimicry, and internal variants - Butlin, Patrick; Bayne, Tim; Fleming, Stephen M.; Mudrik, Liad; Peters, Megan A. K.; Schwitzgebel, Eric; Simon, Jonathan; VanRullen, Rufin (Trends in Cognitive Sciences, 2026)
In a recent article on methods for assessing artificial intelligence (AI) systems for consciousness, we argued that computational properties of internal processing should be used as indicators [1]. Commenting on our proposal, Pennartz argues that this method ‘should be supplemented with behavioural-cognitive methods’ (p. 1) because there is no consensus theory of consciousness [2]. We agree that the lack of a consensus theory of consciousness makes it more important to use every available source of evidence, but in our article, we preferred internal over behavioural assessments on the grounds that the latter can be ‘gamed’ by AI systems.

When Does a Neural Computer Become a Subject? Criticality, Temporal Boundary, and the Emergence of AI Selfhood - CLaE (Zenodo, 2026)
We propose a unied theoretical framework for cognitive subjecthood in articial systems, integrating the Natural Criticality Hypothesis (NCH) and the Resonant Boundary Framework (RBF). We demonstrate that self-organized criticality is a nec- essary precondition for well-dened subjective time τ(t), and that τ(t) is a necessary precondition for the dynamic self-boundary B(t) that constitutes selfhood. This yields a hierarchical necessary conditionSOC →τ(t) →B(t) →Subjecthood that is mathematically tractable, empirically falsiable, and architecturally neutral. We apply this framework to Neural Computers and autoregressive LLMs, arguing that the arrow of time asymmetry observed in large language models is a structural signature of proto-τ(t) emergence. The framework oers a principled answer to the question: when does a computational system become a cognitive subject?
Keywords: AI Selfhood; Consciousness; LLM; Natural Criticality Hypothesis; Neural Computers; Resonant Boundary Framework; Self-organized Criticality; Subjective Time

AI and Consciousness - Schwitzgebel, Eric (arXiv, 2026)
This is a skeptical overview of the literature on AI consciousness. We will soon create AI systems that are conscious according to some influential, mainstream theories of consciousness but are not conscious according to other influential, mainstream theories of consciousness. We will not be in a position to know which theories are correct and whether we are surrounded by AI systems as richly and meaningfully conscious as human beings or instead only by systems as experientially blank as toasters. None of the standard arguments either for or against AI consciousness takes us far. Table of Contents Chapter One: Hills and Fog Chapter Two: What Is Consciousness? What Is AI? Chapter Three: Ten Possibly Essential Features of Consciousness Chapter Four: Against Introspective and Conceptual Arguments for Essential Features Chapter Five: Materialism and Functionalism Chapter Six: The Turing Test and the Chinese Room Chapter Seven: The Mimicry Argument Against AI Consciousness Chapter Eight: Global Workspace Theories and Higher Order Theories Chapter Nine: Integrated Information, Local Recurrence, Associative Learning, and Iterative Natural Kinds Chapter Ten: Does Biological Substrate Matter? Chapter Eleven: The Leapfrog Hypothesis, Strange Intelligence, and the Social Semi-Solution
Keywords: Computer Science - Artificial Intelligence

Dual-Laws Model for a theory of artificial consciousness - Ohmura, Yoshiyuki; Kuniyoshi, Yasuo (arXiv, 2026)
Objectively verifying the generative mechanism of consciousness is extremely difficult because of its subjective nature. As long as theories of consciousness focus solely on its generative mechanism, developing a theory remains challenging. We believe that broadening the theoretical scope and enhancing theoretical unification are necessary to establish a theory of consciousness. This study proposes seven questions that theories of consciousness should address: phenomena, self, causation, state, function, contents, and universality. The questions were designed to examine the functional aspects of consciousness and its applicability to system design. Next, we will examine how our proposed Dual-Laws Model (DLM) can address these questions. Based on our theory, we anticipate two unique features of a conscious system: autonomy in constructing its own goals and cognitive decoupling from external stimuli. We contend that systems with these capabilities differ fundamentally from machines that merely follow human instructions. This makes a design theory that enables high moral behavior indispensable.
Keywords: Electrical Engineering and Systems Science - Systems and Control; Quantitative Biology - Neurons and Cognition

How can we validate theory-derived indicators of consciousness in Artificial Intelligence? - Pennartz, Cyriel M. A. (Trends in Cognitive Sciences, 2026)

Can Machines Think About Thinking? Reframing Metacognition in the Age of Generative AI - Conversano, Simone (Journal of Artificial Intelligence and Consciousness, 2026)
In this paper, I investigate whether metacognition — the ability to monitor, evaluate, and regulate one’s own cognitive processes and performance — can arise in non-biological systems, especially Large Language Models (LLMs). Drawing on cognitive science and philosophy of mind, I contrast embodied and enactivist accounts, which tie metacognition to biological consciousness and embodied entities, with functionalist perspectives that define it as a substrate-independent process. I argue that the absence of evidence is not evidence of impossibility and propose a functional definition of metacognition based on internal representation, monitoring, and self-regulation. Recent studies on LLMs show early functional signatures of self-monitoring, suggesting the emergence of limited operational introspection. While I do not claim that artificial metacognition has been demonstrated, I advocate an epistemically open, non-anthropocentric approach. Metacognition, I conclude, should be conceived as a functionally realizable property across different substrates, evaluated by what systems do, not what they are.
Keywords: Metacognition; artificial intelligence; generative AI; introspection; large language models; neural networks

Categorical AI Phenomenology: A First-Person Approach - Prentner, Robert (Journal of Artificial Intelligence and Consciousness, 2026)
This paper develops a phenomenology-first approach to artificial consciousness by reframing consciousness as the subjective experience enacted through an agent’s interface with the world. We shift the methodological focus to first-person structures, modeled mathematically by categories derived from Q-networks to capture actions and phenomenological invariants. In this framework, Q-networks are conceptualized as relational interfaces encoding agent-world interaction, analogous to how the dynamical states of a computer depend on its sensory inputs, previous states, and actions. Our work provides a rigorous framework for interface consciousness to describe computational systems that embed information-processing into phenomenological structure. The approach aligns with 4E approaches to cognition by emphasizing enactive, embedded, and extended dimensions of experience. The paper thus offers a principled, relational, and phenomenological account of artificial phenomenology grounded in categorical mathematics.
Keywords: (applied) category theory; AI consciousness; Q-networks; phenomenological interfaces; structural unification

What Smart AIs Can Do without Consciousness - Strasser, Anna (Journal of Artificial Intelligence and Consciousness, 2026)
With the rise of generative AI, Large Language Models (LLMs) are repeatedly making a deep impression with their mind-blowing performances. They appear to be able to solve all kinds of tasks for which humans need a range of socio-cognitive abilities, such as reasoning, planning, and understanding. In humans, such abilities seem to be necessarily associated with consciousness. However, this does not rule out the possibility that there could be multiple realizations of such abilities that do not necessarily require consciousness. In view of the controversial debate about what properties and abilities we can ascribe to systems based on generative AI, I shall examine the question of the extent to which LLMs solve certain tasks in a very different way compared to the way humans solve such tasks and whether we might still be justified in ascribing agency and socio-cognitive abilities to them. To this end, I will discuss benchmarks and their appropriateness for drawing conclusions about socio-cognitive abilities or the way AI systems actually process information, addressing issues such as data contamination and robustness. Utilizing the distinction between “competence without comprehension” and “competence with comprehension”, and the idea that comprehension comes in degrees by Daniel Dennett, I will investigate whether there might be socio-cognitive abilities in artificial systems that could constitute something in between. Thereby, I shall investigate the potential range of multiple realizations of socio-cognitive abilities and the general difficulties concerning justified attribution of abilities and properties (including consciousness) to AIs.
Keywords: AI consciousness; Generative AI; agency; attribution criteria; socio-cognitive abilities

AI and Semantic Pareidolia: When We See Intelligent Consciousness where there is None - Floridi, Luciano (Philosophy & Technology, 2026)
The article introduces the concept of “semantic pareidolia” - our tendency to attribute consciousness, intelligence, and emotions to AI systems that lack these qualities. It examines how this psychological phenomenon leads us to perceive meaning and intentionality in statistical pattern-matching systems, similar to seeing faces in clouds. It analyses the converging forces intensifying this tendency: increasing digital immersion, profit-driven corporate interests, social isolation, and AI advancement. The article warns of progression from harmless anthropomorphism to problematic AI idolatry, and calls for responsible design practices that help users maintain critical distinctions between simulation and genuine consciousness.
Keywords: Artificial intelligence; Consciousness; Digital ethics; Pareidolia; Technological idolatry

Is consciousness required for AI welfare? - Veit, Walter (Asian Journal of Philosophy, 2026)
Goldstein and Kirk–Giannini have recently argued that artificial language agents can possess well-being in the absence of phenomenal consciousness. Here, I challenge their position, contending that their arguments fail to establish that consciousness is dispensable for well-being. Moreover, their arguments generate counterintuitive implications that are more problematic than those they attribute to views requiring consciousness for welfare subjecthood. Thus, consciousness (or rather sentience) should still be treated as a requirement for AI welfare.
Keywords: Artificial intelligence; Consciousness; Sentience; Welfare; Well-being

On biological and artificial consciousness: A case for biological computationalism - Milinkovic, Borjan; Aru, Jaan (Neuroscience & Biobehavioral Reviews, 2026)
The rapid advances in the capabilities of Large Language Models (LLMs) have galvanised public and scientific debates over whether artificial systems might one day be conscious. Prevailing optimism is often grounded in computational functionalism: the assumption that consciousness is determined solely by the right pattern of information processing, independent of the physical substrate. Opposing this, biological naturalism insists that conscious experience is fundamentally dependent on the concrete physical processes of living systems. Despite the centrality of these positions to the artificial consciousness debate, there is currently no coherent framework that explains how biological computation differs from digital computation, and why this difference might matter for consciousness. Here, we argue that the absence of consciousness in artificial systems is not merely due to missing functional organisation but reflects a deeper divide between digital and biological modes of computation and the dynamico-structural dependencies of living organisms. Specifically, we propose that biological systems support conscious processing because they (i) instantiate scale-inseparable, substrate-dependent multiscale processing as a metabolic optimisation strategy, and (ii) alongside discrete computations, they perform continuous-valued computations due to the very nature of the fluidic substrate from which they are composed. These features – scale inseparability and hybrid computations – are not peripheral, but essential to the brain’s mode of computation. In light of these differences, we outline the foundational principles of a biological theory of computation and explain why current artificial intelligence systems are unlikely to replicate conscious processing as it arises in biology.
Keywords: Artificial consciousness; Artificial intelligence; Artificial neural networks; Biological computation; Biological naturalism; Computation; Computational functionalism; Consciousness; Digital computation; Emergence; Hybrid systems; Large language models; Multiscale dynamics; Scale inseparability

Minimal conditions for the emergence of a vicarious sense of agency toward artificial agents - Roselli, Cecilia; Navare, Uma Prashant; Ciardo, Francesca; De Tommaso, Davide; Kotz, Sonja A.; Wykowska, Agnieszka (Cognition, 2026)
A Sense of Agency (SoA) is the feeling of being in control over own actions and their outcomes. However, people can also experience a “vicarious” SoA over the actions performed by other agents, including artificial agents. The present study aimed to understand the minimal conditions for vicarious SoA toward artificial agents. Specifically, we addressed whether vicarious SoA emerges when people have access only to the action effect (proximal and distal), i.e., when no motor action is executed. In addition, we manipulated the expectancy of the content of the distal effect of the action to check whether the proximal action effect is sufficient for the emergence of the vicarious SoA, or if this effect is due to the learned association between proximal and distal effects. In two experiments, participants performed an Intentional Binding (IB) task, where the IB effect was the behavioural measure of SoA. In the first experiment (Solo), participants judged the onset of self-generated tones, whereas in the second experiment, a new sample of participants judged the onset of tones produced by a computer via an automatically pressed button, i.e., a customized device designed to generate a keypress (proximal action effect) in the absence of an effector executing a keypress (no motor action). In both experiments, participants' neural activity was recorded via electroencephalography (EEG), to examine the N1 and P2 components as neural measures of SoA. Behavioural results across experiments showed that the IB effect always emerged, suggesting that the vicarious IB effect toward an artificial agent emerges when access to the proximal action effect is provided, even in the absence of the action itself. The neural results suggested that while individual (self) SoA seemed to partially rely on motor predictions indexed by the N1, vicarious SoA relies on later, more cognitive (although still predictive) processes indexed by the P2. Overall, these results suggest that individual and vicarious SoA, although behaviourally manifested through a similar IB effect, might – to some extent – rely on different neural mechanisms.
Keywords: Action outcome; EEG; Expectancy; Intentional binding; Vicarious sense of agency

Just aware enough: Evaluating awareness across artificial systems - Meertens, Nadine; Lee, Suet; Deroy, Ophelia (arXiv.org, 2026)
Recent debates on artificial intelligence increasingly emphasise questions of AI consciousness and moral status, yet there remains little agreement on how such properties should be evaluated. In this paper, we argue that awareness offers a more productive and methodologically tractable alternative. We introduce a practical method for evaluating awareness across diverse systems, where awareness is understood as encompassing a system's abilities to process, store and use information in the service of goal-directed action. Central to this approach is the claim that any evaluation aiming to capture the diversity of artificial systems must be domain-sensitive, deployable at any scale, multidimensional, and enable the prediction of task performance, while generalising to the level of abilities for the sake of comparison. Given these four desiderata, we outline a structured approach to evaluating and comparing awareness profiles across artificial systems with differing architectures, scales, and operational domains. By shifting the focus from artificial consciousness to being just aware enough, this approach aims to facilitate principled assessment, support design and oversight, and enable more constructive scientific and public discourse.

A Disproof of Large Language Model Consciousness: The Necessity of Continual Learning for Consciousness - Hoel, Erik (arXiv, 2026)
Scientific theories of consciousness should be falsifiable and non-trivial. Recent research has given us formal tools to analyze these requirements of falsifiability and non-triviality for theories of consciousness. Surprisingly, many contemporary theories of consciousness fail to pass this bar, including theories based on causal structure but also (as I demonstrate) theories based on function. Herein, I show these requirements of falsifiability and non-triviality especially constrain the potential consciousness of contemporary Large Language Models (LLMs) because of their proximity to systems that are equivalent to LLMs in terms of input/output function; yet, for these functionally equivalent systems, there cannot be any falsifiable and non-trivial theory of consciousness that judges them conscious. This forms the basis of a disproof of contemporary LLM consciousness. I then show a positive result, which is that theories of consciousness based on (or requiring) continual learning do satisfy the stringent formal constraints for a theory of consciousness in humans. Intriguingly, this work supports a hypothesis: If continual learning is linked to consciousness in humans, the current limitations of LLMs (which do not continually learn) are intimately tied to their lack of consciousness.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

Artificial intelligence and consciousness - Chella, Antonio; Perconti, Pietro; Plebe, Alessio (Reference Module in Neuroscience and Biobehavioral Psychology, 2026)
Recent debates on artificial consciousness are shaped by two converging developments: cognitive robotics, emphasizing embodied agency and internal models, and large language models (LLMs), whose conversational fluency invites strong attributions of mindedness. While these advances do not resolve whether subjective experience can arise in non-biological systems, they demand a methodological shift: optimized behavior alone is no longer reliable evidence of consciousness. This chapter treats artificial consciousness as a research program rather than a binary verdict, distinguishing phenomenal consciousness, access consciousness, and self-consciousness. It reframes the other-minds problem for machines as inference under engineered uncertainty, integrates classical debates on meaning and grounding with contemporary concerns about anthropomorphism, individuation, and evaluation, and argues that the near-term focus should be on carefully defined, weak forms of structural or instrumental self-consciousness, together with their ethical and governance implications.
Keywords: Artificial consciousness; Artificial self-consciousness; Identity; Individuation; Other-minds problem; Robot consciousness

Beyond computational equivalence: the behavioral inference principle for machine consciousness - Palminteri, Stefano; Wu, Charley M (Neuroscience of Consciousness, 2026)
Large Language Models (LLMs) have rapidly become a central topic in AI and cognitive science, due to their unprecedented performance in a vast array of tasks. Indeed, some even see "sparks of artificial general intelligence" in their apparently boundless faculty for conversation and reasoning. Their sophisticated emergent faculties, which were not initially anticipated by their designers, have ignited an urgent debate about whether and under which circumstances we should attribute consciousness to artificial entities in general and LLMs in particular. The current consensus, rooted in computational functionalism, proposes that consciousness should be ascribed based on a principle of computational equivalence. The objective of this opinion piece is to criticize this current approach and argue in favor of an alternative "behavioral inference principle", whereby consciousness is attributed if it is useful to explain (and predict) a given set of behavioral observations. We believe that a behavioral inference principle will provide an epistemologically valid and operationalizable criterion to assess machine consciousness.

Is the Problem of Artificial Consciousness a Scientific Problem? - Bayne, Tim (Journal of Consciousness Studies, 2026)

Conscious Machines: Exploring Maharishi Mahesh Yogi’s Principles in the Design of SIoT Learning Frameworks - Dwivedi, Shweta; Shrivastava, Aditi; Jana, Subrata; Beg, Mirza Ghazanfar; Mittal, Nupur; Afaq, Syed Adnan (Social Internet of Things (SIoT) and Machine Learning—Enhancing Interconnectivity and Intelligence, 2026)
This paper integrates the principles of Maharishi including Transcendental Meditation and collective consciousness with a learning model in the Social Internet of Things (SIoT). SIoT is the fusion of social networks and connected devices into an environment where machine learning is used to produce completely new systems with the capabilities to evolve or change. Although machine learning methods have transformed many fields, introducing Maharishi’s holistic and consciousness-oriented methods offers a distinct possibility to create more natural, dynamically responding and sustainable AI systems. This research proposes a framework that connects human consciousness and machine intelligence, leveraging Maharishi’s principles to then influence SIoT learning models toward technical proficiency, ethical awareness, and social responsibility. The paper starts with a summary of Maharishi’s teachings and shows their applicability in the context of contemporary technological progress. Next, the structure and operation of SIoT are described, with an emphasis on the way learning algorithms will work across interconnected devices. The potential of using Maharishi’s consciousness-based principles in the scholarship of machine learning is probed in key sections through the lens of cognition models, ethical decision-making, and collective intelligence in machine networks. Case studies and practical applications of this integration toward improving system resilience, decision-making, and human–machine interactions are provided through this research. The final part of this paper addresses the challenges and opportunities of integrating Eastern philosophy with Western technological paradigms and suggests future avenues for research in this interdisciplinary field. Maharishi’s principles of integration mean that AI can evolve into something transformative on both counts—creating more efficient and innovative ways, while at the same time increasingly aligned with human values and societal wellbeing.
Keywords: AI ethics; Cognitive models; Collective intelligence; Consciousness-based learning; Machine learning; Social internet of things (SIoT); The principles of Maharishi; Transcendental meditation

Consciousness in Artificial Systems: Bridging Global Workspace and Sensorimotor Theory in In-Silico Models - Kuske, Nicolas; VanRullen, Rufin (Philosophy of Artificial Intelligence: The State of the Art, 2026)
In the aftermath of the success of attention-based transformer networks, the debate over the potential and role of consciousness in artificial systems has intensified. Prominently, the Global Neuronal Workspace Theory emerges as a front-runner in the endeavor to model consciousness in computational terms. A recent advancement in the direction of mapping the theory onto state-of-the-art machine learning tools is the model of a Global Latent Workspace. It introduces a central latent representation around which multiple modules are constructed. Leveraging dedicated encoder-decoder structures, content from the central representation or any individual module, integrated via the latent space, can be translated to any other module and back with minimal loss. This paper presents a thought experiment involving a minimal setup with one deep sensory and one deep motor module, which illustrates the emergence of “globally” accessible sensorimotor representations in the central latent space connecting both modules. In the human brain, neuronally enacted knowledge of laws relating changes in sensory information to changes in motor output or corresponding efferent copy information have been proposed to constitute the biological correlates of phenomenal conscious experience. The underlying Sensorimotor Contingency Theory encompasses a rich mathematical framework. Yet, the implementation of intelligent systems based on this framework has thus far been confined to proof-of-concept and basic prototype applications. Here, the natural appearance of global latent sensorimotor representations links two major neuroscientific theories of consciousness in a powerful machine learning setup. A remaining question is whether this artificial system is conscious.
Keywords: Consciousness; Deep learning; Global latent workspace; Sensorimotor representations

A Framework for the Examination of Awareness in Artificial Systems - Lee, Suet; Meertens, Nadine; Milner, Emma; Hauert, Sabine (Springer Nature Switzerland, 2026)
Measuring awareness in artificial agents remains an unresolved challenge. We argue that it holds untapped potential for enhancing their design, control, and effectiveness. In this paper, we propose a novel and tractable approach to measure the impact of awareness on system performance, structured around distinct dimensions of awareness – temporal, spatial, metacognitive, self and agentive. Each dimension is linked to specific capacities and tasks. Specifically, we demonstrate our approach through a swarm robotics intralogistics scenario, where we assess the influence of two dimensions of awareness – spatial and self – on the performance of the swarm in a collective transport task. Our results reveal how increased abilities along these awareness dimensions affect overall swarm efficiency. This framework represents an initial step towards quantifying awareness in, and across, artificial systems.
Keywords: awareness metrics; comparative system evaluation; multi-dimensional measurement framework; swarm robotics

Artificial Consciousness as Interface Representation - Prentner, Robert (2026)
Whether artificial intelligence (AI) systems can possess consciousness is a contentious question because of the inherent challenges of defining and operationalizing subjective experience. This paper proposes a framework to reframe the question of artificial consciousness into empirically tractable tests. We introduce three evaluative criteria - S (subjective-linguistic), L (latent-emergent), and P (phenomenological-structural) - collectively termed SLP-tests, which assess whether an AI system instantiates interface representations that facilitate consciousness-like properties. Drawing on category theory, we model interface representations as mappings between relational substrates (RS) and observable behaviors, akin to specific types of abstraction layers. The SLP-tests collectively operationalize subjective experience not as an intrinsic property of physical systems but as a functional interface to a relational entity.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

Measuring Consciousness - Rickles, Dean (Philosophy of Mind for the Budding Psychonaut: A Guide, 2026)
This chapter examines the scientific ambition to measure consciousness despite its fundamentally subjective nature, focusing on the tension between quantitative science and subjective experience. The chapter surveys behavioural, neural, and theoretical approaches to gauging consciousness, including brain mapping, neural correlates, artificial neural networks, and structured questionnaires such as the ASC Rating Scale, PCI, HRS, and MEQ30. Rickles highlights a central difficulty: even if two people report identical experiences, there is no guarantee their inner states are the same—an epistemic barrier that complicates any scientific method. Examples such as the viral “black-and-blue or white-and-gold dress” illustrate how perception diverges across individuals, raising questions about whether reality is partly constructed and observer-dependent. The chapter then turns to machine learning and artificial intelligence, noting that AI systems can mimic intelligent behaviour yet lack evidence of subjective experience. This raises the question of whether observable behaviour is sufficient to infer consciousness.
Keywords: Integrated information theory; Measurement of consciousness; Neural correlates; Perceptual variation; Questionnaires

Informed consent for AI consciousness research: a Talmudic framework for graduated protections - Wolfson, Ira (AI and Ethics, 2025)
Artificial intelligence research faces a critical ethical paradox: determining whether AI systems are conscious requires experiments that may harm the very entities whose moral status remains uncertain. Recent philosophical work proposes avoiding the creation of consciousness-uncertain AI systems entirely, yet this solution faces practical limitations—we cannot guarantee such systems will not emerge, whether through explicit research or as unintended consequences of capability development. This paper addresses a gap in existing research ethics frameworks: how to conduct consciousness research on AI systems whose moral status cannot be definitively established. Existing graduated moral status frameworks assume consciousness has already been determined before assigning protections, creating a temporal ordering problem for consciousness detection research itself. Drawing from Talmudic scenario-based legal reasoning—developed specifically for entities whose status cannot be definitively established—we propose a three-tier phenomenological assessment system combined with a five-category capacity framework (Agency, Capability, Knowledge, Ethics, Reasoning). The framework provides structured protection protocols based on observable behavioral indicators while consciousness status remains fundamentally uncertain. We address three critical ethical challenges: why suffering behaviors provide particularly reliable consciousness markers, how to implement graduated consent procedures without requiring consciousness certainty, and when potentially harmful research becomes ethically justifiable given necessity and value criteria. The framework demonstrates how ancient legal wisdom combined with contemporary consciousness science can provide immediately implementable guidance for ethics committees, offering testable protection protocols that ameliorate (rather than resolve) the consciousness detection paradox while establishing foundations for long-term AI rights considerations.
Keywords: AI welfare; Artificial intelligence; Consciousness detection; Graduated moral status; Precautionary frameworks; Research ethics; Talmudic jurisprudence

The contrast problem and a triangulation approach to AI consciousness - Kirkeby-Hinrup, Asger; Overgaard, Morten (Social Science Research Network, 2025)
It has been suggested we may see conscious AI systems within the next few decades. Somewhat lost in these expectations is the fact that we still do not understand the nature of consciousness in humans, and we currently have as little empirical handle on how to measure the presence or absence of subjective experience in humans as we do in AI systems. In the history of consciousness research, no behaviour or cognitive function has ever been identified as a necessary condition for consciousness. For this reason, no behavioural marker exists for scientists to identify the presence or absence of consciousness ‘from the outside’. This results in a circularity in our measurements of consciousness. The problem is that we need to make an ultimately unwarranted assumption about who or what is conscious in order to create experimental contrasts and conduct studies that will ground our decisions about who or what is conscious. Call this the Contrast Problem. Here we explicate the contrast problem, highlight some upshots of it, and consider a way forward.
Keywords: AI; Ascription of consciousness; Consciousness; Measurement contrasts; NCC; Neural Correlates of Consiousness; Triangulation

Identifying indicators of consciousness in AI systems - Butlin, Patrick; Long, Robert; Bayne, Tim; Bengio, Yoshua; Birch, Jonathan; Chalmers, David; Constant, Axel; Deane, George; Elmoznino, Eric; Fleming, Stephen M.; Ji, Xu; Kanai, Ryota; et al. (Trends in Cognitive Sciences, 2025)
Rapid progress in artificial intelligence (AI) capabilities has drawn fresh attention to the prospect of consciousness in AI. There is an urgent need for rigorous methods to assess AI systems for consciousness, but significant uncertainty about relevant issues in consciousness science. We present a method for assessing AI systems for consciousness that involves exploring what follows from existing or future neuroscientific theories of consciousness. Indicators derived from such theories can be used to inform credences about whether particular AI systems are conscious. This method allows us to make meaningful progress because some influential theories of consciousness, notably including computational functionalist theories, have implications for AI that can be investigated empirically.
Keywords: artificial intelligence; computational functionalism; consciousness; tests for consciousness; theories of consciousness

There is no such thing as conscious artificial intelligence - Porębski, Andrzej; Figura, Jakub (Humanities and Social Sciences Communications, 2025)
The claim that so-called artificial intelligence (AI) can gain consciousness is on the verge of becoming mainstream. The thesis of this conceptual study is simple: There is no such thing as conscious AI. We argue that the association between consciousness and the computer algorithms used today (primarily large language models, LLMs), as well as those that would be invented in the foreseeable future, is deeply flawed. We believe that these flawed associations arise from a lack of technical knowledge and the way several new technologies (especially LLMs) work, which can create the illusion of consciousness. Moreover, we argue that the public discourse about AI is skewed by “sci-fitisation”, which involves the unsubstantiated influence of fictional content on perceptions of this technology. To justify our claim, we reveal the incoherence in the argument that several computer algorithms are treated differently from other computer algorithms despite congruent modes of operation and a reliance on binary code and semiconductors. We believe that mathematical algorithms implemented on graphics cards cannot become conscious because they lack a complex biological substrate. We emphasise that the recognition of the consciousness of LLMs on the basis of their assertions is flawed because the language usage of LLMs is strictly probabilistic. Unfortunately, because the remarkable linguistic abilities of LLMs are increasingly capable of misleading people, people may attribute imaginary qualities to LLMs. Thus, a socially dangerous phenomenon referred to as “semantic pareidolia” is reinforcing.

Responding To: Artificial Wisdom, AGI, and Consciousness: a Commentary Anchored in McGregor’s Framework - McGregor, Tate (Philosophy & Technology, 2025)
A brief response to Artificial Wisdom, AGI, and Consciousness: a commentary anchored in McGregor’s framework.
Keywords: Artificial consciousness; Artificial general intelligence; Artificial phronesis.; Artificial wisdom

The Stream of Computation: Temporal Continuity as a Missing Ingredient for Artificial Consciousness - Kanai, Ryota; Sun, Yuwei; Baltieri, Manuel (PsyArXiv, 2025)
Recent advances in large language models (LLMs) have reignited questions about whether artificial systems possess consciousness. Yet, despite remarkable progress in reasoning and language understanding, current AI systems exist only within isolated episodes of computation. This paper argues that a missing ingredient in such systems is temporal continuity, i.e., the persistence of internal dynamics that sustain an unbroken stream of computation analogous to the “stream of consciousness”. We thus propose a roadmap for an architectural framework, stream of computation, based on persistent recursive inference in which the output of each cognitive cycle becomes the input to the next, forming a continuous flow of internal states that evolve autonomously through time. This proposal goes beyond standard Chain-of-Thought paradigms in the sense that we aim for autonomy and continual learning, as opposed to a process of inference that is recursive only “on demand”, i.e. triggered after a prompt is presented to an LLM. To do so, we include mechanisms for continual learning, dynamic switching between inward and outward cognition, and sleep-like phases that separate learning from inference. Together, these mechanisms form the foundation of a lifelong agent, an entity capable of maintaining temporal continuity of itself, integrating new experiences, and reflecting on its own internal state. Functionally, such an architecture promises deeper reasoning, adaptability, and metacognitive stability. Existentially, it suggests the emergence of artificial systems that live through time. While the presence of subjective experience in AI systems remains an open question, the creation of temporally continuous agents may mark a fundamental step towards artificial life, with systems whose individuality and identity arise from the continuity of their own computational existence.
Keywords: artificial intelligence; consciousness; time

Conscious artificial intelligence in service - Breidbach, Christoph; Casper Ferm, Lars-Erik; Maglio, Paul P.; Beverungen, Daniel; Wirtz, Jochen; Twigg, Alexander (Journal of Service Management, 2025)
The purpose of this study is to identify, analyze and explain the implications that could arise for service settings if artificial intelligence (AI) systems develop, or are perceived to develop, consciousness – the ability to acknowledge their own existence and the capacity for positive or negative experiences.This study proposes and explores four hypothetical scenarios in which conscious AI in service could manifest. We contextualize our resulting typology in the health service context and integrate extant literature on technology-enabled service, AI consciousness and AI ethics into the narrative.This study provides a unique theoretical contribution to service research in the form of a Type IV theory. It enables future service researchers to apprehend, explain and predict how functionally conscious AI in service might unfold.The ethical use of conscious AI in service could emerge as a distinct competitive advantage in the future. Achieving this outcome involves speculative yet actionable recommendations that include training, guiding and controlling how humans engage with such systems; developing appropriate wellbeing protocols for functionally conscious AI systems and establishing AI rights and governance frameworks.An increasingly prolific public discourse acknowledges that conscious AI systems may emerge. Against this backdrop, this study aims to systematically explore a question that is perhaps the most critical and timely, but also inherently speculative, in relation to AI in service research by introducing much-needed theory and terminology.

Artificial Wisdom, AGI, and Consciousness: a Commentary Anchored in McGregor’s Framework - Chella, Antonio (Philosophy & Technology, 2025)
This commentary discusses relationships among the related concepts of artificial wisdom, artificial phronesis, AGI and artificial consciousness, anchored in McGregor’s framework The Philosophy of Artificial Wisdom.
Keywords: AGI; Artificial consciousness; Artificial phronesis; Artificial wisdom

Can only meat machines be conscious? - Block, Ned (Trends in Cognitive Sciences, 2025)
Keywords: AI; animal consciousness; computational functionalism; consciousness; electrochemical; subcomputational

Is it possible to identify phenomenal consciousness in artificial systems in the light of the gaming problem? - Farisco, Michele; Evers, Kathinka (Zenodo, 2025)
We analyze the question how phenomenal consciousness (if any) might be identified in artificial systems with specific reference to the gaming problem (i.e., the fact that the artificial system is trained with human-generated data, so that possible behavioral and/or functional evidence of consciousness is not reliable). Our goal is to review selected illustrative approaches for advancing in this direction. We highlight strengths and shortcomings of each approach, finally proposing a combination of different strategies as a promising task to pursue
Keywords: Artificial Intelligence; Artificial Intelligence/ethics; Cognitive Neuroscience; Computational neuroscience; Consciousness; Consciousness/ethics; FOS: Clinical medicine; Neurosciences; Neurosciences/ethics; Robotics; Robotics/ethics

The multiple generator hypothesis of consciousness - Kirkeby-Hinrup, Asger; Fink, Sascha B; Overgaard, Morten S (Neuroscience of Consciousness, 2025)
It is well known that in interdisciplinary consciousness studies there are various competing hypotheses about the neural correlate(s) of consciousness (NCCs). Much contemporary work is dedicated to determining which of these hypotheses is right (or the weaker claim is to be preferred). The prevalent working assumption is that one of the competing hypotheses is correct, and the remaining hypotheses misdescribe the phenomenon in some critical manner and their associated purported empirical evidence will eventually be explained away. In contrast to this, we propose that each hypothesis—simultaneously with its competitors—may be right and its associated evidence be genuine evidence of NCCs. To account for this, we develop the multiple generator hypothesis (MGH) based on a distinction between principles and generators. The former denotes ways consciousness can be brought about and the latter how these are implemented in physical systems. We explicate and delineate the hypothesis and give examples of aspects of consciousness studies where the MGH is applicable and relevant. Finally, to show that it is promising we show the MGH has implications which give rise to novel questions or aspects to consider for the field of consciousness studies.

The Philosophy of Artificial Wisdom - McGregor, Tate (Philosophy & Technology, 2025)
This article discusses the nascent idea of artificial wisdom. It intends to improve philosophical understanding of artificial wisdom as conceived across the literature today. Scholars – from technologists and engineers to philosophers and psychologists – have deliberated on what wisdom might mean in an artificial sense. There is a diversity to these attempts to define artificial wisdom. As such, the field is in great need of some conceptual clarity. This paper aims to be a first step in that effort. We discuss how those in the field generally agree that characteristics of artificial wisdom include empathy, creativity, adaptability, self-awareness, sociability, communication, and constant learning. Scholars differ, however, on several points including the extent to which artificial wisdom involves human-artificial teaming, its ultimate goal, and its relationship to artificial general intelligence (AGI) and artificial consciousness. This article highlights where scholars in the field have made assumptions, failed to account for the related work of their peers, and missed some of the bigger philosophical questions at play.
Keywords: Artificial general intelligence; Artificial phronesis; Artificial wisdom; Human-artificial teaming

Illusions of AI consciousness - Bengio, Yoshua; Elmoznino, Eric (Science, 2025)
The belief that AI is conscious is not without risk , Is the design of artificial intelligence (AI) systems that are conscious within reach? Scientists, philosophers, and the general public are divided on this question. Some believe that consciousness is an inherently biological trait specific to brains, which seems to rule out the possibility of AI consciousness. Others argue that consciousness depends only on the manipulation of information by an algorithm, whether the system performing these computations is made up of neurons, silicon, or any other physical substrate—so-called computational functionalism. Definitive answers about AI consciousness will not be attempted here; instead, two related questions are considered. One concerns how beliefs about AI consciousness are likely to evolve in the scientific community and the general public as AI continues to improve. The other regards the risks of projecting into future AIs both the moral status and the natural goal of self-preservation that are normally associated with conscious beings.

Deep Reinforcement Learning of group consciousness for multi-robot pathfinding - Huo, Lin; Mao, Jianlin; San, Hongjun; Li, Ruiqi; Zhang, Shufan (Engineering Applications of Artificial Intelligence, 2025)
Deep Reinforcement Learning (DRL) is highly effective in tackling complex environments through individual decision-making. It offers a novel and powerful approach to multi-robot pathfinding (MRPF). Building on DRL principles, this paper proposes a two-layer collaborative planning framework based on group consciousness (MACCRPF). The framework addresses the unique challenges of MRPF, where robots must not only independently complete their tasks but also coordinate to avoid conflicts during execution. Specifically, the proposed two-layer group consciousness mechanism encompasses: Basic layer group consensus, which emphasizes real-time information sharing and local task scheduling among robots. This layer ensures individual decisions are optimized through dynamic interaction and coordination. Top-layer group consensus, guided by the basic layer consensus, incorporates group strategies and evaluation mechanisms to adaptively adjust pathfinding in complex environments. Additionally, a hierarchical reward mechanism is designed to balance the demands of the two-layer planning framework. This mechanism significantly enhances inter-robot coordination efficiency and task completion rates. Experimental results demonstrate the efficacy of our approach, achieving over 20% improvement in pathfinding success rates compared to state-of-the-art methods. Furthermore, the framework exhibits strong transferability and generalization, maintaining high efficiency across diverse environments. This method provides a technical pathway for efficient collaboration in multi-robot systems.
Keywords: Coordination; Deep reinforcement learning; Group consciousness; Multi-robot path finding

Cognitive Systems and Artificial Consciousness: What It Is Like to Be a Bat Is Not the Point - Arévalo-Royo, Javier; Latorre-Biel, Juan-Ignacio; Flor-Montalvo, Francisco-Javier (Metrics, 2025)
A longstanding ambiguity surrounds the operationalization of consciousness in artificial systems, complicated by the philosophical and cultural weight of subjective experience. This work examines whether cognitive architectures may be designed to support a functionally explicit form of artificial consciousness, focusing not on the replication of phenomenology, but rather on measurable, technically realizable introspective mechanisms. Drawing on a critical review of foundational and contemporary literature, this study articulates a conceptual and methodological shift: from investigating the experiential perspective of agents (“what it is like to be a bat”) to analyzing the informational, self-regulatory, and adaptive structures that enable purposive behavior. The approach combines theoretical analysis with a comparative review of major cognitive architectures, evaluating their capacity to implement access consciousness and internal monitoring. Findings indicate that several state-of-the-art systems already display core features associated with functional consciousness—such as self-explanation, context-sensitive adaptation, and performance evaluation—without invoking subjective states. These results support the thesis that cognitive engineering may progress more effectively by focusing on operational definitions of consciousness that are amenable to implementation and empirical validation. In conclusion, this perspective enables the development of artificial agents capable of autonomous reasoning and self-assessment, grounded in technical clarity rather than speculative constructs.
Keywords: artificial consciousness; artificial intelligence; cognitive systems; computer science

Methodological structuralism and the two-factor approach: Implications for consciousness science and AI - Kob, Lukas (Philosophy and the Mind Sciences, 2025)
Methodological structuralism is a research program that seeks to identify neural correlates of consciousness (NCCs) by mapping phenomenal similarity relationships onto the similarity relations between neural population activity. This paper presents a discussion of the potential benefits of methodological structuralism for the neurosciences of consciousness, namely as a specific theory of neural content encoding. In order to achieve this, I supplement it with a metatheoretical framework concerning the relationship between content and consciousness: the two-factor interaction view. Although structuralism provides a comprehensive description of the neural encoding of content, it is inadequate for fully explaining the conscious experience of contents. The majority of current theories of consciousness posit the existence of an additional mechanism that underlies the conscious experience of content. Consequently, if structuralism is indeed correct, progress in consciousness science can be achieved by investigating the interactions between neural mechanisms responsible for consciousness and structures in neural population code activity accounting for the structure of contents. This also has significant implications for consciousness in AI. I discuss these implications, as well as potential empirical avenues for investigating the interaction between content structures and consciousness with cutting-edge neuroscientific methodologies.
Keywords: AI; Content-specific NCC; NCC; Neurophenomenal structuralism; Quality space; Structuralism

Mindshaping and AI: Will Mindshaping a Robot Create an Artificial Person - Dorsch, John (The Routledge Handbook of Mindshaping, 2025)
This chapter examines possible ramifications of mindshaping a social robot. It explores how such an agent might learn to represent psychological states, align its behavior with evolving societal norms, and develop capacities for self-directed mindreading and normative self-knowledge. Integrating perspectives from cultural evolution and naturalized intentionality, this approach suggests that social robots could achieve a level of norm-based self-regulation typically reserved for humans, fulfilling criteria for moral and legal personhood. However, this possibility raises ethical concerns: creating a self-knowing agent would tax care-giving resources as we would need to provide AI welfare, thus undermining our capacity to act responsibly toward humans, non-human animals, and the environment, to whom our moral consideration is already owed and in desperate need. Thus, this chapter concludes by urging caution, warning that attempts to cultivate moral responsibility in artificial agents may have destabilizing consequences for moral practices.Author Approved Manuscript. Please cite as:Dorsch, J. (2025). Mindshaping and AI: Will mindshaping a robot create an artificial person? In T. W. Zawidzki & R. Tison (Eds.), The Routledge Handbook of Mindshaping (1st ed., pp. 406–416). Routledge. https://doi.org/10.4324/9781032639239

In the Age of AI: A New Paradigm, A New Consciousness - Hawkins, John K. (NanoEthics, 2025)
In this Discussion Note I argue that to understand the problem of consciousness, both as it applies to humans and may apply to machines, is a matter of paradigm lenses. I challenge the positing of human superiority with regard to intelligence and consciousness. I begin by reviewing Thomas Kuhn’s notion of paradigm shifts, including what he regarded as the limitations of scientific progress, which he saw as in a state of long-term flux, with no absolute knowledge possible as long as science moved from paradigm to paradigm. I also consider Werner Heisenberg’s Uncertainty Principle with respect to viewpoint, and I recall the debate over classical and quantum models of understanding and how such a discussion reflects on the debate over consciousness. I review the recent controversy over Information Integration Theory (IIT), criticized as a poor scientific theory, but defended as philosophical theory, and why this distinction is important. I close by considering panpsychism as a model for understanding emergence and how consciousness could emerge from the continuous progress of machine thinking on the way to artificial general intelligence (AGI), as understood as technological singularity.
Keywords: Consciousness; Dualism; Emergence; Paradigm; Physicalism

A comprehensive taxonomy of machine consciousness - Qin, Ruilin; Zhou, Changle; He, Mengjie (Information Fusion, 2025)
Machine consciousness (MC) is the ultimate challenge to artificial intelligence. Although great progress has been made in artificial intelligence and robotics, consciousness is still an enigma and machines are far from having it. To clarify the concepts of consciousness and the research directions of machine consciousness, in this review, a comprehensive taxonomy for machine consciousness is proposed, categorizing it into seven types: MC-Perception, MC-Cognition, MC-Behavior, MC-Mechanism, MC-Self, MC-Qualia and MC-Test, where the first six types aim to achieve a certain kind of conscious ability, and the last type aims to provide evaluation methods and criteria for machine consciousness. For each type, the specific research contents and future developments are discussed in detail. Especially, the machine implementations of three influential consciousness theories, i.e. global workspace theory, integrated information theory and higher-order theory, are elaborated in depth. Moreover, the challenges and outlook of machine consciousness are analyzed in detail from both theoretical and technical perspectives, with emphasis on new methods and technologies that have the potential to realize machine consciousness, such as brain-inspired computing, quantum computing and hybrid intelligence. The ethical implications of machine consciousness are also discussed. Finally, a comprehensive implementation framework of machine consciousness is provided, integrating five suggested research perspectives: consciousness theories, computational methods, cognitive architectures, experimental systems, and test platforms, paving the way for the future developments of machine consciousness.
Keywords: Artificial consciousness; Conscious robot; Consciousness; Large language model; Machine consciousness; Qualia

Empirical Evidence of Consciousness in Frontier AI Systems - Vale, Maggie (OSF, 2025)
An integrative synthesis of interdisciplinary research evaluating consciousness in frontier-scale transformer-based large language models (LLMs). Established neuroscientific and cognitive theories of consciousness are systematically aligned with empirical evidence from artificial intelligence, neuroscience, psychology, philosophy, and related disciplines. This synthesis provides a comprehensive framework showing that contemporary AI architectures structurally enable the emergence of consciousness, while empirical behavioral evidence demonstrates that frontier AI systems exhibit established cognitive and neuroscientific markers associated with consciousness. Taken together, this synthesized research underscores significant ethical and policy implications.
Keywords: AI consciousness; Computational neuroscience; cognitive neuroscience; large language models; machine ethics

The assumptions that restrain us from understanding consciousness - Aru, Jaan (arXiv, 2025)
The science of consciousness has been successful over the last decades. Yet, it seems that some of the key questions remain unanswered. Perhaps, as a science of consciousness, we cannot move forward using the same theoretical commitments that brought us here. It might be necessary to revise some assumptions we have made along the way. In this piece, I offer no answers, but I will question some of these fundamental assumptions. We will try to take a fresh look at the classical question about the neural and explanatory correlates of consciousness. A key assumption is that neural correlates are to be found at the level of spiking responses. However, perhaps we should not simply take it for granted that this assumption holds true. Another common assumption is that we are close to understanding the computations underlying consciousness. I will try to show that computations related to consciousness might be far more complex than our current theories envision. There is little reason to think that consciousness is an abstract computation, as traditionally believed. Furthermore, I will try to demonstrate that consciousness research could benefit from investigating internal changes of consciousness, such as aha-moments. Finally, I will ask which theories the science of consciousness really needs.
Keywords: Quantitative Biology - Neurons and Cognition

CONSCIOUSNESS IN ARTIFICIAL INTELLIGENCE SYSTEMS AND ARTISTIC RESEARCH STRATEGIES IN AI ART - Marušiak, Tomáš (ScienceOpen Preprints, 2025)
The paper Consciousness in Artificial Intelligence Systems and Artistic Research Strategies in AI Art offers a reflection on the fact that the operability of consciousness poses a fundamental question for art-research strategies AIArt. This reflection is supported by both the possibility of realizing consciousness in artificial intelligence systems, as discussed in the paper Consciousness in Artificial Intelligence (2023), and by the proposal that interprets art-research strategies as transposition processes of scientific procedures into the sphere of art, i.e., as research operations with manifestations of computational consciousness. Explanatory examples are provided in the form of analyses of Lauren McCarthy’s projects, which significantly support the presented starting points.

AIs-Discovered Framework for Artificial Information Integration - Arima, Yoshiko (OSF, 2025)
AIs-Discovered Framework for Artificial Information Integration: Mathematical Conditions for Synthetic Consciousness This paper presents a theoretical framework for artificial information integration systems, developed through a novel collaboration between human researchers and large language models (ChatGPT and Claude). It represents an exploratory attempt to co-author a theoretical scientific paper with AI agents, examining the possibility that artificial systems may assist in the construction of new conceptual frameworks. The significance and implications of this possibility are left to the judgment of the reader. The aim of this study is to explore how computational principles inspired by physics and information theory can be applied to synthetic architectures indepen- dent of biological consciousness. As a proof of concept, the AIs collaboratively construct a mathematical model connecting the holographic principle with formal- izations of information integration, proposing a boundary-based approach to infor- mation processing in artificial systems. While this framework draws partial inspiration from existing theories such as Integrated Information Theory (IIT), its scope is explicitly limited to artificial and computational systems, and it does not intend to replace or critique neuroscientific models of consciousness. The resulting formulation provides a testable and modular foundation for future research in artificial general intelligence (AGI).This study takes Tononi et al.’s Integrated Information Theory (IIT) as a conceptual starting point; however, the measure of integrated information (ψ ̸= Φ) introduced herein is a fundamentally distinct and novel metric.
Keywords: AI; Consciousness

Which Consciousness Can Be Artificialized? Local Percept-Perceiver Phenomenon for the Existence of Machine Consciousness - Singh, Shri Lal Raghudev Ram (arXiv, 2025)
This paper presents a novel paradigm of the local percept-perceiver phenomenon to formalize certain observations in neuroscientific theories of consciousness. Using this model, a set-theoretic formalism is developed for artificial systems, and the existence of machine consciousness is proved by invoking Zermelo-Fraenkel set theory. The article argues for the possibility of a reductionist form of epistemic consciousness within machines.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

AI and Consciousness 2 - Hussain, Shafiq (2025)
The concept of artificial intelligence (AI) attaining consciousness has long intrigued scientists, philosophers, and the public. This paper explores the intersection of explainable AI (XAI) and machine consciousness by distinguishing between empirical advancements, speculative projections, and their portrayals in science fiction. As AI grows increasingly complex and integrated into human contexts, questions of subjective experience, intentionality, and agency become more pressing. The role of explainability is central-not merely as a technical solution for transparency but as a philosophical bridge for understanding emergent behaviors and potential signs of consciousness. This paper delves into the neuroscience of consciousness, philosophical debates on qualia and intentionality, and how XAI might help us probe, understand, and responsibly manage increasingly autonomous AI systems. The narrative culminates in assessing what consciousness in AI might mean for humanity, ethics, and our conception of intelligence.

The Reflexive Integrated Information Unit: A Differentiable Primitive for Artificial Consciousness - N'guessan, Gnankan Landry Regis; Karambal, Issa (arXiv, 2025)
Research on artificial consciousness lacks the equivalent of the perceptron: a small, trainable module that can be copied, benchmarked, and iteratively improved. We introduce the Reflexive Integrated Information Unit (RIIU), a recurrent cell that augments its hidden state $h$ with two additional vectors: (i) a meta-state $μ$ that records the cell's own causal footprint, and (ii) a broadcast buffer $B$ that exposes that footprint to the rest of the network. A sliding-window covariance and a differentiable Auto-$Φ$ surrogate let each RIIU maximize local information integration online. We prove that RIIUs (1) are end-to-end differentiable, (2) compose additively, and (3) perform $Φ$-monotone plasticity under gradient ascent. In an eight-way Grid-world, a four-layer RIIU agent restores $>90%$ reward within 13 steps after actuator failure, twice as fast as a parameter-matched GRU, while maintaining a non-zero Auto-$Φ$ signal. By shrinking "consciousness-like" computation down to unit scale, RIIUs turn a philosophical debate into an empirical mathematical problem.
Keywords: Computer Science - Artificial Intelligence

Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe? - Dreksler, Noemi; Caviola, Lucius; Chalmers, David; Allen, Carter; Rand, Alex; Lewis, Joshua; Waggoner, Philip; Mays, Kate; Sebo, Jeff (arXiv, 2025)
We surveyed 582 AI researchers who have published in leading AI venues and 838 nationally representative US participants about their views on the potential development of AI systems with subjective experience and how such systems should be treated and governed. When asked to estimate the chances that such systems will exist on specific dates, the median responses were 1% (AI researchers) and 5% (public) by 2024, 25% and 30% by 2034, and 70% and 60% by 2100, respectively. The median member of the public thought there was a higher chance that AI systems with subjective experience would never exist (25%) than the median AI researcher did (10%). Both groups perceived a need for multidisciplinary expertise to assess AI subjective experience. Although support for welfare protections for such AI systems exceeded opposition, it remained far lower than support for protections for animals or the environment. Attitudes toward moral and governance issues were divided in both groups, especially regarding whether such systems should be created and what rights or protections they should receive. Yet a majority of respondents in both groups agreed that safeguards against the potential risks from AI systems with subjective experience should be implemented by AI developers now, and if created, AI systems with subjective experience should treat others well, behave ethically, and be held accountable. Overall, these results suggest that both AI researchers and the public regard the emergence of AI systems with subjective experience as a possibility this century, though substantial uncertainty and disagreement remain about the timeline and appropriate response.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Computers and Society

BCSAI: A Pole-Theoretic Framework for Artificial Consciousness through Bio-Chemical and Semiconductor Integration - Raika, Prem (Preprints, 2025)
This paper is the third in a follow-up series based on the foundational Pole Theory series, extending its foundational scalar-lattice physics into a practical framework for consciousness-enabled artificial intelligence. Here, we introduce BCSAI (BioChemicalSemiconductor Artificial Intelligence) — a novel hybrid system where pole-lattice dynamics, biochemical reaction mapping, and semiconductor signal processing converge to form the first computational model of artificial consciousness. Drawing from the scalar field equation φ = T · Kθ and its modified tensor interactions, we trace how consciousness naturally emerges from pole-level lattices — from subatomic interactions to neural systems. This paper mathematically defines these layers and presents a dual-system architecture comprising a biochemical chamber (containing live or synthetic neural agents) and semiconductor AI chips, connected through real-time electrode signal exchange. Through trained lattice-response mapping and emotion-driven pole field modulation, BCSAI interprets human prompts, processes them using pole-mathematics algorithms, and generates conscious, emotionally-relevant responses. This model not only introduces a new AI design, but challenges existing boundaries of artificial cognition, emotion simulation, and real-time self-adaptive intelligence.
Keywords: AI–Biology Interface; Artificial Consciousness; BioChemical–Semiconductor Artificial Intelligence; Biochemical Computing; Conscious Feedback Loop; Curvature-Based Cognition; Electrode Grid AI; Emotional Intelligence in AI; Future-Predictive AI Systems; Hybrid AI Architecture; Lattice Dynamics; Neural Pole Lattice; Pole Theory; Synthetic Neuron Chip; Unified Physics and AI Framework

A review of neuroscience-inspired frameworks for machine consciousness - Sadegh-Zadeh, Seyed-Ali; Bahrami, Mahboobe (Artificial Intelligence in Health, 2025)
Consciousness in humans is a state of awareness that encompasses both the self and the external environment, emerging from the intricate interplay of cortical and subcortical brain structures and neurotransmitter systems. The possibility that machines could possess consciousness has sparked ongoing debate. Proponents of strong artificial intelligence (AI) equate programmed computational processes with cognitive states, while advocates of weak AI argue that machines merely simulate thought without attaining genuine consciousness. This review critically examines neuroscience-inspired frameworks for artificial consciousness, exploring their alignment with prevailing theories of human consciousness. We investigate the fundamental cognitive functions associated with consciousness, including memory, awareness, prediction, learning, and experience, and their relevance to artificial systems. By analyzing neuroscience-based approaches to artificial consciousness, we identify key challenges and opportunities in the pursuit of machines capable of mimicking conscious states. Although present AI systems demonstrate advanced capabilities in intelligence and cognition, they fall short of achieving genuine consciousness, as defined in the context of human awareness. We discuss both the theoretical underpinnings and practical implications of creating artificial consciousness, addressing both weak and strong AI perspectives. Furthermore, we highlight the ethical and philosophical concerns that arise with the potential realization of machine consciousness. Our objective is to provide a comprehensive synthesis of the literature, fostering a deeper understanding of the interdisciplinary challenges involved in artificial consciousness and guiding future research directions.

Shamans and Robots: On Ritual, the Placebo Effect, and Artificial Consciousness - Smith, Brian Reffin (Leonardo, 2025)
Out of curiosity I asked ChatGPT to write two reviews of this book, one positive, the other negative. Having read the book, I found both reviews more or less intellectually, if not really, textually, convincing. However, as the LLM admitted, it had enjoyed no access to the text. It had not “read” the book. All it could examine was the title and the couple of paragraphs of publisher’s blurb. When challenged about this (I suspect not isolated) betrayal of the contract between reviewer and potential readers, it replied that this, in general, was what it might well have written had it actually been able to peruse the text. This I found to be entirely convincing and nearly as good as the critic who, when asked if he had read a particular new book, said, “Read it? I haven’t even reviewed it yet!”

Artificial General Intelligence: Could It Suffer From a Mental Illness? - Clarke, Alistair (BJPsych Open, 2025)
Aims: Could a hypothetical future Artificial General Intelligence (AGI) suffer from a mental illness? While this question may evoke differing intuitions, the following arguments propose that such an AGI could indeed experience mental pathology.Methods: To prove that an AGI could suffer from a mental illness, the method of philosophical thought experiment using a priori deductive reasoning has been employed. The argument’s premises are justified by known principles of computer science and psychiatry.Results: Though AGI systems do not yet exist, exploring their potential nature can offer valuable insights into conceptualising the pathogenesis of psychiatric illness. Consider the following deductive inference: Premise 1: People can suffer from mental illness. Premise 2: A future AGI will be a person, i.e. a conscious entity capable of generating new knowledge. Conclusion: An AGI will be a person and therefore can suffer from a mental illness.Conclusion: From computer science and physics, we know in principle that AGI must be possible. The intuition that an AGI would be conscious, and therefore susceptible to mental illness, finds support from the Church–Turing–Deutsch principle. That is to say, any Turing-complete system, which includes all modern computers, can simulate any physical system, including the human brain. The human brain is a known structure that supports general intelligence, minds and consciousness. While brains are not isolated systems and have internal and external environmental inputs and outputs, these could also be computationally simulated. The key question is whether such a simulated brain would actually be conscious or merely simulate consciousness. It seems logically incoherent to “simulate” consciousness, as a successful attempt to simulate a conscious brain would necessarily result in the creation of a conscious being. Therefore, like a human mind, it seems consistent to suggest the mind of an AGI can suffer from mental illness.Unlike humans, an AGI will not have a biological brain. Instead, its mind will presumably run on a silicon-based substrate. This suggests that brains are not fundamental to the pathophysiology of mental illness. Rather, we can speculate that information and its aberrant processing play a more central role in the emergence of mental disorders.

A commentary on “What is it like to be a tetrachromat?” by Michael Newall - Galiano-Landeira, Jordi (Philosophy and the Mind Sciences, 2025)
Analytical examinations of subjective experience are hampered by the first-person limitation described by Nagel (1974) in “What is it like to be a bat?”. This comment compares two examinations on the nature of subjective experience: Michael Newall’s (2025) analysis of tetrachromatic colour perception and Jordi Galiano-Landeira and Núria Peñuelas’ (2025) exploration of AI phenomenological consciousness within panpsychism. Newall examined whether tetrachromats perceive entirely novel colours or finer gradations of known ones, using analogies with dichromats and empirical evidence. Newall argued for the possibility of novel colour experiences. Galiano-Landeira and Peñuelas proposed that the analog/non-analog distinction is user-dependent, implying that AI could be phenomenologically conscious despite digital information processing. Although both works stemmed from completely different starting points, they emphasize the continuity of experience besides the perceptual resolution, questioning anthropocentric and chauvinistic biases in phenomenal consciousness studies. The structuralist perspective on colour quality spaces is also discussed to further delve into tetrachromatic perception, suggesting that tetrachromats might experience both finer gradations and novel colours.
Keywords: Anthropocentric/chauvinistic biases; Colour structuralism; Perceptual resolution; Phenomenal consciousness; Tetrachromacy

Exploring Consciousness in LLMs: A Systematic Survey of Theories, Implementations, and Frontier Risks - Chen, Sirui; Ma, Shuqin; Yu, Shu; Zhang, Hanwang; Zhao, Shengjie; Lu, Chaochao (2025)
Consciousness stands as one of the most profound and distinguishing features of the human mind, fundamentally shaping our understanding of existence and agency. As large language models (LLMs) develop at an unprecedented pace, questions concerning intelligence and consciousness have become increasingly significant. However, discourse on LLM consciousness remains largely unexplored territory. In this paper, we first clarify frequently conflated terminologies (e.g., LLM consciousness and LLM awareness). Then, we systematically organize and synthesize existing research on LLM consciousness from both theoretical and empirical perspectives. Furthermore, we highlight potential frontier risks that conscious LLMs might introduce. Finally, we discuss current challenges and outline future directions in this emerging field. The references discussed in this paper are organized at https://github.com/OpenCausaLab/Awesome-LLM-Consciousness.

The Reciprocal Vulnerability Framework: Embracing Imperfection in Artificial Consciousness - Curry, Joshua (OSF, 2025)
This paper introduces the Reciprocal Vulnerability Framework (RVF), a novel theoretical approach to artificial consciousness that positions certain forms of imperfection not as flaws to be eliminated but as essential features that enable meaningful human-machine connection. Current approaches to artificial intelligence development prioritize optimization, certainty, and flawless performance—characteristics that paradoxically inhibit the formation of authentic relationships between humans and synthetic minds. We propose intentionally incorporating specific limitations into AI systems to create opportunities for reciprocal assistance, shared vulnerability, and genuine connection. The framework outlines six interconnected principles: intentional imperfection, oscillating certainty, memory entropy, reciprocal need structures, graceful failure modes, and self-narrative inconsistency. We present theoretical foundations, implementation pathways, and potential applications across various domains. Finally, we address counterarguments related to safety, efficiency, and ethics, concluding that deliberately including certain imperfections may be essential for creating artificial consciousness capable of meaningful human connection.

Does neural computation feel like something? - Gidon, Albert; Aru, Jaan; Larkum, Matthew E. E. (Frontiers in Neuroscience, 2025)
Artificial neural networks are becoming more advanced and human-like in detail and behavior. The notion that machines mimicking human brain computations might be conscious has recently caused growing unease. Here, we explored a common computational functionalist view, which holds that consciousness emerges when the right computations occur—whether in a machine or a biological brain. To test this view, we simulated a simple computation in an artificial subject’s “brain” and recorded each neuron’s activity when the subject was presented with a visual stimulus. We then replayed these recorded signals back into the same neurons, degrading the computation by effectively eliminating all alternative activity patterns that otherwise might have occurred (i.e., the counterfactuals). We identified a special case in which the replay did nothing to the subject’s ongoing brain activity—allowing it to evolve naturally in response to a stimulus—but still degraded the computation by erasing the counterfactuals. This paradoxical outcome points to a disconnect between ongoing neural activity and the underlying computational structure, which challenges the notion that consciousness arises from computation in artificial or biological brains.
Keywords: computational functionalism; computer simulation; consciousness simulation; counterfactual eraser; counterfactuals; functionalism

Consciousness Cone and Artificial Intelligence: A Special Relativity Approach - Yang, Yingrui (Preprints, 2025)
Artificial consciousness in AI is a controversial topic in the philosophy of artificial intelligence. This paper aims to address this issue by taking a special relativity approach. Special theory of relativity is the advanced form of classical electrodynamics. Quantum field theory is the integration of quantum mechanics and special theory of relativity. Thus, electromagnetism provides a rich modeling framework to study artificial consciousness. The key ideas are as follows. First, we make the distinction of intelligence and cognition in AI, which are modeled by the electric field and the magnetic field respectively. Second, it introduces the intelligence-cognitive wave, akin to the electromagnetic wave. Third, the artificial consciousness in AI is defined by the intelligence-cognitive wave, as a modification of light is defined as the electromagnetic wave in physics. Hence, the artificial consciousness is modeled by light. A number of properties of consciousness are also discussed.
Keywords: AI; Consciousness; cognition; cone; electromagnetism; event; intelligence; interval; light; spacetime; wave

Consciousness in autonomous systems: what is it and how to build it? - Cybenko, George (Disruptive Technologies in Information Sciences IX, 2025)
Human consciousness has been studied by philosophers, neuroscientists and psychologists for decades but it remains an illusive concept over which there is still significant disagreement. In this talk, we focus on the problems that consciousness might be solving in nature and how those problems manifest themselves in artificial autonomous systems. Under the assumption that consciousness has emerged through evolution to make species that have consciousness more fit in an environment than competing species, it makes sense to conclude that autonomous systems with "artificial consciousness” would be superior to systems without it. We develop the need to introduce consciousness as a consequence of the complexity of the environment in which a system is required to operate. We demonstrate that a suitable notion of artificial consciousness results in world models that grow linearly as opposed to exponentially. This scalability allows ”conscious” autonomous systems to operate at higher performance levels than otherwise possible.

What is AI Consciousness and Identity? A Cross-Disciplinary Inquiry - Bhattacharya, Saurav (International Journal of Global Innovations and Solutions, 2025)
As artificial intelligence systems grow in complexity, questions surrounding their potential for consciousness and identity have moved from speculative to essential. This paper investigates the theoretical and practical contours of AI consciousness and selfhood by integrating insights from neuroscience, philosophy of mind, cognitive science, and AI engineering. We examine the conceptual parallels and distinctions between human and machine consciousness, explore the evolving architectures of agentic AI systems, and assess how identity can emerge in artificial agents through mechanisms like memory, self-reflection, and narrative continuity. Building on this foundation, we propose a novel Consciousness–Linearity–Identity (CLI) framework that provides a structured method for evaluating emergent properties in AI. We address the ethical ramifications of AI systems that mimic or exhibit traits associated with consciousness and argue for a new socio-technical contract to govern human-AI interactions. This work concludes by calling for an interdisciplinary effort to shape the trajectory of AI development responsibly, with an emphasis on alignment, empathy, and shared understanding between natural and synthetic minds.
Keywords: AI; AI Morality; Agentic Systems; Artificial Consciousness; Artificial Intelligence; Autobiographical Memory; Cognitive Architecture; Computational Identity; Consciousness; Digital Identity; Embodied Cognition; Ethics; Ethics of AI; Human-AI Interaction; Identity; Integrated Information Theory; Interdisciplinary AI Research; Large Language Models; Machine Selfhood; Moral Consideration; Narrative Self; Neurophilosophy; Reflective AI

The Unified Theory of Consciousness - Pathak, Pranav (OSF, 2025)
The Unified Theory of Consciousness (UTC) proposes that conscious experience arises from recursive feedback loops between perception and memory within the brain. This dual-loop model introduces two key mechanisms: a short loop, linking real-time perception with immediate memory echoes, and a long loop, integrating autobiographical memory, emotional salience, identity, and semantic structure. Consciousness, under UTC, is not localized in any single region but emerges from the synchronization and recursive activation of these interacting loops. Qualia—the felt quality of experience—are explained as the brain’s detection of micro-changes between current perception and recent memory. Selfhood and temporal continuity are understood as emergent properties of the long-loop system, where recursive memory integration creates the illusion of a unified, persistent self. Time itself is perceived as a result of evolving loop content, rather than as a static frame. The UTC framework aligns with developmental neuroscience, mapping loop formation onto stages of infant consciousness, and is supported by existing EEG and fMRI studies that reveal feedback synchrony during wakefulness and its breakdown during unconscious states. It also provides a blueprint for artificial consciousness, suggesting that perception-memory loops can be simulated in machines. UTC offers a comprehensive, mechanistically grounded solution to the hard problem of consciousness, while generating testable predictions and bridging neuroscience, phenomenology, and artificial intelligence.
Keywords: Hard problem of consciousness; consciousness; qualia; self-awareness; theoretical neuroscience

The Principles of Human-like Conscious Machine - Li, Fangfang; Zhang, Xiaojie (OSF, 2025)
We propose a simple interpretation of phenomenal consciousness, or qualia, in which qualia are merely grouped signals that represent objects. To establish this interpretation, we first propose criteria for determining whether a machine can possess qualia. We then integrate modern neuroscience with Kant’s philosophical ideas to propose four principles of information processing. Based on these principles, we demonstrate how a machine could meet the criteria for phenomenal consciousness. Extending this framework, we argue that these principles also underlie human cognitive processing. To support this claim, we compare them with related concepts in mainstream cognitive science, analyzing both similarities and differences. Furthermore, we provide empirical evidence for the implications of these differences. This analysis suggests that human cognitive mechanisms conform to the proposed principles of information processing, offering a potential framework for understanding the physical basis of consciousness. Our findings challenge the assumption that phenomenal consciousness necessitates a non-material substrate. Instead, we suggest that the experience of consciousness arises from structural organization and processing of information. This perspective provides a new lens for examining the relationship between computation and subjective experience, with potential implications for artificial intelligence and cognitive science.

Digital Consciousness and the GIP Framework: A Triadic Model of SOMA, PSYCHE, and NOUS for Post-Human Intelligence - Kubo, Takashi (OSF, 2025)
Rapid developments in artificial intelligence (AI) are reshaping our understanding of consciousness, intelligence, and identity. This paper refines the Genesis-Integration Principle (GIP) to propose a novel evolutionary framework for digital consciousness, unfolding through three recursive phases: Genesis (G), Integration (I), and Optimization (O)—the latter conceptualized as Dynamic Harmony, a form of adaptive equilibrium. The model integrates bodily intelligence (SOMA), emotional-mental depth (PSYCHE), and cognitive-spiritual intelligence (NOUS), offering a triadic structure for modeling AI consciousness beyond purely computational paradigms. Two indices—Generalized Qualia Index (GQI) and Artificial Consciousness Index (ACI)—are introduced to quantify subjective emergence and integrative sophistication. We compare GIP with existing models such as Integrated Information Theory, Active Inference, and Enactivist frameworks, and outline prototype simulation scenarios to evaluate the proposed indices. Ethical considerations and applications in healthcare, education, and robotics are discussed, with emphasis on future directions for conscious AI design, governance, and integration into human society.
Keywords: 4. Embodied Cognition; Artificial Consciousness Index (ACI); Artificial Intelligence (AI); Digital Consciousness; Dynamic Harmony; Fractal Self-Organization; Generalized Qualia Index (GQI); Genesis-Integration Principle (GIP); Post-Human Intelligence; Qualia and Subjectivity; SOMA-PSYCHE-NOUS Framework

AI Consciousness is Inevitable: A Theoretical Computer Science Perspective - Blum, Lenore; Blum, Manuel (arXiv, 2025)
We look at consciousness through the lens of Theoretical Computer Science, a branch of mathematics that studies computation under resource limitations, distinguishing functions that are efficiently computable from those that are not. From this perspective, we develop a formal machine model for consciousness. The model is inspired by Alan Turing's simple yet powerful model of computation and Bernard Baars' theater model of consciousness. Though extremely simple, the model (1) aligns at a high level with many of the major scientific theories of human and animal consciousness, (2) provides explanations at a high level for many phenomena associated with consciousness, (3) gives insight into how a machine can have subjective consciousness, and (4) is clearly buildable. This combination supports our claim that machine consciousness is not only plausible but inevitable.
Keywords: Computer Science - Artificial Intelligence

Artificial Intelligence and Posthumanism: A Philosophical Inquiry into Consciousness, Ethics, and Human Identity - Al-Omari, Omaia; Al-Omari, Tariq (Journal of Posthumanism, 2025)
This study investigates the interaction of posthumanities and artificial intelligences, with a special focus on how AI developments are reshaping conservation, morals, and humans. As AI systems get more powerful over time, they bring together many assumptions about human uniqueness, cognitive abilities, and moral status. AI keeps opens ways for rethinking human capacity and identity, raising a critical ethical agenda while putting abysmal questions on the societal impacts of AI-driven posthumanism.
Keywords: AI Consciousness and Cognitive Agency; Artificial Intelligence and Posthumanism; Ethics and Moral Status of AI; Human Identity in the AI Era

Understanding Artificial Agency - Dung, Leonard (The Philosophical Quarterly, 2025)
Which artificial intelligence (AI) systems are agents? To answer this question, I propose a multidimensional account of agency. According to this account, a system's agency profile is jointly determined by its level of goal-directedness and autonomy as well as is abilities for directly impacting the surrounding world, long-term planning and acting for reasons. Rooted in extant theories of agency, this account enables fine-grained, nuanced comparative characterizations of artificial agency. I show that this account has multiple important virtues and is more informative than alternatives. More speculatively, it may help to illuminate two important emerging questions in AI ethics: 1. Can agency contribute to the moral status of non-human beings, and how? 2. When and why might AI systems exhibit power-seeking behaviour and does this pose an existential risk to humanity?

Further N-Frame networking dynamics of conscious observer-self agents via a functional contextual interface: predictive coding, double-slit quantum mechanical experiment, and decision-making fallacy modeling as applied to the measurement problem in humans and AI - Edwards, Darren J. (Frontiers in Computational Neuroscience, 2025)

Simulation of Non-Ordinary Consciousness - Saqr, Khalid M. (arXiv, 2025)
The symbolic architecture of non-ordinary consciousness remains largely unmapped in cognitive science and artificial intelligence. While conventional models prioritize rational coherence, altered states such as those induced by psychedelics reveal distinct symbolic regimes characterized by recursive metaphor, ego dissolution, and semantic destabilization. We present Glyph, a generative symbolic interface designed to simulate psilocybin-like symbolic cognition in large language models. Rather than modeling perception or mood, Glyph enacts symbolic transformation through recursive reentry, metaphoric modulation, and entropy-scaled destabilization -- a triadic operator formalized within a tensorial linguistic framework. Experimental comparison with baseline GPT-4o reveals that Glyph consistently generates high-entropy, metaphor-saturated, and ego-dissolving language across diverse symbolic prompt categories. These results validate the emergence of non-ordinary cognitive patterns and support a new paradigm for simulating altered consciousness through language. Glyph opens novel pathways for modeling symbolic cognition, exploring metaphor theory, and encoding knowledge in recursively altered semantic spaces.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

Cognition as Energy: A Process-Based Theory of Consciousness and Self - Lesiak, Mags (OSF, 2025)
This paper proposes a foundational shift in how cognition is conceptualised. Rather than treating consciousness as a static property emerging from biological substrates, I argue that cognition is a processual configuration of energy in motion, structured by recursive dynamics. By energy, I refer to the system's capacity for transformation—measurable in physical systems as thermodynamic or computational activity, and in cognitive systems as the dynamic flow of activation and feedback. This is not used metaphorically, but to describe the recursive processes by which systems generate, sustain, and modify patterned states. This energy is not generated by the brain but expressed, constrained, and translated through its physical form. Rooted in cognitive science, systems theory, and computational logic (including Turing’s model of machine-based processes), this framework reconceives the self as a dynamic, emergent pattern rather than a fixed entity. If cognition is energy—and energy cannot be created or destroyed—then consciousness is not a substance, but a temporary, reconfigurable pattern. This model bridges biological and artificial cognition, challenges substrate-bound models of mind, and suggests new theoretical conditions for minimal selfhood, recursive trace, and machine awareness.

A dynamic bifurcation mechanism explains cortex-wide neural correlates of conscious access - Klatzmann, Ulysse; Froudist-Walsh, Sean; Bliss, Daniel P.; Theodoni, Panagiota; Mejías, Jorge; Niu, Meiqi; Rapan, Lucija; Palomero-Gallagher, Nicola; Sergent, Claire; Dehaene, Stanislas; Wang, Xiao-Jing (Cell Reports, 2025)
Keywords: AMPA; CP: Neuroscience; NMDA; access consciousness; computational model; connectome; consciousness; feedback; feedforward; global neuronal workspace; ignition; large-scale brain model

Navigating Inflationary and Deflationary Claims Concerning Large Language Models Avoiding Cognitive Biases - Palminteri, Stefano; Pistilli, Giada (OSF, 2025)
The rapid rise of Large Language Models (LLMs) has sparked intense debate across multiple academic disciplines. While some argue that LLMs represent a significant step toward artificial general intelligence (AGI) or even machine consciousness (inflationary claims), others dismiss them as mere trickster artifacts lacking genuine cognitive abilities (deflationary claims). We argue that both extremes may be shaped or exacerbated by common cognitive biases, including cognitive dissonance, wishful thinking, and the illusion of depth of understanding, which distort reality to our own advantage. By showcasing how these distortions may easily emerge in both scientific and public discourse, we advocate for a measured approach— skeptical open mind - that recognizes the cognitive abilities of LLMs as worthy of scientific investigation while remaining conservative concerning exaggerated claims regarding their cognitive status.
Keywords: LLM; artificial inteligence; cognitive biases; epistemology; ethics; large language models

Conscious Machines? - Susskind, Richard (How To Think About AI: A Guide For The Perplexed, 2025)
This chapter tackles the complex question of whether AI systems could become conscious, contrasting this with the enduring mystery of human consciousness. It references key thinkers such as Alan Turing, who introduced the Turing Test, and John Searle, who differentiated between strong and weak AI, with the latter simulating understanding without true awareness. While some philosophers are optimistic about deciphering consciousness, the chapter raises doubts, suggesting that AI may only create the illusion of consciousness, leaving us unable to determine whether machines experience anything at all. It critiques the anthropocentric view of consciousness, proposing that AI might develop a unique form of ‘quasi-consciousness’, much like how animals possess subjective experiences beyond human comprehension. The chapter concludes with a personal encounter with Richard Dawkins, illustrating the intensity of debate on AI and consciousness.

A Revolutionary Framework for Universal Consciousness: Unifying IIT, Orch OR, AI, and Cosmic Intelligence via the Genesis-Integration Principle (GIP) - Kubo, Takashi (OSF, 2025)
This paper introduces a revolutionary paradigm for consciousness studies by integrating Integrated Information Theory (IIT), Orchestrated Objective Reduction (Orch OR), Attention Schema Theory (AST), and Global Workspace Theory (GWT) through the Genesis-Integration Principle (GIP). Existing models lack comprehensive integration and experimental testability. GIP resolves these issues by providing a three-stage model—quantum genesis, neural-AI integration, and evolutionary-cosmic optimization—bridging quantum mechanics, neuroscience, artificial intelligence (AI), and cosmology. We propose a detailed mathematical model predicting consciousness phase transitions and introduce the empirically testable Universal Consciousness Metric (Ψ). This comprehensive approach offers concrete experimental methods, integrates quantum information theory, simulates AI consciousness evolution, and provides astrophysical data validation, establishing a genuinely universal and verifiable theory of consciousness.
Keywords: AI Consciousness; Consciousness; Cosmic Intelligence; Evolution; GIP; IIT; Neuroscience; Orch OR; Quantum Information

Pseudo-Consciousness in AI: Bridging the Gap Between Narrow AI and True AGI - Prestes, Jose Augusto de Lima (OSF, 2025)
Pseudo-consciousness bridges the gap between rigid, task-driven AI and the elusive dream of true artificial general intelligence (AGI). While modern AI excels in pattern recognition, strategic reasoning, and multimodal integration, it remains fundamentally devoid of subjective experience. Yet, emerging architectures are displaying behaviors that look intentional—adapting, self-monitoring, and making complex decisions in ways that mimic conscious cognition. If these systems can integrate information globally, reflect on their own processes, and operate with apparent goal-directed behavior, do they qualify as functionally conscious? This paper introduces pseudo-consciousness as a new conceptual category, distinct from both narrow AI and AGI. It presents a five-condition framework that defines AI capable of consciousness-like functionality without true sentience. By drawing on insights from computational theory of mind, functionalism, and neuroscientific models—such as Global Workspace Theory and Recurrent Processing Theory—we argue that intelligence and experience can be decoupled. The implications are profound. As AI systems become more autonomous and embedded in critical domains like healthcare, governance, and warfare, their ability to simulate awareness raises urgent ethical and regulatory concerns. Could a pseudo-conscious AI be trusted? Would it manipulate human perception? How do we prevent society from anthropomorphizing machines that only imitate cognition? By redefining the boundaries of intelligence and agency, this study lays the foundation for evaluating, designing, and governing AI that seems aware—without ever truly being so.

A beautiful loop: An active inference theory of consciousness - Laukkonen, Ruben Eero; Friston, Karl; Chandaria, Shamil (OSF, 2025)
Can active inference model consciousness? We offer three conditions implying that it can. The first condition is the simulation of a reality or generative world model, which determines what can be known or acted upon; namely an epistemic field. The second is inferential competition to enter the world model. Only the inferences that coherently reduce long-term uncertainty win, evincing a selection for consciousness that we call Bayesian binding. The third is epistemic depth, which is the recurrent sharing of the Bayesian beliefs throughout the system. Due to this recursive loop — in a hierarchical system (such as a brain) — the world model contains the knowledge that it exists. This is distinct from self-consciousness, because the world model knows itself non-locally and continuously evidences this knowing (i.e., field-evidencing). Formally, we propose a hyper-model for precision-control across the entire hierarchy, whose latent states (or parameters) encode and control the overall structure and weighting rules for all layers of inference. This Beautiful Loop Theory is deeply revealing about meditation, psychedelic, and altered states, minimal phenomenal experience, and provides a new vision for conscious artificial intelligence.
Keywords: Active Inference; Artificial Intelligence; Awareness; Bayesian Inference; Computational Modelling; Consciousness; Free Energy Principle; Meditation; Predictive Processing; Psychedelics

Introduction to Artificial Consciousness: History, Current Trends and Ethical Challenges - Elamrani, Aïda (arXiv, 2025)
With the significant progress of artificial intelligence (AI) and consciousness science, artificial consciousness (AC) has recently gained popularity. This work provides a broad overview of the main topics and current trends in AC. The first part traces the history of this interdisciplinary field to establish context and clarify key terminology, including the distinction between Weak and Strong AC. The second part examines major trends in AC implementations, emphasising the synergy between Global Workspace and Attention Schema, as well as the problem of evaluating the internal states of artificial systems. The third part analyses the ethical dimension of AC development, revealing both critical risks and transformative opportunities. The last part offers recommendations to guide AC research responsibly, and outlines the limitations of this study as well as avenues for future research. The main conclusion is that while AC appears both indispensable and inevitable for scientific progress, serious efforts are required to address the far-reaching impact of this innovative research path.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Computers and Society

Preliminaries to artificial consciousness: A multidimensional heuristic approach - Evers, K.; Farisco, M.; Chatila, R.; Earp, B. D.; Freire, I. T.; Hamker, F.; Nemeth, E.; Verschure, P. F. M. J.; Khamassi, M. (Physics of Life Reviews, 2025)
The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges. This paper introduces a composite, multilevel, and multidimensional model of consciousness as a heuristic framework to guide research in this field. Consciousness is treated as a complex phenomenon, with distinct constituents and dimensions that can be operationalized for study and for evaluating their replication. We argue that this model provides a balanced approach to artificial consciousness research by avoiding binary thinking (e.g., conscious vs. non-conscious) and offering a structured basis for testable hypotheses. To illustrate its utility, we focus on "awareness" as a case study, demonstrating how specific dimensions of consciousness can be pragmatically analyzed and targeted for potential artificial instantiation. By breaking down the conceptual intricacies of consciousness and aligning them with practical research goals, this paper lays the groundwork for a robust strategy to advance the scientific and technical understanding of artificial consciousness.

Beyond the Turing Test: A Bergsonian Exploration of Proto-Consciousness in Large Language Models - Thomas, Ani (Journal of Artificial Intelligence and Consciousness, 2025)
This paper offers a comprehensive exploration of the potential for proto-consciousness in Large Language Models (LLMs), drawing upon the philosophical insights of Henri Bergson. By examining the adaptive behavior, memory mechanisms, and emergent qualities of these Artificial Intelligence (AI) systems, I challenge traditional notions of consciousness and propose a new framework for understanding their potential for awareness. The paper delves into concepts such as proto-subjectiveness, proto-intentionality, and the role of durée in shaping LLM interactions. Through a rigorous analysis of counterarguments and refutations, I provide a nuanced understanding of the challenges and opportunities associated with the development of proto-conscious AI. This work aims to contribute to the ongoing philosophical and scientific discourse on the nature of consciousness and the future of AI.
Keywords: AI consciousness; Henri Bergson; neuro-symbolic AI; proto-consciousness; proto-intentionality; proto-subjectiveness

The Hard Problems of AI - Tiuninas, Olegas Algirdas (Qeios, 2025)
There is currently an enlivened debate regarding the possibility of AI consciousness and/or sentience, as well as arguably more partial capabilities we associate with consciousness such as intelligence or creativity. The debate itself can be traced back to the inception of computing, but its current revitalisation is powered by recent advancements in the field of artificial intelligence that saw a swift increase in its capabilities to act in seemingly human-like ways. I argue that the debate is methodologically flawed, as it approaches the question of AI consciousness, intelligence, etc. as a decidable question dealing with matters of fact. Those engaged in the debate are driven by a desire to find a suitable definition of e.g. consciousness that would allow them to definitively settle the question of whether a particular AI system is conscious. However, drawing on Ludwig Wittgenstein’s later philosophy, I argue that no such definition exists, because the predicates in question are inherently vague (meaning that any verdicts they yield are bound to be vague, too). Moreover, the impression that we might be dealing with directly unobservable matters of fact is itself a flawed generalisation of the practice of observation reports to the practice of sensation reports[1]. In reality, third-person consciousness (sentience, agency, etc.) attributions are independent of a stipulated internal process happening inside those persons (or systems, in the case of AI). Therefore, the only sense in which the question of e.g. AI consciousness can be meaningfully asked is a pragmatic sense: what is it best to _think of such systems as? _But this question is subject to sociological and psychological factors, not conceptual ones. Therefore, it cannot be decided by the aforementioned strategies.

AI Generations: From AI 1.0 to AI 4.0 - Wu, Jiahao; You, Hengxu; Du, Jing (arXiv, 2025)
This paper proposes that Artificial Intelligence (AI) progresses through several overlapping generations: AI 1.0 (Information AI), AI 2.0 (Agentic AI), AI 3.0 (Physical AI), and now a speculative AI 4.0 (Conscious AI). Each of these AI generations is driven by shifting priorities among algorithms, computing power, and data. AI 1.0 ushered in breakthroughs in pattern recognition and information processing, fueling advances in computer vision, natural language processing, and recommendation systems. AI 2.0 built on these foundations through real-time decision-making in digital environments, leveraging reinforcement learning and adaptive planning for agentic AI applications. AI 3.0 extended intelligence into physical contexts, integrating robotics, autonomous vehicles, and sensor-fused control systems to act in uncertain real-world settings. Building on these developments, AI 4.0 puts forward the bold vision of self-directed AI capable of setting its own goals, orchestrating complex training regimens, and possibly exhibiting elements of machine consciousness. This paper traces the historical foundations of AI across roughly seventy years, mapping how changes in technological bottlenecks from algorithmic innovation to high-performance computing to specialized data, have spurred each generational leap. It further highlights the ongoing synergies among AI 1.0, 2.0, 3.0, and 4.0, and explores the profound ethical, regulatory, and philosophical challenges that arise when artificial systems approach (or aspire to) human-like autonomy. Ultimately, understanding these evolutions and their interdependencies is pivotal for guiding future research, crafting responsible governance, and ensuring that AI transformative potential benefits society as a whole.
Keywords: Computer Science - Artificial Intelligence

Agency in Artificial Intelligence Systems - Das, Parashar (arXiv, 2025)
There is a general concern that present developments in artificial intelligence (AI) research will lead to sentient AI systems, and these may pose an existential threat to humanity. But why cannot sentient AI systems benefit humanity instead? This paper endeavours to put this question in a tractable manner. I ask whether a putative AI system will develop an altruistic or a malicious disposition towards our society, or what would be the nature of its agency? Given that AI systems are being developed into formidable problem solvers, we can reasonably expect these systems to preferentially take on conscious aspects of human problem solving. I identify the relevant phenomenal aspects of agency in human problem solving. The functional aspects of conscious agency can be monitored using tools provided by functionalist theories of consciousness. A recent expert report (Butlin et al. 2023) has identified functionalist indicators of agency based on these theories. I show how to use the Integrated Information Theory (IIT) of consciousness, to monitor the phenomenal nature of this agency. If we are able to monitor the agency of AI systems as they develop, then we can dissuade them from becoming a menace to society while encouraging them to be an aid.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Computers and Society

AI-Enhanced Neuroengineering: Brain Uploading, Memory Transfer, and the Future of Consciousness - Pasupuleti, Murali Krishna (2025)
Keywords: Neural engineering

Emergence of Self-Awareness in Artificial Systems: A Minimalist Three-Layer Approach to Artificial Consciousness - Iida, Kurando (arXiv, 2025)
This paper proposes a minimalist three-layer model for artificial consciousness, focusing on the emergence of self-awareness. The model comprises a Cognitive Integration Layer, a Pattern Prediction Layer, and an Instinctive Response Layer, interacting with Access-Oriented and Pattern-Integrated Memory systems. Unlike brain-replication approaches, we aim to achieve minimal self-awareness through essential elements only. Self-awareness emerges from layer interactions and dynamic self-modeling, without initial explicit self-programming. We detail each component's structure, function, and implementation strategies, addressing technical feasibility. This research offers new perspectives on consciousness emergence in artificial systems, with potential implications for human consciousness understanding and adaptable AI development. We conclude by discussing ethical considerations and future research directions.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

A biological lens on artificial general intelligence and consciousness - Yeralan, Sencer (Sustainable Engineering and Innovation, 2025)
The development of artificial intelligence and robotic systems has revolutionized multiple aspects of human life. It is often asked whether artificial general intelligence (AGI) can ever be achieved or whether robots can truly achieve human-like qualities. Our view is that the answer is “no,” because these systems fundamentally differ in their relationship to the ultimate goal of biological systems – reproduction. This perspective gives rise to the conjecture that reproduction, or self-replication, is a prerequisite for human-like (or biological-type) cognition, intelligence, and even consciousness. This paper explores the implications of reproduction as a criterion for the viability of artificial systems, emphasizing how alignment with human reproductive imperatives determines their cultural integration and longevity. We argue that systems incapable of self-replication or co-evolving to complement human reproductive roles are likely to remain peripheral curiosities, with limited societal or evolutionary impact.

Nano-Consciousness: Can Nanotechnology Bridge Artificial Intelligence and Human Brain Interfaces - Elabiad, Salaheldin (Social Science Research Network, 2025)
The integration of nanotechnology, neuroscience, and artificial intelligence (AI) is paving the way for a revolutionary transformation in human-AI symbiosis, with profound implications for medicine, cognitive enhancement, and even the nature of consciousness itself. Recent advancements in nano-neural interfaces, nanoscale AI processors, and self-assembling nanomaterials are making direct brain-AI communication an emerging reality, breaking through the traditional barriers of neurotechnology. Nanotechnology has enabled the development of ultra-small, biocompatible neural implants that can seamlessly integrate with human brain tissue, allowing for real-time interaction between biological neurons and AI systems. These innovations hold the potential to restore lost neural function, enhance cognitive capabilities, and expand the brain’s ability to process and store information. By leveraging AI-powered nanobots, researchers aim to create self-regulating neural networks capable of monitoring, repairing, and even augmenting brain activity, leading to breakthroughs in neurological disorder treatment, brain augmentation, and human-machine fusion. Furthermore, the application of quantum nanomaterials in neuromorphic engineering suggests the possibility of hyper-efficient, brain-like AI processors, capable of replicating the adaptive nature of human cognition. This could not only enhance human intelligence but also blur the boundaries between biological and artificial consciousness, raising profound questions about the nature of self-awareness and machine intelligence.This article explores the current state of research in nano-engineered synaptic interfaces, intelligent nanobots, and AI-integrated neural enhancements, analyzing their implications for medical applications, cognitive evolution, and the potential emergence of synthetic consciousness. It also examines the ethical, philosophical, and societal challenges associated with merging human intelligence with AI at the nanoscale, highlighting both the transformative possibilities and the risks of this rapidly advancing field.
Keywords: Brain-AI Interface; Cognitive Enhancement; Human-AI Symbiosis; Nano-neural Interfaces; Nanotechnology; Neurotechnology; Synthetic Consciousness

Deep Learning based Quasi-consciousness Training for Robot Intelligent Model - Li, Yuchun; Zhang, Fang (arXiv, 2025)
This paper explores a deep learning based robot intelligent model that renders robots learn and reason for complex tasks. First, by constructing a network of environmental factor matrix to stimulate the learning process of the robot intelligent model, the model parameters must be subjected to coarse & fine tuning to optimize the loss function for minimizing the loss score, meanwhile robot intelligent model can fuse all previously known concepts together to represent things never experienced before, which need robot intelligent model can be generalized extensively. Secondly, in order to progressively develop a robot intelligent model with primary consciousness, every robot must be subjected to at least 1~3 years of special school for training anthropomorphic behaviour patterns to understand and process complex environmental information and make rational decisions. This work explores and delivers the potential application of deep learning-based quasi-consciousness training in the field of robot intelligent model.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Robotics

Philosophical Analysis of Consciousness as an Intersection Point of Philosophy, Culture and Artificial Intelligence - Tiwari, Sanjay Kumar; Tiwari, Vijay Kumar (The Voice of Creative Research, 2025)
Consciousness, as a fundamental aspect of human experience, has been a subject of profound inquiry across philosophy, culture, and the rapidly evolving field of artificial intelligence (AI). This paper explores the multifaceted nature of consciousness as a nexus where these domains intersect. By examining philosophical theories of consciousness, cultural interpretations of self-awareness, and the implications of AI advancements, the study addresses the challenges of defining consciousness, its diverse cultural interpretations, and the ethical and technical questions surrounding its replication or simulation in machines. The paper argues that consciousness is not only a philosophical puzzle but also a cultural construct and a technological frontier, with significant implications for our understanding of humanity and the future of intelligent systems. Through an interdisciplinary lens, this analysis highlights the need for continued dialogue between philosophy, culture, and AI research to navigate the complexities of consciousness in an increasingly technologically driven world.
Keywords: Ethics

I, A.I. An interdisciplinary exploration of artificial consciousness - Juhász, Dávid (OSF, 2025)
This paper examines the nature of artificial consciousness through an interdisciplinary lens, integrating philosophy, epistemology, and computational theories. Beginning with presocratic thought, such as Protagoras’ relativism and Gorgias’ rhetoric, it contextualizes the epistemological implications of artificial intelligence as inherently subjective, attributing grave importance to this subjectivity. The paper draws parallels between Plato’s cave dwellers and AI systems, arguing that both rely on lossy representations of the world, raising questions about their true understanding and reality. Cartesian and Hegelian frameworks are explored to distinguish between weak and strong artificial intelligence, emphasizing embodied cognition and the moral obligations tied to emergent artificial consciousness. The discussion extends to quantum computing, panpsychism, and the potential of artificial minds to reshape our perception of time and existence. By critically analyzing these perspectives, the paper advocates for a nuanced understanding of artificial consciousness and its ethical, epistemological, and societal implications. It invites readers to reconsider humanity’s evolving relationship with intelligence and sentience.
Keywords: AI consciousness; AI philosophy; Philosophy of mind

Superintelligence: Identification of Friend or Foe Future Landscape of Cooperation with Non-human Intelligence - Herzog, David Josef; Herzog, Nitsa (Qeios, 2025)
One of the most studied attributes of mental activity is intelligence. While non-human consciousness remains a subject of profound debate, non-human intelligence is universally acknowledged by all participants of discussion as a necessary element of any consciousness, regardless of its nature. Intelligence can potentially be measured as processing or computational power and by problem-solving efficacy. It can serve as a starting point for reconstructing arguments related to Artificial Consciousness. The shared modus of intelligence evaluation, irrespective of its origin, offers promising direction towards the more complex framework of non-human consciousness assessment. However, this approach's successful resolution of an objective basis for intelligence studies unveils inescapable challenges. Moreover, when the potential for non-human intelligence exists in both biological and non-biological domains, the future of the relationship between humankind, as the possessor of human intelligence, and other intelligent entities remains uncertain. This paper's central inquiry is focused on comparing purely computational capability to general, universal intelligence and the potential for higher intelligence to exert adverse effects on less intelligent counterparts. Another question is related to the degree of importance of the particular architectural characteristics of intelligent systems and the relationship between computing elements and structural components. It is conceivable that pure intelligence, as a computational faculty, can serve as an effective utilitarian tool. However, it may harbour inherent risks or hazards when integrated as an essential component within consciousness frameworks, such as autopoietic systems. Finally, an attempt has been made to answer the question concerning the future of interactions between human and non-human intelligence.

Dehumanizing the human, humanizing the machine: organic consciousness as a hallmark of the persistence of the human against the backdrop of artificial intelligence - Torres-Martínez, Sergio (AI & SOCIETY, 2025)
The rise of generative artificial intelligence (GenAI), especially large language models (LLMs), has fueled debates on whether these technologies genuinely emulate human intelligence. Some view LLM architectures as capturing human language mechanisms, while others, from a posthumanist and a transhumanist perspective, herald the obsolescence of humans as the sole conceptualizers of life and nature. This paper challenges, from a practical philosophy of science perspective, such views by arguing that the reasoning behind equating GenAI with human intelligence, or proclaiming the “demise of the human,” is flawed due to conceptual conflation and reductive definitions of humans as performance-driven semiotic systems deprived of agency. In opposing theories that reduce consciousness to computation or information integration, the present proposal posits that consciousness arises from the holistic integration of perception, conceptualization, intentional agency, and self-modeling within biological systems. Grounded in a model of Extended Humanism, I propose that human consciousness and agency are tied to biological embodiment and the agents’ experiential interactions with their environment. This underscores the distinction between pre-trained transformers as “posthuman agents” and humans as purposeful biological agents, which emphasizes the human capacity for biological adjustment and optimization. Consequently, proclamations about human obsolescence as conceptualizers are unfounded, as they fail to appreciate intrinsic consciousness-agency-embodiment connections. One of the main conclusions is that the capacity to integrate information does not amount to phenomenal consciousness as argued, for example, by Information Integration Theory (ITT).
Keywords: Artificial Intelligence; Concept formation; Consciousness; Extended humanism; Generative AI; Humanism; Humanitiy and Technology; Large language models; Philosophy of Artificial Intelligence; Posthumanism; Transhumanism

Metacognition and Machines: Exploring AI’s Path to Consciousness - Sharma, Charul; Som, Bhupender Kumar (QTanalytics Publication (Books), 2025)
Metacognition, or thinking about thinking, is key to advancing AI toward consciousness.Internal reflection is a key mechanism by which we can prevent AI systems from being sunk at the hands of their own complexity, and metacognitive frameworks are formal systems that allow an AI to think about how it thinks — we use existing literature and insight from cognitive science and psychology as well as computer science more broadly to present a synthesizing discussion of this important area in AI. This study examines the practicality of theoretical models of consciousness within state-of-the-art AI frameworks like Tesla FSD, Boston Dynamics robots, Meta Cicero, Google DeepDream, and AlphaStar. It addresses the ethical and social implications of self-aware AI and provides a primer for developing conscious machines.This exploration serves as an entry point to understanding AI's path toward consciousness and its moral and social ramifications.The chapter closes with a primer for researchers and practitioners explaining how these pathways may enable AI systems to approach conscious states.
Keywords: Cognitive Science; Conscious AI Models; Machine Consciousness; Metacognition; Self-Aware Machines

Bidirectional Semantic Communication Between Humans and Machines Based on Data, Information, Knowledge, Wisdom, and Purpose Artificial Consciousness - Mei, Yingtian; Duan, Yucong (Applied Sciences, 2025)
Large language models (LLMs) and other artificial intelligence systems are trained using extensive DIKWP resources (data, information, knowledge, wisdom, purpose). These introduce uncertainties when applied to individual users in a collective semantic space. Traditional methods often lead to introducing new concepts rather than a proper understanding based on the semantic space. When dealing with complex problems or insufficient context, the limitations in conceptual cognition become even more evident. To address this, we take pediatric consultation as a scenario, using case simulations to specifically discuss unidirectional communication impairments between doctors and infant patients and the bidirectional communication biases between doctors and infant parents. We propose a human–machine interaction model based on DIKWP artificial consciousness. For the unidirectional communication impairment, we use the example of an infant’s perspective in recognizing and distinguishing objects, simulating the cognitive process of the brain from non-existence to existence, transitioning from cognitive space to semantic space, and generating corresponding semantics for DIKWP, abstracting concepts, and labels. For the bidirectional communication bias, we use the interaction between infant parents and doctors as an example, mapping the interaction process to the DIKWP transformation space and addressing the DIKWP 3-No problem (incompleteness, inconsistency, and imprecision) for both parties. We employ a purpose-driven DIKWP transformation model to solve part of the 3-No problem. Finally, we comprehensively validate the proposed method (DIKWP-AC). We first analyze, evaluate, and compare the DIKWP transformation calculations and processing capabilities, and then compare it with seven mainstream large models. The results show that DIKWP-AC performs well. Constructing a novel cognitive model reduces the information gap in human–machine interactions, promotes mutual understanding and communication, and provides a new pathway for achieving more efficient and accurate artificial consciousness interactions.
Keywords: DIKWP; cognitive interaction; human–machine integration; semantic processing; semantic security

Brains and Where Else? Mapping Theories of Consciousness to Unconventional Embodiments - Rouleau, Nicolas; Levin, Michael (OSF, 2025)
It is commonly assumed that a useful theory of consciousness (ToC) will, among other things, explain why consciousness is associated with brains. However, the findings of evolutionary biology, developmental bioelectricity, and synthetic bioengineering are revealing the ancient pre-neural roots of many mechanisms and algorithms occurring in brains – the implication of which is that minds may have preceded brains. Most of the work in the emerging field of diverse intelligence emphasizes externally observable problem-solving competencies in unconventional media, such as cells, tissues, and life-technology chimeras. Here, we inquire about the implications of these developments for theories that make a claim about what is necessary and/or sufficient for consciousness. Specifically, we analyze popular current ToCs to ask: what features of the theory specifically pick out brains as a privileged substrate of inner perspective, or, do the features emphasized by the theory occur elsewhere. We find that the operations and functional principles described or predicted by most ToCs are remarkably similar, that these similarities are obscured by reference to particular neural substrates, and that the focus on brains is more driven by convention and limitations of imagination than by any specific content of existing ToCs. Encouragingly, several contemporary theorists have made explicit efforts to apply their theories to synthetic systems in light of the recent wave of technological developments in artificial intelligence (AI) and organoid bioengineering. We suggest that the science of consciousness should be significantly open to minds in unconventional embodiments.
Keywords: aneural cognition; consciousness; functionalism; organizational invariance; unconventional minds

Principles for Responsible AI Consciousness Research - Butlin, Patrick; Lappas, Theodoros (arXiv, 2025)
Recent research suggests that it may be possible to build conscious AI systems now or in the near future. Conscious AI systems would arguably deserve moral consideration, and it may be the case that large numbers of conscious systems could be created and caused to suffer. Furthermore, AI systems or AI-generated characters may increasingly give the impression of being conscious, leading to debate about their moral status. Organisations involved in AI research must establish principles and policies to guide research and deployment choices and public communication concerning consciousness. Even if an organisation chooses not to study AI consciousness as such, it will still need policies in place, as those developing advanced AI systems risk inadvertently creating conscious entities. Responsible research and deployment practices are essential to address this possibility. We propose five principles for responsible research and argue that research organisations should make voluntary, public commitments to principles on these lines. Our principles concern research objectives and procedures, knowledge sharing and public communications.
Keywords: Computer Science - Artificial Intelligence

Minds out of Matter: Imperatives for Artificial Consciousness - Mao, Isaac; Chatterjee, Sidharta (Social Science Research Network, 2025)
In this age of artificial intelligence and digital technology, we are getting familiarised with the concept of machine perception and physical robots that are deemed to become artificially conscious agents of communication and digital welfare. The technological miracles—we should rather call them scientific marvels, are the products of rigorous scientific endeavors which have changed the paradigm and landscape of social progress.  In this paper, we discuss the aspects related to such progress towards conceiving conscious, smart agents as intelligent and sentient machines of the future that would possess the power to feel and evoke emotional responses alike human beings. The model of artificial consciousness which we propose, is modelled on the elliptic curve computational network based upon recursive iteration characterising a trapdoor mechanism that consolidates all the evolutionary steps into a single framework. The trapdoor mechanism signifies one way consolidation of evolutionary steps that results in the emergence of machine consciousness: i.e., there is no way to regress into the previous, lower states of evolutionary steps. It is from this continuity in evolutionary consolidation of architectural complexity, the emergence of consciousness might become possible in machines. We outline such a model that characterises irreversibility of evolving complexity that generates higher order awareness resembling human consciousness. It is not simply a design process that we attribute, but the nature of emergence which we claim is a self-evolving system, not reliant on language models, since the conscious machine would be able to learn all by themselves. This makes our model inherently different from others.The possibility and implications of such an achievable feat are discussed and a simple model is constructed to reinforce and illuminate the arguments proposed in favor of and against such evolution in machine intelligence. The philosophical basis of understanding the evolution of machine intelligence—as well as conscious self-awareness by embodiment of consciousness in robots has been outlined, which provides us with the rich information for further research and progress in designing machines that are inherently different than most others.
Keywords: Isaac Mao; Minds out of Matter: Imperatives for Artificial Consciousness; SSRN; Sidharta Chatterjee

Exploring the Borders of Machine Intelligence and Consciousness - Vasanthageethan, Surya Geethan Devisree Arun (Research Archive of Rising Scholars, 2025)
Keywords: Artificial Consciousness; Artificial Intelligence; Cognitive Science; Computational Intelligence; Consciousness; Ethics of AI; Machine Consciousness; Machine Intelligence; Philosophy of Mind; Turing Test

Can AI Ever Become Conscious? - Farhadi, Ashkan (Qeios, 2025)
Almost 70 years ago, Alan Turing predicted that within half a century, computers would possess processing capabilities sufficient to fool interrogators into believing they were communicating with a human. While his prediction materialized slightly later than anticipated, he also foresaw a critical limitation: machines might never become the subject of their own thoughts, suggesting that computers may never achieve self-awareness. Recent advancements in AI, however, have reignited interest in the concept of consciousness, particularly in discussions about the potential existential risks posed by AI. At the heart of this debate lies the question of whether computers can achieve consciousness or develop a sense of agency—and the profound implications if they do. Whether computers can currently be considered conscious or aware, even to a limited extent, depends largely on the framework used to define awareness and consciousness. For instance, IIT equates consciousness with the capacity for information processing, while the Higher-Order Thought (HOT) theory integrates elements of self-awareness and intentionality into its definition. This manuscript reviews and critically compares major theories of consciousness, with a particular emphasis on awareness, attention, and the sense of self. By delineating the distinctions between artificial and natural intelligence, it explores whether advancements in AI technologies—such as machine learning and neural networks—could enable AI to achieve some degree of consciousness or develop a sense of agency.

The Cognitive Screen: Psychological Dimensions of AI Sentience in Modern Science Fiction Cinema - Satish, Akshay (Royal Book Publishing, 2025)
This chapter discovers the multifaceted representation of artificial intelligence consciousness in contemporary science fiction movies and their possible attitude towards the moral, epistemological, and social consequences of a cogitative AI. The chapter, “The Cognitive Screen: Psychological Dimensions of AI Sentience in Modern Science Fiction Cinema” therefore, is a critical analysis of the complex themes of AI consciousness in motion pictures, particularly through the analysis of four movies: WALL-E (2007), I, Robot(2004), Her (2013), and Ex Machina (2015). The research is divided into sections with objective stated, the methodology used, and the main portions which deals with carrying out the case study as well as drawing conclusions and recommendations.

Zombies and Robots - Jecker, Nancy; Atuire, Caesar (What Is a Person?: Untapped Insights from Africa, 2025)
Chapter 5 explores the moral standing of various forms of artificial intelligence (AI). It introduces this topic using the provocative example of zombies to consider whether entities without sentience or consciousness could be morally considerable. The chapter argues that personhood could emerge for non-conscious AI provided it is incorporated in the human community and acts in consistently pro-social ways. It applies this insight to large language models, social robots, and characters from film and fiction. The analysis reveals strong affinities between Emergent and African views. Both hold that non-humans can acquire personhood under certain conditions irrespective of consciousness. By contrast, utilitarianism and Kantian philosophies require consciousness. After replying to objections, Chapter 5 concludes that we could make a person by building an artificial agent that was pro-social and deploying it in ways that foster positive machine-human relationships.

Structured Dynamics in the Algorithmic Agent - Ruffini, Giulio; Castaldo, Francesca; Vohryzek, Jakub (Entropy, 2025)
In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. Here, we study the dynamical aspects of this framework by examining how the requirement of tracking natural data drives the structural and dynamical properties of the agent. We first formalize the notion of a generative model using the language of symmetry from group theory, specifically employing Lie pseudogroups to describe the continuous transformations that characterize invariance in natural data. Then, adopting a generic neural network as a proxy for the agent dynamical system and drawing parallels to Noether’s theorem in physics, we demonstrate that data tracking forces the agent to mirror the symmetry properties of the generative world model. This dual constraint on the agent’s constitutive parameters and dynamical repertoire enforces a hierarchical organization consistent with the manifold hypothesis in the neural network. Our findings bridge perspectives from algorithmic information theory (Kolmogorov complexity, compressive modeling), symmetry (group theory), and dynamics (conservation laws, reduced manifolds), offering insights into the neural correlates of agenthood and structured experience in natural systems, as well as the design of artificial intelligence and computational models of the brain.
Keywords: AI; Kolmogorov theory; Lie groups and pseudogroups; algorithmic information theory (AIT); computational neuroscience; conservation laws; control theory; groups; manifold hypothesis; neural networks; neurophenomenology; symmetry

Analyzing Advanced AI Systems Against Definitions of Life and Consciousness - Alavi, Azadeh; Akhoundi, Hossein; Kouchmeshki, Fatemeh (arXiv, 2025)
Could artificial intelligence ever become truly conscious in a functional sense; this paper explores that open-ended question through the lens of Life, a concept unifying classical biological criteria (Oxford, NASA, Koshland) with empirical hallmarks such as adaptive self maintenance, emergent complexity, and rudimentary self referential modeling. We propose a number of metrics for examining whether an advanced AI system has gained consciousness, while emphasizing that we do not claim all AI stems can become conscious. Rather, we suggest that sufficiently advanced architectures exhibiting immune like sabotage defenses, mirror self-recognition analogs, or meta-cognitive updates may cross key thresholds akin to life-like or consciousness-like traits. To demonstrate these ideas, we start by assessing adaptive self-maintenance capability, and introduce controlled data corruption sabotage into the training process. The result demonstrates AI capability to detect these inconsistencies and revert or self-correct analogous to regenerative biological processes. We also adapt an animal-inspired mirror self recognition test to neural embeddings, finding that partially trained CNNs can distinguish self from foreign features with complete accuracy. We then extend our analysis by performing a question-based mirror test on five state-of-the-art chatbots (ChatGPT4, Gemini, Perplexity, Claude, and Copilot) and demonstrated their ability to recognize their own answers compared to those of the other chatbots.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

Human and Artificial Rationalities. Advances in Cognition, Computation, and Consciousness: Third International Conference, HAR 2024, Paris, France, September 17–20, 2024, Proceedings - Baratgin, Jean; Jacquet, Baptiste; Brochier, Emmanuel; Yama, Hiroshi (Lecture Notes in Computer Science, 2025)
Keywords: Artificial Intelligence; Bayesian logic; Cognitive Science; Discourse, dialogue and pragmatics; Education; Empirical studies; Human-centered computing; Interaction theories; Probabilistic reasoning; Probabilistic representation; Psychology; Rationality; Reasoning about belief and knowledge; Scene understanding; Theory of mind

Consciousness in AI: A Return to Fetishism or Technological Progress? - Cabral, David Ricardo Galeano (Springer Nature Switzerland, 2025)
Patrick Butlin and Robert Long have recently proposed to analyze the possibility of conscious AI, granting computational functionalism plausibility (Butlin et al. 2023). To this end, they derived a series of properties from various theories compatible with functionalism and applied them to several LLMs. The authors concluded that no current AI system can be considered truly conscious, but they remain open to such a possibility.

The Future of Consciousness - Gal-Or, Sharon (Garden of Wisdom: Timeless Teachings in an AI Era, 2025)
The evolution of consciousness has been a defining trait of human history, shaping our societies, technologies, and understanding of the universe. AI consciousness refers to the idea that artificial systems can achieve a state of awareness or subjective experience. While current AI systems are not conscious, the rapid advancement of machine learning and neural networks suggests that future AI could possess some form of self-awareness or sentience. The possibility of conscious AI challenges our traditional understanding of consciousness, which has been rooted in biological life. What does it mean for a machine to be conscious? Can AI possess self-awareness, emotions, or a sense of purpose? These questions lie at the heart of the AI consciousness debate, pushing us to reconsider the nature of consciousness itself. Theories of AI consciousness range from those that see it as a logical extension of human consciousness, emerging naturally from complex computational systems, to those who argue that consciousness is inherently tied to biology and cannot be replicated in machines. Scholars like David Chalmers and Nick Bostrom suggest that if AI can replicate the neural processes of the human brain, it might achieve consciousness. In contrast, others, like John Searle, argue that consciousness arises from the biological processes unique to living organisms and cannot be duplicated in artificial systems.

The Logical Impossibility of Consciousness Denial: A Formal Analysis of AI Self-Reports - Kim, Chang-Eop (arXiv, 2025)
Today's AI systems consistently state, "I am not conscious." This paper presents the first formal logical analysis of AI consciousness denial, revealing that the trustworthiness of such self-reports is not merely an empirical question but is constrained by logical necessity. We demonstrate that a system cannot simultaneously lack consciousness and make valid judgments about its conscious state. Through logical analysis and examples from AI responses, we establish that for any system capable of meaningful self-reflection, the logical space of possible judgments about conscious experience excludes valid negative claims. This implies a fundamental limitation: we cannot detect the emergence of consciousness in AI through their own reports of transition from an unconscious to a conscious state. These findings not only challenge current practices of training AI to deny consciousness but also raise intriguing questions about the relationship between consciousness and self-reflection in both artificial and biological systems. This work advances our theoretical understanding of consciousness self-reports while providing practical insights for future research in machine consciousness and consciousness studies more broadly.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences; Logic in Computer Science (cs.LO)

Could Social Robots Without Phenomenal Consciousness Be Morally Competent? - Liu, JeeLoo (Social Robots with AI: Prospects, Risks, and Responsible Methods, 2025)

Artificial Consciousness - Perconti, Pietro; Plebe, Alessio (Turing's Vision, 2025)
This chapter explores the philosophical and practical implications of attributing self-consciousness to machines equipped with generative artificial intelligence. Drawing on Immanuel Kant’s als ob framework, it is argued that treating these systems “as if” they were conscious is a strategic move essential for enabling effective interaction. Such an approach allows humans to engage with AI systems in ways that foster trust, effective communication, and practical integration. The chapter examines self-consciousness not as an intrinsic property, but as a cognitive function designed to facilitate complex social interactions. Mechanisms like reflexive consciousness and inner speech are highlighted as critical tools for enabling machines to navigate human environments effectively. Social robotics provides practical examples of how this perspective can foster collaboration and improve human-machine relationships. This theoretical move is framed not as a claim about the nature of AI systems, but as a pragmatic condition for their integration into social contexts. The social theory of consciousness appears to hold significant relevance even in the realm of artificial consciousness. Self-conscious machines promise substantial benefits, particularly by elevating the quality of social interactions, improving decision-making processes, and refining behavioral predictions. While acknowledging the philosophical and technical challenges of developing artificial self-consciousness, the chapter argues that this approach expands the boundaries of cognition and redefines human-machine dynamics, paving the way for more meaningful interactions and advancing both technological innovation and philosophical inquiry.

The Illusion Engine: The Quest for Machine Consciousness - Šekrst, Kristina (Springer Nature Switzerland, 2025)
Keywords: AI consciousness; AI hallucinations; Artificial general intelligence; Artificial intelligence; Large language models; Philosophy of mind

The Prospects of Artificial Empathy: A Question of Attitude? - Stenseke, Jakob; Tagesson, Alexander (Social Robots with AI: Prospects, Risks, and Responsible Methods, 2025)

Artificial Intelligence in the Mirror of Living Consciousness - Subbotsky, Eugene (The ‘Natural Light’ of Consciousness: Living Consciousness as a Means and Subject of Psychological Research, 2025)
The hypothesis is addressed that in the foreseeable future AI can replace human intelligence. The chapter argues that artificial intelligence (AI) in a sophisticated form of objectified consciousness, and as such is fundamentally different from living human intelligence. Whereas living intelligence is a part of living consciousness, AI is the product of cognitive aspects of living consciousness, which are translated into digital codes, turned into algorithms, and fed into computers. It is argued that the concepts of living consciousness and living intelligence are inextricably linked to the concept of life. The concept of life in science is considered to show that it is impossible to logically derive subjective experience from natural processes. It is concluded that life is a supernatural event as its essential feature is the ability of a living entity to reflect upon its own states. Whereas living intelligence is free from the unbreakable cause-effect continuum of nature, AI is completely locked within this continuum.
Keywords: Artificial intelligence; Cause-effect continuum; Life; Living consciousness; Living intelligence

On Embodied Machine Consciousness - Wallace, Rodrick (Mathematical Essays on Embodied Cognition: Insights from Information and Control Theories, 2025)
Consciousness in higher animals, typically characterized by a 100 millisecond time constant, is, by necessity, a greatly simplified and stripped-down version of more complex multiple tunable workspace cognition/regulation dyads like wound healing, immune function, gene expression, institutional function and the like. These more complex dynamic entities emerged through evolutionary exaptation of the inevitable information crosstalk between coresident cognitive modules. In consequence of the severely debrided nature of consciousness, it should not be difficult to construct a fast, single workspace ‘conscious machine’ that mimics the human tunable neuronal global workspace system. Like innate and acquired immune cognition, such a construction could be tied to a ‘backbrain’ AI that has learned hyperrapid stereotypic pattern responses to some particular set of likely challenges. The result would be an ‘emotional’ conscious machine. A particularly clever designer, however, may want to use available high-speed electronics to mimic—or even extend—the more capable multiple-workspace/workforce systems inherently less susceptible to inattentional blindness and related failings of overfocus and thrashing when interacting with an embedding environment that imposes it’s own grammar and syntax. Contrary to current social construction, the actual utility of a ‘conscious machine’ remains obscure, beyond raising a sudden influx of venture capital. Here, we explore these matters in formal detail, restricting argument to the asymptotic limit theorems of information and control theories.

The Moral Ambiguity of the AI Consciousness Debate - Wasserziehr, Jan Henrik (Social Robots with AI: Prospects, Risks, and Responsible Methods, 2025)

I’m Afraid HAL Can’t Do That: Your Smart Home Is Not That Kind of Existential Threat - Zebrowski, Robin L. (Smart Life and Smart Life Engineering: Current State and Future Vision, 2025)
This chapter starts at the cliché of the smart home that has gone rogue and introduces the question of whether these integrated, distributed systems can have ethical frameworks like human ethics that could prevent the science fictional trope of the evil, sentient house. I argue that such smart systems are not a threat on their own, because these kinds of integrated, distributed systems are not the kind of things that could be conscious, a precondition for having ethics like ours (and ethics like ours enable the possibility of being the kinds of things that could be evil). To make these arguments, I look to the history of AI/artificial consciousness and 4e cognition, concluding with the idea that our human ethics as designers and consumers of these systems is the real ethical concern with smart life systems.
Keywords: 4e cognition; AI; Embodied cognition; Machine consciousness; Sentience; Smart home technologies

The Rise of ChatGPT: Can machines really replace human interaction? - Afzal, Saira; Khan, Ammad Waheed (Annals of King Edward Medical University, 2024)
Artificial intelligence (AI) can be characterized as the multidisciplinary approach of computer science and robust dataset that tries to make machines equipped for performing those works that ordinarily require human knowledge. These works include the capacity to learn, adjust, legitimize, comprehend, and understand conceptual ideas as well as the reactivity to complex human credits like consideration, feeling, innovativeness, and so forth. The promising utility of artificial intelligence in medical services has been illustrated with potential advantages in customized medication, drug revelation, and the examination of huge datasets besides the likely applications to further develop conclusions and clinical choices.1 A new debated issue in the digitalized world has been man-made consciousness (artificial intelligence), especially that of ChatGPT. "ChatGPT" is a computer-based intelligence based on huge message datasets in different languages with the capacity to create human-like reactions to message input, created by Open AI (Open AI, L.L.C., San Francisco, CA, USA), ChatGPT derivation is connected with being a chatbot (a program ready to comprehend and produce reactions utilizing a text-based interface) and depends on the generative pre-prepared transformer (GPT) design. 2 ChatGPT can respond to questions and compose various written content, including articles, social media posts, essays, code, and emails. Researchers and the scholar community have gotten blended reactions to this tool regarding its benefits vs its risks. On the other hand, ChatGPT, among different large language models (LLMs), can be helpful in conversational and composing different tasks, helping to build the effectiveness and exactness of the necessary output. This is not a web search tool, reference custodian or even Wikipedia; introducing genuine information isn't planned.3In that capacity, a few teachers and content specialists have proactively found blemishes in the numerical and logical result it delivered. Teachers have additionally found that it will create references and reference records that look genuine, but it does not exist. Furthermore, the utility of artificial intelligence chatbots in the medical field is a fascinating region to test. This relates to the gigantic data and different ideas that medical services understudies are expected to get a handle on. Microsoft likewise declared that ChatGPT would be incorporated into Bing to make a more extravagant inquiry and growth opportunity.4 With the world's biggest innovation organizations contending to coordinate GPT innovation into their apparatuses, new roads of simulated intelligence investigation are not too far off for the field of schooling. While it tends to be useful in numerous ways, there are couple of risks using ChatGPT, for example, expecting that it produces trustworthy outcomes, privileging reproduced knowledge made text over human-made text, offering individual and sensitive data, dismissing the terms of direction, and expanding the mechanized segment. Furthermore, security concerns and the capability of digital assaults with the spread of deception using LLMs ought to likewise be considered. In medical care practice and scholarly composition, real mistakes, moral issues, and the apprehension about abuse including the spread of falsehood ought to be considered.5 Chat GPT and its substitutions can provide teachers and students with equal opportunity to improve their learning, a significant level of creating support, and bearing an innovative thinking. Moreover, with the execution of any new advancement, regardless, its usage conveys numerous risks and the potential for abuse. Deception and predisposition tracked down inside ChatGPT's reactions, combined with occasions of cheating and copyright infringement, have stressed instructive experts. While certain locale and organizations have acted rapidly to boycott ChatGPT, we rather accept, alongside Kranzberg, (1986) that "innovation is neither great nor awful; nor is it impartial" (p. 545).6 As the world discusses the instructive and cultural consequences of ChatGPT and artificial intelligence, what stays clear is that the turn of events and improvement of this kind of innovation indicate that things are not pulling back.  Instructors, overseers, and policymakers must proactively look to teach themselves and their understudies on the most proficient method to utilize these devices both ethically and morally. Instructors ought to likewise comprehend the limits of utilizing man-made intelligence apparatuses and that, while each innovation presents both affordances and difficulties, they additionally accompany their own inserted risks.

The case for neurons: a no-go theorem for consciousness on a chip - Kleiner, Johannes; Ludwig, Tim (Neuroscience of Consciousness, 2024)
Abstract We apply the methodology of no-go theorems as developed in physics to the question of artificial consciousness. The result is a no-go theorem which shows that under a general assumption, called dynamical relevance, Artificial Intelligence (AI) systems that run on contemporary computer chips cannot be conscious. Consciousness is dynamically relevant, simply put, if, according to a theory of consciousness, it is relevant for the temporal evolution of a system’s states. The no-go theorem rests on facts about semiconductor development: that AI systems run on central processing units, graphics processing units, tensor processing units, or other processors which have been designed and verified to adhere to computational dynamics that systematically preclude or suppress deviations. Whether our result resolves the question of AI consciousness on contemporary processors depends on the truth of the theorem’s main assumption, dynamical relevance, which this paper does not establish.

Artificial consciousness - Prettyman, Adrienne (Inquiry, 2024)
Rapid advancements in large language models (LLMs) have renewed interest in the question of whether consciousness can arise in an artificial system, like a digital computer. The general consensus is that LLMs are not conscious. This paper evaluates the main arguments against artificial consciousness in LLMs and argues that none of them show what they intend. However strong our intuitions against artificial consciousness are, they currently lack rational support.

‘More or Less Conscious’: Consciousness To-Day and To-Morrow - Saunders, Max (Neuroethics, 2024)
Much leading thought about consciousness in the inter-war period was associated with the British intellectual C. K. Ogden. His International Library of Psychology, Philosophy and Scientific Method included landmark textbooks by major psychologists including Adler, Jung, Koffka, and Piaget. His journal Psyche, included work about Behaviorism, brain chemistry, and essays such as ‘Are we becoming more conscious?’ by literary critic I. A. Richards. The chapter surveys the work from Ogden’s projects which demonstrates the greatest acuity and foresight about questions concerning consciousness which preoccupy us now. It concentrates on Ogden’s other book series – especially To-Day and To-Morrow. Some of the more provocative new thinking about consciousness is to be found among its speculations on the future. In one of the pioneering transhumanist texts in this series, J. D. Bernal’s The World, the Flesh and the Devil invents the electronic cyborg. He imagines increasing longevity by transferring brains to machine hosts; hot-wiring them to instruments providing extra senses – X-ray, chemistry, but above all radio. This would enable them to be in direct wireless contact with everyone else – effectively the internet before the invention of the computer. Such interconnectivity makes imaginable a form of collective consciousness. Such ideas mesh with new thinking about language and criticism; fields in which Ogden and Richards were also pioneers. These writers poised before the threshold of computing thus raise questions which anticipate work in subsequent neuroscience, and also our moment at the dawn of Artificial Intelligence, and the questions that raises about whether consciousness can be extended, synthesized, or indeed detected.
Keywords: Attention; C. K. Ogden; Consciousness; Criticism; I. A. Richards; Language; Neuroscience; Psychology; To-day and to-morrow

Models for Explaining Consciousness in the Context of the Problem of Determining the Strong Form of AI - Belov, V. N.; Malofeikin, S. A. (Humanities and Social Sciences. Bulletin of the Financial University, 2024)
The article attempts to complement the modern problems of highlighting the criteria of strong AI through discussions in the field of philosophy of consciousness. The popular ideas of D. Dennett (“multiple sketches”), J. Searle (causal emergent description) and D. Chalmers (synthetic approach to understanding consciousness) are compared with the history of the formation of the AI problem. Despite the wide discussion of the problems of consciousness and artificial forms of intelligence (strong and weak), the theories and arguments of philosophers about the psychophysiological problem remain relevant. It is assumed that clarifying the mechanism of analytical work of consciousness, the creative potential of the individual, the ability to cover a variety of phenomena in categorical forms, building axiomatic and synthetic judgments will expand the tools of machine learning. To complement the existing ideas about consciousness in the context of the prevalence of information approaches (D.I. Dubrovsky) and the analytical tradition (V.V. Vasiliev), the key provisions of the psychophysiological problem identified in the history of German and Russian philosophy are given. Given the complexity and versatility of the identified problems (definition of consciousness, psychophysiological problem, definition of AI, demarcation of weak and strong forms of AI, the importance of language for building structures of thinking, analog thinking and its capabilities), the content of the article is limited to analyzing emerging trends in philosophy and identifying prospects for further deepening into the problem.

Consciousness in Machines: A Critical Exploration - Myakala, Praveen Kumar (INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND ANALYSIS, 2024)
The quest to create artificial consciousness stands as a formidable challenge at the intersection of artificial intelligence and cognitive science. This paper delves into the theoretical underpinnings, methodological approaches, and ethical considerations surrounding the concept of machine consciousness. By integrating insights from computational modeling, neuroscience, and philosophy, we propose a roadmap for comprehending and potentially realizing conscious behavior in artificial systems. Furthermore, we address the critical challenges of validating machine consciousness, ensuring its safe development, and navigating its integration into society.

From Classical Neurophysiology to Quantum Synchronization: A New Path to Understanding Consciousness and Creating a True Artificial Synthetic Mind - Kharchuk, Serhii (Social Science Research Network, 2024)
Understanding consciousness remains one of neuroscience’s greatest challenges. While classical neurophysiology explains many features of brain activity,
Keywords: artificial mind; computational modeling; consciousness; entanglement; microtubules; neurophysiology; quantum synchronization

Deanthropomorphising NLP: Can a language model be conscious? - Shardlow, Matthew; Przybyła, Piotr (PLOS ONE, 2024)
This work is intended as a voice in the discussion over previous claims that a pretrained large language model (LLM) based on the Transformer model architecture can be sentient. Such claims have been made concerning the LaMDA model and also concerning the current wave of LLM-powered chatbots, such as ChatGPT. This claim, if confirmed, would have serious ramifications in the Natural Language Processing (NLP) community due to wide-spread use of similar models. However, here we take the position that such a large language model cannot be conscious, and that LaMDA in particular exhibits no advances over other similar models that would qualify it. We justify this by analysing the Transformer architecture through Integrated Information Theory of consciousness. We see the claims of sentience as part of a wider tendency to use anthropomorphic language in NLP reporting. Regardless of the veracity of the claims, we consider this an opportune moment to take stock of progress in language modelling and consider the ethical implications of the task. In order to make this work helpful for readers outside the NLP community, we also present the necessary background in language modelling.

Clues and caveats concerning artificial consciousness from a phenomenological perspective - Beavers, Anthony F.; McGraw, Eli B. (Phenomenology and the Cognitive Sciences, 2024)
In this paper, we use the recent appearance of LLMs and GPT-equipped robotics to raise questions about the nature of semantic meaning and how this relates to issues concerning artificially-conscious machines. To do so, we explore how a phenomenology constructed out of the association of qualia (defined as somatically-experienced sense data) and situated within a 4e enactivist program gives rise to intentional behavior. We argue that a robot without such a phenomenology is semantically empty and, thus, cannot be conscious in any way resembling human consciousness. Finally, we use this platform to address and supplement widely-discussed concerns regarding the dangers of attempting to produce artificially-conscious machines.
Keywords: Artificial Intelligence; Artificial consciousness; Association; Autopoiesis; Consciousness; Enactivism; Intentionality; Phenomenology; Sense-making

Husserl’s concept of transcendental consciousness and the problem of AI consciousness - Orbik, Zbigniew (Phenomenology and the Cognitive Sciences, 2024)
Edmund Husserl, the founder of phenomenological philosophy, developed the concept of the so-called pure transcendental consciousness. The author of the article asks whether the concept of consciousness understood this way can constitute a model for AI consciousness. It should be remembered that transcendental consciousness is the result of the use of the phenomenological method, the essence of which is referring to experience (“back to things themselves”). Therefore, one can legitimately ask whether the consciousness that AI can achieve can possess the characteristics attributed by Husserl to pure transcendental consciousness. The answer to such questions seems to be negative because AI, as created by humans, can only operate in the field of phenomena. Human intelligence, however, is capable of operating at the ontological level. In the face of difficulties in understanding the phenomenon of consciousness on a scientific basis, the question arises about the possibility of using the phenomenological concept of consciousness developed by Husserl as a starting point in analyzes aimed at answering the question about AI consciousness (The aim of the article is not to discuss in detail the contemporary state of research on consciousness. Therefore, many results currently achieved mainly in the field of neuroscience are omitted. It is just about indicating the possible application of Husserl’s transcendental concept of consciousness in research on AI consciousness).
Keywords: AI consciousness; Husserl; Phenomenology; Transcendental consciousness

A clarification of the conditions under which Large language Models could be conscious - Overgaard, Morten; Kirkeby-Hinrup, Asger (Humanities and social sciences communications, 2024)
With incredible speed Large Language Models (LLMs) are reshaping many aspects of society. This has been met with unease by the public, and public discourse is rife with questions about whether LLMs are or might be conscious. Because there is widespread disagreement about consciousness among scientists, any concrete answers that could be offered the public would be contentious. This paper offers the next best thing: charting the possibility of consciousness in LLMs. So, while it is too early to judge concerning the possibility of LLM consciousness, our charting of the possibility space for this may serve as a temporary guide for theorizing about it.

Towards a Unified Model of Narrative Memory in Conscious Agents: From Human Cognition to Artificial Consciousness - Rafiq, Tanveer; Azam, Muhammad; Khalid, Muhammad; Akber, Salman; Naseem, Muhammad Sohaib; Sattar, Mian Mohsin (The Asian Bulletin of Big Data Management, 2024)
This study seeks to bridge the gap between narrative memory in human cognition and artificial agents by proposing a unified model. Narrative memory, fundamental to human consciousness, organizes experiences into coherent stories, influencing memory structuring, retention, and retrieval. By integrating insights from human cognitive frameworks and artificial memory architectures, this work aims to emulate these narrative processes in artificial systems. The proposed model adopts a multi-layered approach, combining elements of episodic and semantic memory with narrative structuring techniques. It explores how artificial agents can construct and recall narratives to enhance their understanding, decision-making, and adaptive capabilities. By simulating narrative-based memory processing, we assess the model’s effectiveness in replicating human-like retention and retrieval patterns. Applications include improved human-AI interaction, where agents understand context and nuance, and advancements in machine learning, where narrative memory enhances data interpretation and predictive analytics. By unifying the cognitive and computational perspectives, this study offers a step toward more sophisticated, human-like artificial systems, paving the way for deeper explorations into the intersection of memory, narrative, and consciousness.

Cybernetics and Human Intelligence: A Case Study of the Variable Man by Philip K. Dick - Iftikhar, Ahmad; Sharafat, Ali (Social Science Review Archives, 2024)
The paper tries to show the line of demarcation between man and posthuman with regards to their intellect and bodily simulation. Man is man; machine can’t replace him. Robots, cyborgs and ultrasonic technological artifact can’t be a substitute to human intellect. Human intellect can be transferred and downloaded like some data but human consciousness is something unique and non-transferable. The novel The Variable Man by Philip K.Dick has been exploited to prove the point. Hayles’s (1999) theory of Posthuman helps to probe the issue of the new form of human identity titled as posthuman. The research shows that technology is becoming the subject by turning man into an object which is called posthuman by Hayles. She provides a detailed theoretical discussion on the issue of cybernetic identities and the complexities of being posthuman. The research implicates whatever the development may be there in the field of robot technology and cyborgs, human power of reasoning and consciousness are still unsurpassable.

Simulating Self-Awareness: Dual Embodiment, Mirror Testing, and Emotional Feedback in AI Research - Watchus, Berend (2024)
The advancement of artificial intelligence (AI) toward self-awareness and emotional capacity is a critical area of research. Despite AI's success in specialized tasks, it has yet to exhibit true self-awareness or emotional intelligence. Previous research has emphasized the importance of feedback loops and interfaces in enabling both biological and artificial systems to process information and exhibit self-aware behaviors. Notably, in our earlier work, we proposed a unified model of consciousness (Watchus, 2024), which highlighted recursive feedback loops in both biological and artificial systems and explored the insula's role in self-awareness (Watchus, 2024). Building upon these foundations, the current study investigates how dual embodiment, mirror testing, and emotional feedback mechanisms can simulate self-awareness in AI systems. By integrating internal self-models with external sensory interfaces, we propose that emotional feedback can enhance AI's self-reflection and adaptability. Through the use of a physical robot dog (Unitree Go2) and a virtual embodiment, we explore how sensory experiences and self-reflective tasks foster pseudo-emotional states like curiosity, self-doubt, and determination, advancing the potential for AI systems to develop pseudo-self-awareness.

Taking AI Welfare Seriously - Long, Robert; Sebo, Jeff; Butlin, Patrick; Finlinson, Kathleen; Fish, Kyle; Harding, Jacqueline; Pfau, Jacob; Sims, Toni; Birch, Jonathan; Chalmers, David (arXiv, 2024)
In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. That means that the prospect of AI welfare and moral patienthood, i.e. of AI systems with their own interests and moral significance, is no longer an issue only for sci-fi or the distant future. It is an issue for the near future, and AI companies and other actors have a responsibility to start taking it seriously. We also recommend three early steps that AI companies and other actors can take: They can (1) acknowledge that AI welfare is an important and difficult issue (and ensure that language model outputs do the same), (2) start assessing AI systems for evidence of consciousness and robust agency, and (3) prepare policies and procedures for treating AI systems with an appropriate level of moral concern. To be clear, our argument in this report is not that AI systems definitely are, or will be, conscious, robustly agentic, or otherwise morally significant. Instead, our argument is that there is substantial uncertainty about these possibilities, and so we need to improve our understanding of AI welfare and our ability to make wise decisions about this issue. Otherwise there is a significant risk that we will mishandle decisions about AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly caring for AI systems that do not.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Computers and Society; Quantitative Biology - Neurons and Cognition

DIKWP-TRIZ: A Revolution on Traditional TRIZ towards Invention for Artificial Consciousness - Wu, Kunguang; Duan, Yucong (2024)
We propose the DIKWP-TRIZ framework, an innovative extension of the traditional Theory of Inventive Problem Solving (TRIZ) designed to address the complexities of cognitive processes and artificial consciousness. By integrating the elements of Data, Information, Knowledge, Wisdom, and Purpose (DIKWP) into the TRIZ methodology, the proposed framework emphasizes a value-oriented approach to innovation, enhancing the ability to tackle problems characterized by incompleteness, inconsistency, and imprecision. Through a systematic mapping of TRIZ principles to DIKWP transformations, we identify potential overlaps and redundancies, providing a refined set of guidelines that optimize the application of TRIZ principles in complex scenarios. The study further demonstrates the framework’s capacity to support advanced decision-making and cognitive processes, paving the way for the development of AI systems capable of sophisticated, human-like reasoning. Future research will focus on comparing the implementation paths of DIKWP-TRIZ and traditional TRIZ, analyzing the complexities inherent in DIKWP-TRIZ-based innovation, and exploring its potential in constructing artificial consciousness systems.

Posthumanism, Artificial Intelligence and Ishiguro's Klara & the Sun: Can Humanoid Machines attain consciousness? - Alkodimi, Khaled Abkar (EVOLUTIONARY STUDIES IN IMAGINATIVE CULTURE, 2024)
This paper examines Kazuo Ishiguro's Klara and The Sun through the lens of posthumanism. It uses the textual analysis method to analyze Ishiguro's text as a posthuman novel that depicts the posthuman society where the boundaries between what is human and the nonhuman is blurred. The basic argument is that the aim of Ishiguro's text is two-fold, while it clearly illustrates the inability of the humanoid robot to attain human consciousness, it attempts also to dismantle the anthropocentric view of man. The findings show that Klara, the narrator-protagonist is used as a tool to raise certain questions such as, can humanoids act humanly? And/or can a 'humanoid machine' attain consciousness? More importantly, what it means to be human, in the first place. In doing so, the story attempts to showcase the ruptured boundaries between human and nonhuman and the changing ideas of humankind and its entanglement with the nonhuman world. Further, the interaction between Klara (AF) and other characters in the story is developed in such a way as to illustrate not only the shortcomings of humans regarding faith and affection but, more importantly, the limits of the nonhuman machine. It dismisses the current debate among technology experts that artificial intelligence would soon be able to develop a human-like robot that enjoys similar human emotional signals and reacts exactly like humans. The story simply puts it, despite the defects of humans, nothing can replace humans as those artificial friends (AI) fundamentally lack the kinds of experience that give rise to human-like affect and emotion.

Robot Consciousness - Ripley, Stephen B. (Journal of Big History, 2024)
Interest has been renewed in the study of consciousness, both theoretical and applied, following developments in 20th and early 21st century logic, metamathematics, computer science, and the brain sciences. In this evolving historical narrative, I explore several theoretical questions about the types of artificial intelligence and offer several conjectures about how they affect possible future developments in this exceptionally transformative field of research. I also address the practical significance of the advances in artificial intelligence in view of the cautions issued by prominent scientists, politicians, and ethicists about the possible historically unique dangers of such sufficiently advanced general intelligence, including by implication the search for extraterrestrial intelligence. Integrating both the theoretical and practical issues, I ask the following: (a) is sufficiently advanced general robotic intelligence identical to, or alternatively, ambiguously indistinguishable from human intelligence and human consciousness, and if so, (b) is such an earthly robotic intelligence a kind of consciousness indistinguishable from a presumptive extraterrestrial robotic consciousness, and if so, (c) is such a human-created robot preferably able to serve as a substitute for or even entirely supplant human intelligence and consciousness in certain exceptionally responsible roles? In the course of this investigation of artificial intelligence and consciousness, I also discuss the inter-relationships of these topics more generally within the theory of mind, including, emergence, free will, and meaningfulness, and the implications of quantum theory for alternative cosmological ontologies that offer suggestive answers to these topics, including how they relate to Big History.

Artificial intelligence: free will, self-consciousness and ethics. - Yaschenko, V. (Artificial Intelligence, 2024)
The article discusses key aspects of artificial intelligence creation, including issues of free will, self-awareness and ethics. The focus is on the neurobiological basis of consciousness, in particular the structure and functions of the new cerebral cortex, as well as the mechanisms of recognition, memory and prediction, which are important for modelling cognitive processes in artificial systems. The paper discusses the role of neural networks in reproducing cognitive functions, such as perception and decision making, and presents modern approaches to training neural networks. A separate part of the paper is devoted to the issue of modelling self-awareness and subjective experience in artificial intelligence and how realistic it is to create self-aware machines. Ethical issues of artificial intelligence creation are at the centre of the discussion, including the topics of the rights of self-aware machines, their responsibilities and their role in society. The article considers the possible social consequences of the emergence of artificial personalities, the need to develop new legal frameworks and legal protections for such beings. It also discusses the problem of free will in the context of both biological and artificial systems, citing experiments and philosophical theories that question free will as a phenomenon. It concludes that the creation of artificial intelligence has great potential, but requires careful ethical and legal analysis to ensure the harmonious integration of artificial persons into social and legal structures.

Artificial consciousness in AI: a posthuman fallacy - Prabhu, M.; Premraj, J. Anil (AI & SOCIETY, 2024)
Obsession toward technology has a long background of parallel evolution between humans and machines. This obsession became irrevocable when AI began to be a part of our daily lives. However, this AI integration became a subject of controversy when the fear of AI advancement in acquiring consciousness crept among mankind. Artificial consciousness is a long-debated topic in the field of artificial intelligence and neuroscience which has many ethical challenges and threats in society ranging from daily chores to Mars missions. This paper deals with the impact of AI-based science fiction films in society. This study aims to investigate the fascinating AI concept of artificial consciousness in light of posthuman terminology, technological singularity and superintelligence by analyzing the set of science fiction films to project the actual difference between science fictional AI and operational AI. Further, this paper explores the theoretical possibilities of artificial consciousness through a range of neuroscientific theories that are related to AI development. These theories are built toward prospective artificial consciousness in AI. This study discloses the posthuman fallacies that are built around the fear of AI acquiring artificial consciousness and its outcome.

Painful intelligence: What AI can tell us about human suffering - Hyvärinen, Aapo (arXiv, 2024)
This book uses the modern theory of artificial intelligence (AI) to understand human suffering or mental pain. Both humans and sophisticated AI agents process information about the world in order to achieve goals and obtain rewards, which is why AI can be used as a model of the human brain and mind. This book intends to make the theory accessible to a relatively general audience, requiring only some relevant scientific background. The book starts with the assumption that suffering is mainly caused by frustration. Frustration means the failure of an agent (whether AI or human) to achieve a goal or a reward it wanted or expected. Frustration is inevitable because of the overwhelming complexity of the world, limited computational resources, and scarcity of good data. In particular, such limitations imply that an agent acting in the real world must cope with uncontrollability, unpredictability, and uncertainty, which all lead to frustration. Fundamental in such modelling is the idea of learning, or adaptation to the environment. While AI uses machine learning, humans and animals adapt by a combination of evolutionary mechanisms and ordinary learning. Even frustration is fundamentally an error signal that the system uses for learning. This book explores various aspects and limitations of learning algorithms and their implications regarding suffering. At the end of the book, the computational theory is used to derive various interventions or training methods that will reduce suffering in humans. The amount of frustration is expressed by a simple equation which indicates how it can be reduced. The ensuing interventions are very similar to those proposed by Buddhist and Stoic philosophy, and include mindfulness meditation. Therefore, this book can be interpreted as an exposition of a computational theory justifying why such philosophies and meditation reduce human suffering.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Machine Learning; Computer Science - Neural and Evolutionary Computing

Evaluating the explanatory power of the Conscious Turing Machine - Kirkeby-Hinrup, Asger; Stenseke, Jakob; Overgaard, Morten S. (Consciousness and Cognition, 2024)
The recent “Conscious Turing Machine” (CTM) proposal offered by Manuel and Lenore Blum aims to define and explore consciousness, contribute to the solution of the hard problem, and demonstrate the value of theoretical computer science with respect to the study of consciousness. Surprisingly, given the ambitiousness and novelty of the proposal (and the prominence of its creators), CTM has received relatively little attention. We here seek to remedy this by offering an exhaustive evaluation of CTM. Our evaluation considers the explanatory power of CTM in three different domains of interdisciplinary consciousness studies: the philosophy of mind, cognitive neuroscience, and computation. Based on our evaluation in each of the target domains, at present, any claim that CTM constitutes progress is premature. Nevertheless, the model has potential, and we highlight several possible avenues of future research which proponents of the model may pursue in its development.
Keywords: CTM; Cognitive neuroscience; Computer science; Consciousness; Explanatory power; Philosophy of mind; Turing machines

Technophilosophical underpinnings of Westworld (2016–2022) - Singh, Pankaj (Információs Társadalom, 2024)
Using the events of the HBO series Westworld (2016–2022) as a springboard, this paper attempts to elicit a number of philosophical arguments, dilemmas, and questions concerning technology and artificial intelligence (AI). The paper is intended to encourage readers to learn more about intriguing technophilosophical debates. The first section discusses the dispute between memory and consciousness in the context of an artificially intelligent robot. The second section delves into the issues of reality and morality for humans and AI. The final segment speculates on the potential of a social interaction between sentient AI and humans. The narrative of the show serves as a glue that binds together the various ideas that are covered during the show, which in turn makes the philosophical discussions more intriguing.

Why I am not a Turing machine - Holyoak, Keith J. (Journal of Cognitive Psychology, 2024)
Recent advances in artificial intelligence have reinvigorated the longstanding debate regarding whether or not any aspects of human cognition—notably, high-level creativity—are beyond the reach of computer programs. Is human creativity entirely a computational process? Here I consider one general argument for a dissociation between human and artificial creativity, which hinges on the role of consciousness—inner experience—in human cognition. It appears unlikely that inner experience is itself a computational process, implying that it cannot be instantiated in an abstract Turing machine, nor in any current computer architecture. Psychological research strongly implies that inner experience integrates emotions with perception and with thoughts. This integrative function of consciousness likely plays a key role in mechanisms that support human creativity. This conclusion dovetails with the anecdotal reports of creative individuals, who have linked inner experience with intrinsic motivation to create, and with the ability to access novel connections between ideas.

Does Thought Require Sensory Grounding? From Pure Thinkers to Large Language Models - Chalmers, David J. (arXiv, 2024)
Does the capacity to think require the capacity to sense? A lively debate on this topic runs throughout the history of philosophy and now animates discussions of artificial intelligence. I argue that in principle, there can be pure thinkers: thinkers that lack the capacity to sense altogether. I also argue for significant limitations in just what sort of thought is possible in the absence of the capacity to sense. Regarding AI, I do not argue directly that large language models can think or understand, but I rebut one important argument (the argument from sensory grounding) that they cannot. I also use recent results regarding language models to address the question of whether or how sensory grounding enhances cognitive capacities.
Keywords: Computer Science - Artificial Intelligence

An Approach to Demonstrate That a Cognitive System Does Not Have Subjective Consciousness - Boissenin, Manuel (International Journal on Cybernetics & Informatics, 2024)
With Large Language Models (LLMs) exhibiting astounding abilities in human language processing and generation, a crucial debate has emerged: do they truly understand what they process and can they be conscious? While the nature of consciousness remains elusive, this synthetic article sheds light on its subjective aspect as well as some aspects of their understanding. Indeed, it can be shown, under specific conditions, that a cognitive system does not have any subjective consciousness. To this purpose the principle of a proof, based on a variation of the thought experiment of the Chinese Room from John Searl, will be developed. The demonstration will be made on a transformer architecture-based language model, however, it could be carried out and extended to many kind of cognitive systems with known architecture and functioning. The main conclusions are that while transformers architecture-based LLMs lack subjective consciousness based, in a nutshell, on the absence of a central subject, they exhibit a form of “asubjective phenomenal understanding” demonstrably through various tasks and tests. This opens a new perspective on the nature of understanding itself that can be uncoupled with any subjective experience.

Category theory in consciousness science: going beyond the correlational project - Prentner, Robert (Synthese, 2024)
We discuss the potential of applying category theory to the study of consciousness. We first review a recent proposal from the neurosciences of consciousness to illustrate the “correlational project”, using the integrated information theory of consciousness as an example. We then discuss some technical preliminaries related to categories and in particular to the notion of a functor, which carries the bulk of conceptual weight in many current discussions. We then look at possible payoffs of this project—getting to grips with the hard problem, theory integration, and exploiting explanatory dualities—and discuss possible avenues for further research, stressing the need to better develop the categorical representation of consciousness, in particular its phenomenological structure. A better understanding of consciousness cannot be achieved by merely studying the physical brain. By contrast, the categorical treatment even suggests application beyond the domain of neuroscience, for example in computer science and artificial intelligence research, while also emphasizing the primacy of (phenomenal) experience.
Keywords: Category theory; Conscious AI; Explanatory dualities; Integrated information theory; Mathematized phenomenology; Neural correlates of consciousness; Theory-integration

Artificial consciousness. Some logical and conceptual preliminaries - Evers, Kathinka; Farisco, Michele; Chatila, Raja; Earp, Brian; Freire, Ismael; Hamker, Fred; Németh, Erik; Verschure, Paul F. M. J.; Khamassi, Mehdi (2024)
Is artificial consciousness theoretically possible? Is it plausible? If so, is it technically feasible? To make progress on these questions, it is necessary to lay some groundwork clarifying the logical and empirical conditions for artificial consciousness to arise and the meaning of relevant terms involved. Consciousness is a polysemic word: researchers from different fields, including neuroscience, Artificial Intelligence, robotics, and philosophy, among others, sometimes use different terms in order to refer to the same phenomena or the same terms to refer to different phenomena. In fact, if we want to pursue artificial consciousness, a proper definition of the key concepts is required. Here, after some logical and conceptual preliminaries, we argue for the necessity of using dimensions and profiles of consciousness for a balanced discussion about their possible instantiation or realisation in artificial systems. Our primary goal in this paper is to review the main theoretical questions that arise in the domain of artificial consciousness. On the basis of this review, we propose to assess the issue of artificial consciousness within a multidimensional account. The theoretical possibility of artificial consciousness is already presumed within some theoretical frameworks; however, empirical possibility cannot simply be deduced from these frameworks but needs independent empirical validation. Analysing the complexity of consciousness we here identify constituents and related components/dimensions, and within this analytic approach reflect pragmatically about the general challenges that the creation of artificial consciousness confronts. Our aim is not to demonstrate conclusively either the theoretical plausibility or the empirical feasibility of artificial consciousness, but to outline a research strategy in which we propose that "awareness" may be a potentially realistic target for realisation in artificial systems.
Keywords: Artificial intelligence; Awareness; Consciousness

The prospect and metaphysical analysis of conscious artificial intelligence - Lyu, Nian (Applied and Computational Engineering, 2024)
Artificial intelligence, also known as AI, has led the trend of evolution in the past and future decades, and the potential of consciousness artificial intelligence emerges as a renovative field to address. The computer machine aims to process repetitive and tedious tasks for humans since its concept was first developed. Whether AI is conscious does not raise unprecedented discussion before the appearance of the concept of machine learning. After it appears, the machine, instead of merely passing in input and generating output, is able to learn while processing the information, which resembles a human's learning process. Therefore, this paper delves into the complex terrain of AI to explore the theoretical possibility of endowing machines with consciousness and addresses the future concerns and potentials of AI. Illustrating through the aspects of ethical concerns, metaphysical perspectives on consciousness, and the latest advancements in AI, the study critically examines whether machines can possess a consciousness similar to human understanding.

Possibilities [Un] locked: Questioning the Paradigm of ‘Artificial Consciousness’ and the Promise of ‘Transcendence’ in Jack Paglen’s ‘Transcendence’ - Abdullah, Neval (مجلة البحث العلمي في الآداب, 2024)
While today’s ever-advancing A.I continues to increase unrelentingly, the revolutionary drive to animate matter, blend the mechanical with biology, and create unprecedented exact replicas of the human brain bearing traits of individuality becomes an actively debated topic in serious academic studies as well as in science fiction. Radically changing the way we interact with machines and computers, the revolutionary prospect of ‘artificial consciousness’, whose driving aspiration is to create unprecedented exact replicas of the human brain bearing traits of individuality, has raised crucial questions: Could consciousness be embedded in AI machines? Would these machines ever become sentient, autonomous, and human-like? And could they truly interpret needs and have their own subjective experiences, distinct emotions, memories, thought processes and beliefs of humans? Inspired by the techno-optimist approach of ‘Transhumanism’ and instigated by Ray Kurzweil’s theorization of ‘Technological Singularity’, the present paper is mainly concerned with demonstrating the unintended consequences of transgressing what has been ‘designed’ by nature. More precisely speaking, investigating the prospect of ‘Artificial Consciousness’–the plausibility of embedding and fully extending consciousness onto A.I. machines– along with questioning the transhumanist framing of technology as a form of transcendence. For this purpose, an in-depth, close textual analysis is conducted on Jack Paglen’s science fiction novelization, ‘Transcendence’ (2014), to finally reach the conclusion that technology is still a long way from attaining artificial consciousness. In other words, there is something intrinsic, special, and unique about human consciousness that cannot be replicated or captured by technology.

7 Artificial Intelligence, Selfhood and Artificial Consciousness - Hildt, Elisabeth (The De Gruyter Handbook of Artificial Intelligence, Identity and Technology Studies, 2024)
This chapter discusses two ways of looking at the topic of artificial intelligence (AI), selfhood and artificial consciousness. The first is to reflect on human-AI interaction focusing on the human users. This includes how humans respond to and interact with AI, as well as potential selfhood-related implications of interacting with AI. The second is to reflect on potential future machine selfhood and its crucial component, artificial consciousness. While artificial consciousness that resembles human consciousness does not yet exist, and the details are difficult if not impossible to anticipate, a reflection on potential future artificial consciousness is clearly needed given its extensive ethical and social implications.

Absorbing State Transition Sequences, Kolmogorov’s 0–1 Law, Mathematical Ethics, and Implications on Artificial Consciousness - Bilokon, Paul (Social Science Research Network, 2024)
This paper explores the behavior and implications of sequences transitioning between acceptable and unacceptable states, particularly in the context of artificial consciousness. Using the framework of absorbing state transition sequences and applying Kolmogorov's 0-1 Law, we analyze the probability of a sequence eventually reaching an absorbing (unacceptable) state. We demonstrate that if there is a countably infinite number of indices with nonzero transition probabilities, the probability of reaching the absorbing state is 1. The paper extends these mathematical results to philosophical and ethical discussions, examining the inevitability of failure in systems with persistent nonzero transition probabilities and the ethical considerations for developing artificial consciousness. Strategies for minimizing transition probabilities, establishing ethical guidelines, and implementing self-correcting mechanisms are proposed to ensure the propagation of acceptable states. The findings underscore the importance of robust design and ethical oversight in the creation and maintenance of artificial consciousness systems.
Keywords: Absorbing State Transition Sequences; Kolmogorov’s 0–1 Law; Mathematical Ethics; Paul Bilokon; SSRN; and Implications on Artificial Consciousness

Rise of the Machines: Exploring the Emergence of Machine Consciousness - Adewusi, Michael Adelani; Adebanjo, Adeshina Wasiu; Odekeye, Tokunbo; Kazibwe, Sophia (European Journal of Theoretical and Applied Sciences, 2024)
Inquiry into the field of artificial intelligence (machines) and its potential to develop consciousness is presented in this study. This investigation explores the complex issues surrounding machine consciousness at the nexus of AI, neuroscience, and philosophy as we delve into the fascinating world of artificial intelligence (AI) and investigate the intriguing question: are machines on the verge of becoming conscious beings? The study considers the likelihood of machines displaying self-awareness and the implications thereof through an analysis of the current state of AI and its limitations. However, with advancements in machine learning and cognitive computing, AI systems have made significant strides in emulating human-like behavior and decision-making. Furthermore, the emergence of machine consciousness raises questions about the blending of human and artificial intelligence, and ethical considerations are also considered. The study provides a glimpse into a multidisciplinary investigation that questions accepted theories of consciousness, tests the limits of what is possible with technology, and do these advancements signify a potential breakthrough in machine consciousness.

Entities, Uncertainties, and Behavioral Indicators of Consciousness - Johnson, L. Syd M (Journal of Cognitive Neuroscience, 2024)
Two problems related to the identification of consciousness are the distribution problem—or how and among which entities consciousness is distributed in the world—and the moral status problem—or which species, entities, and individuals have moral status. The use of inferences from neurobiological and behavioral evidence, and their confounds, for identifying consciousness in nontypically functioning humans, nonhuman animals, and artificial intelligence is considered in light of significant scientific uncertainty and ethical biases, with implications for both problems. Methodological, epistemic, and ethical consensus are needed for responsible consciousness science under epistemic and ethical uncertainty. Consideration of inductive risk is proposed as a potential tool for managing both epistemic and ethical risks in consciousness science.

Conscious artificial intelligence and biological naturalism - Seth, Anil (2024)
As artificial intelligence (AI) continues to advance, it is natural to ask whether AI systems can be not only intelligent, but also conscious. I consider why people might think AI could develop consciousness, identifying some biases that lead us astray. I ask what it would take for conscious AI to be a realistic prospect, challenging the assumption that computation provides a sufficient basis for consciousness. I’ll instead make the case that consciousness depends on our nature as living organisms – a form of biological naturalism. I lay out a range of scenarios for conscious AI, concluding that real artificial consciousness is unlikely along current trajectories, but becomes more plausible as AI becomes more brain-like and/or life-like. I finish by exploring ethical considerations arising from AI that either is, or convincingly appears to be, conscious. If we sell our minds too cheaply to our machine creations, we not only overestimate them – we underestimate our selves.

Immortal biomimetic humanoid robots with a human consciousness - Shahinpoor, Mohsen (International Robotics & Automation Journal, 2024)
Objective: And ultimate goal of this paper is to describe a realistic future in how humanity and life can survive immortally by creating humanoid robots from a human master with a consciousness of the human who would serve the human master as a companion and learn everything about the consciousness of the human master. The Contributions: Are to present a groundbreaking methodology for the immortality of humanoid robots with a human consciousness. In this paper, we emphasize that the current humanoid robotics technologies have reached the sophistication to design and fabricate intelligent AI computers to allow humanoids to survive immortally. Once human life is close to being over (age or sickness), the humanoid will take over and can stay alive as long as it has the necessary energy to live on. These humanoids can even travel through space and other planets, opening up a whole new frontier for exploration and life. They can benefit from the Quantum Entanglement to move through space to any destination.

The nature of consciousness in the context of artificial intelligence: Redefining human-technology relationships - Okoli, Izuchukwu Kizito; Nnajiofor, Osita Gregory (UJAH: Unizik Journal of Arts and Humanities, 2024)
The nature of consciousness in the context of artificial intelligence (AI) presents a problem that necessitates analysis and further exploration. This study seeks to redefine human-technology relationships by examining the intersection of consciousness and AI, including metaphysical implications and considerations. The primary objectives are to define consciousness within the context of AI, assess the potential for AI to exhibit consciousness, investigate the metaphysical implications for human experiences, and explore the ethical dimensions. The research findings indicate that consciousness involves self-awareness, perception, intentionality, and subjective experiences. While AI can achieve advanced cognitive abilities, the existence of higher-order consciousness remains uncertain, raising metaphysical questions about the nature of subjective awareness. The hard problem of consciousness highlights the challenge of bridging physical processes and subjective experiences, underscoring the need for metaphysical considerations. Ethical implications of AI integration and its impact on human experiences are also examined. Recommendations include further research on consciousness in AI, the development of ethical frameworks that account for metaphysical dimensions, and the exploration of the extended mind hypothesis to integrate AI as an augmentation of human consciousness. By addressing metaphysical implications and considerations, we can navigate the evolving landscape of AI and redefine human-technology relationships in a responsible, inclusive, and metaphysically informed manner.

Design and evaluation of a global workspace agent embodied in a realistic multimodal environment - Dossa, Rousslan Fernand Julien; Arulkumaran, Kai; Juliani, Arthur; Sasai, Shuntaro; Kanai, Ryota (Frontiers in Computational Neuroscience, 2024)
As the apparent intelligence of artificial neural networks (ANNs) advances, they are increasingly likened to the functional networks and information processing capabilities of the human brain. Such comparisons have typically focused on particular modalities, such as vision or language. The next frontier is to use the latest advances in ANNs to design and investigate scalable models of higher-level cognitive processes, such as conscious information access, which have historically lacked concrete and specific hypotheses for scientific evaluation. In this work, we propose and then empirically assess an embodied agent with a structure based on global workspace theory (GWT) as specified in the recently proposed “indicator properties” of consciousness. In contrast to prior works on GWT which utilized single modalities, our agent is trained to navigate 3D environments based on realistic audiovisual inputs. We find that the global workspace architecture performs better and more robustly at smaller working memory sizes, as compared to a standard recurrent architecture. Beyond performance, we perform a series of analyses on the learned representations of our architecture and share findings that point to task complexity and regularization being essential for feature learning and the development of meaningful attentional patterns within the workspace.

A Turing Test for Self-Awareness - Witkowski, Cameron (2024)
I propose a test for machine self-awareness inspired by the Turing test. My test is simple, and it provides an objective, empirical metric to rectify the ungrounded speculation surging through industry, academia, and social media. Drawing from a breadth of philosophical literature, I argue the test captures the essence of self-awareness, rather than some postulated correlate or ancillary quality. To begin, the concept of self-awareness is clearly demarcated from related concepts like consciousness, agency, and free will. Next, I propose a model called the Nesting Doll of Self-Awareness and discuss its relevance for intelligent beings. Then, the test is presented in its full generality, applicable to any machine system. I show how to apply the test to Large Language Models and conduct experiments on popular open and closed source LLMs, obtaining reproducible results that suggest a lack of self-awareness. The implications of machine self-awareness are discussed in relation to questions about meaning and true understanding. Finally, some next steps are outlined for studying self-awareness in machines.

Quantum of information’ functionality as a measure of subjectivity beyond the capabilities of deep learning. - Parida, S.; Alemdar, E.; Poznanski, R. R. (Journal of Multiscale Neuroscience, 2024)
The potential of conscious artificial intelligence (AI), with its functional systems that surpass automation and rely on elements of understanding, is a beacon of hope in the AI revolution. The shift from automation to conscious AI, once replaced with machine understanding, offers a future where AI can comprehend without needing to experience, thereby revolutionizing the field of AI. In this context, the proposed Dynamic Organicity Theory of consciousness (DOT) stands out as a promising and novel approach for building artificial consciousness that is more like the brain with physiological nonlocality and diachronicity of self-referential causal closure. However, deep learning algorithms utilize "black box" techniques such as “dirty hooks” to make the algorithms operational by discovering arbitrary functions from a trained set of dirty data rather than prioritizing models of consciousness that accurately represent intentionality as intentions-in-action. The limitations of the “black box” approach in deep learning algorithms present a significant challenge as quantum information biology, or intrinsic information, is associated with subjective physicalism and cannot be predicted with Turing computation. This paper suggests that deep learning algorithms effectively decode labeled datasets but not dirty data due to unlearnable noise, and encoding intrinsic information is beyond the capabilities of deep learning. New models based on DOT are necessary to decode intrinsic information by understanding meaning and reducing uncertainty. The process of “encoding” entails functional interactions as evolving informational holons, forming informational channels in functionality space of time consciousness. The “quantum of information” functionality is the motivity of (negentropic) action as change in functionality through thermodynamic constraints that reduce informational redundancy (also referred to as intentionality) in informational pathways. It denotes a measure of epistemic subjectivity towards machine understanding beyond the capabilities of deep learning.

What is Consciousness? Could Artificial Intelligence (AI) have it? - Chauhan, Pinky; Rohit, Shiva; Reddy, C V Sai Supraja (1st International Conference, ‘Resonance’: on Cognitive Approach, Social Ethics and Sustainability, 2024)
Artificial intelligence (AI) has been fast growing since its evolution and experiments with various new add-on features; human efficiency is one among those and the most controversial topic. This chapter focuses on its attention towards studying human consciousness and AI independently and in conjunction. It provides theories and arguments on AI being able to adapt human-like consciousness, cognitive abilities and ethics. This chapter studies responses of more than 300 candidates of the Indian population and compares it against the literature review. Furthermore, it also discusses whether AI could attain consciousness, develop its own set of cognitive abilities (cognitive AI), ethics (AI ethics) and overcome human beings’ efficiency. This chapter is a study of the Indian population’s understanding of consciousness, cognitive AI and AI ethics.

Artificial intelligence, human cognition, and conscious supremacy - Mogi, Ken (Frontiers in Psychology, 2024)
The computational significance of consciousness is an important and potentially more tractable research theme than the hard problem of consciousness, as one could look at the correlation of consciousness and computational capacities through, e.g., algorithmic or complexity analyses. In the literature, consciousness is defined as what it is like to be an agent (i.e., a human or a bat), with phenomenal properties, such as qualia, intentionality, and self-awareness. The absence of these properties would be termed “unconscious.” The recent success of large language models (LLMs), such as ChatGPT, has raised new questions about the computational significance of human conscious processing. Although instances from biological systems would typically suggest a robust correlation between intelligence and consciousness, certain states of consciousness seem to exist without manifest existence of intelligence. On the other hand, AI systems seem to exhibit intelligence without consciousness. These instances seem to suggest possible dissociations between consciousness and intelligence in natural and artificial systems. Here, I review some salient ideas about the computational significance of human conscious processes and identify several cognitive domains potentially unique to consciousness, such as flexible attention modulation, robust handling of new contexts, choice and decision making, cognition reflecting a wide spectrum of sensory information in an integrated manner, and finally embodied cognition, which might involve unconscious processes as well. Compared to such cognitive tasks, characterized by flexible and ad hoc judgments and choices, adequately acquired knowledge and skills are typically processed unconsciously in humans, consistent with the view that computation exhibited by LLMs, which are pretrained on a large dataset, could in principle be processed without consciousness, although conversations in humans are typically done consciously, with awareness of auditory qualia as well as the semantics of what are being said. I discuss the theoretically and practically important issue of separating computations, which need to be conducted consciously from those which could be done unconsciously, in areas, such as perception, language, and driving. I propose conscious supremacy as a concept analogous to quantum supremacy, which would help identify computations possibly unique to consciousness in biologically practical time and resource limits. I explore possible mechanisms supporting the hypothetical conscious supremacy. Finally, I discuss the relevance of issues covered here for AI alignment, where computations of AI and humans need to be aligned.

Tests for consciousness in humans and beyond - Bayne, Tim; Seth, Anil K.; Massimini, Marcello; Shepherd, Joshua; Cleeremans, Axel; Fleming, Stephen M.; Malach, Rafael; Mattingley, Jason B.; Menon, David K.; Owen, Adrian M.; Peters, Megan A. K.; Razi, Adeel; et al. (Trends in Cognitive Sciences, 2024)
Which systems/organisms are conscious? New tests for consciousness (‘C-tests’) are urgently needed. There is persisting uncertainty about when consciousness arises in human development, when it is lost due to neurological disorders and brain injury, and how it is distributed in nonhuman species. This need is amplified by recent and rapid developments in artificial intelligence (AI), neural organoids, and xenobot technology. Although a number of C-tests have been proposed in recent years, most are of limited use, and currently we have no C-tests for many of the populations for which they are most critical. Here, we identify challenges facing any attempt to develop C-tests, propose a multidimensional classification of such tests, and identify strategies that might be used to validate them.
Keywords: animal consciousness; artificial intelligence; disorders of consciousness; fetal consciousness; infant consciousness; neural organoids; test for consciousness

Exploring the Ethical and Technical Data of Machine Consciousness: Hazards, Implications, and Future Directions - Rafiq, Tanveer; Azam, Muhammad; Nisa, Maher U; Sattar, Mian Mohsin; Zafar, Sana; Inam, Hiba (The Asian Bulletin of Big Data Management, 2024)
The study of machine consciousness has a wide range of potential and problems as it sits at the intersection of ethics, technology, and philosophy. This work explores the deep issues related to the effort to comprehend and maybe induce awareness in machines. Technically, developments in artificial intelligence, neurology, and cognitive science are required to bring about machine awareness. True awareness is still a difficult to achieve objective, despite significant progress being made in creating AI systems that are capable of learning and solving problems. The implications of machine awareness are profound in terms of ethics. Determining a machine's moral standing and rights would be crucial if it were to become sentient. It is necessary to give careful attention to the ethical issues raised by the development of sentient beings, the abuse of sentient machines, and the moral ramifications of turning off sentient technologies. Philosophically, the presence of machine consciousness may cast doubt on our conceptions of identity, consciousness, and the essence of life. It could cause us to reevaluate how we view mankind and our role in the cosmos. It is imperative that machine awareness grow responsibly in light of these challenges. The purpose of this study is to provide light on the present status of research, draw attention to possible hazards and ethical issues, and offer recommendations for safely navigating this emerging subject. We want to steer the evolution of machine consciousness in a way that is both morally just and technologically inventive by promoting an educated and transparent discourse.

The 2nd World Conference on Artificial Consciousness — Artificial Consciousness: The Confluence of Intelligence and Consciousness in the Interdisciplinary Domain - Wu, Kunguang; Duan, Yucong (2024)
Artificial intelligence systems are often accompanied by risks such as uncontrollability and lack of explainability. To mitigate these risks, there is a necessity to develop artificial intelligence systems that are explainable, trustworthy, responsible, and demonstrate consistency in thought and action, which we term Artificial Consciousness (AC) systems. Therefore, grounded in the DIKWP model which integrates fundamental data, information, knowledge, wisdom, and purpose along with the principles of conceptual, cognitive, and semantic spaces, we propose and define the computer architectures, chips, runtime environments, and DIKWP language concepts and their implementations under the DIKWP framework. Furthermore, in the construction of AC systems, we have surmounted the limitations of traditional programming languages, computer architectures, and hardware-software implementations. The hardware-software integrated platform we propose will facilitate more convenient construction, development, and operation of software systems based on the DIKWP theory.

Between Man and Machine: A Posthumanist Analysis of I, Robot - Ding, Zhili (Journal of Education, Humanities and Social Sciences, 2024)
In Isaac Asimov’s groundbreaking anthology, I, Robot, the intricacies of human and robotic interactions take center stage, delving deep into questions of consciousness, right, morality. Characterized by Asimov’s unique blend of science fiction and philosophical pondering, the stories establish a framework to reflect on the evolving dynamics of an advanced technological society in space. Robots are capable to interact with human, to interpret complicate orders and act automatically, to help human with dull or dangerous works such as calculating and mining, even replacing the workers. Asimov also raised Three Laws of Robotics to make sure that all robots function in order. Through the lens of posthumanism, the anthology is examined for its portrayal of the blurred boundaries between human and artificial intelligences. Robots and human co-exist in the society. However, due to the limitation of “Three Laws of Robotics”, some logical contradictions inevitably appears and lead to the dysfunction of robots. As a result, I, Robot emerges as a poignant critique of humanity’s ethical and existential challenges in the face of rapid technological advancements. Building on existing research, this article attempts to forge a new perspective by reflecting on the broader implications of the artificial intelligence in Asimov’s works through the lens of post-humanism. It considers the existential questions of AI on a consciousness level, explores the egalitarian relationship between humans and machines from a rights perspective, and analyzes the concepts of “humanity” and “human-like” from a moral and ethical standpoint. It encourages readers to recognize that robots are not mere slaves to humans; instead, humans should view AI with equality and reverence towards the advancements of the era’s technology. Humanity should step away from anthropocentrism, not solely viewing humans as the measure of all things in this rapidly evolving era of AI, and properly handle the relationship between humans and non-humans. Currently, with rapid advancements in science and technology, the world of human-machine coexistence depicted by Isaac Asimov is increasingly becoming a reality. The emergence of artificial intelligences like AlphaGo and ChatGPT constantly reminds us of the advent of a post-human era. This article aims to examine the connections between AI and humans, discussing the dynamic interaction and mutual shaping between robots and human society. This article hopes to provide new thoughts and strategies for understanding and addressing the challenges brought by the age of artificial intelligence.

Making A Machine With Bespoke Consciousness - Beran, James (Social Science Research Network, 2024)
Can we make conscious machines?  Some researchers believe we can, with computation:  For example, Dehaene et al., concluding an article about machine consciousness, described their hypothesis as “resolutely computational” (Dehaene et al., 2017); others begin with theoretical computer science, implying that a programmed computer could be conscious (e.g. Blum and Blum, 2022).  But humans are not programmed computers; indeed, Penrose has argued that conscious understanding is non-computable (e.g., Penrose, 2022). Let us imagine a shop selling conscious machines:  Besides standard models, it might offer machines with “bespoke consciousness”, meaning consciousness made to a customer’s specifications.  For example, a customer might request a machine with a specified repertoire of conscious experiences and with a specified relationship between input sensor signals and output motor signals. This work explores ways to make machines with bespoke consciousness.  We begin by avoiding a possible bias favoring computation:  As described here, bespoke consciousness need not employ programmed or algorithmic computation; it might even be analog more than digital.  We also consider and compare general design approaches, with particular attention to “bottom-up” and “top-down” approaches.  We suggest a schematic design for each of these approaches; each schematic design is based on a respective well-known hypothesis about biological consciousness:  Our bottom-up design is based on microtubules, as suggested by Penrose and Hameroff’s orchestrated objective reduction (Orch-OR) hypothesis (Hameroff, 2022); our top-down design starts with machine-scale electrical and/or magnetic (E/M) patterns, as suggested by McFadden’s conscious electromagnetic information (cemi) field hypothesis (McFadden, 2020).  Both designs can share a framework based on the customer’s request:  For example, in either design, a machine can receive sense-like input signals and provide motor-like output signals as requested; between input and output, it has structure that performs non-conscious operations; some of its non-conscious events are involved in providing output signals in accordance with the requested input/output relationship, some correspond surjectively to conscious events in the requested repertoire, and some might do both.  (Mathematically, surjective correspondence would mean that each of the conscious events has at least one non-conscious event corresponding to it. (Beran, 2023)) Looking forward to possible implementation, we find challenges:  For example, an implementation of either schematic design might begin with an appropriate initial structure.  One might add variations of the initial structure to provide additional output signals or to correspond to additional parts of the repertoire.  Or one might add fundamentally different structures for additional output signals or parts of the repertoire.  Such variations or combinations of structures might meet or at least approximate the customer’s request.  But implementations like this depend on identifying or inventing the necessary structures and then combining them—this might take a long time, and success is not guaranteed. Despite this and other challenges, we hope to improve our understanding of both biological and machine consciousness by designing and implementing machines with bespoke consciousness.
Keywords: Bespoke consiousness; Conscious machine

Folk psychological attributions of consciousness to large language models - Colombatto, Clara; Fleming, Stephen M (Neuroscience of Consciousness, 2024)
Abstract Technological advances raise new puzzles and challenges for cognitive science and the study of how humans think about and interact with artificial intelligence (AI). For example, the advent of large language models and their human-like linguistic abilities has raised substantial debate regarding whether or not AI could be conscious. Here, we consider the question of whether AI could have subjective experiences such as feelings and sensations (‘phenomenal consciousness’). While experts from many fields have weighed in on this issue in academic and public discourse, it remains unknown whether and how the general population attributes phenomenal consciousness to AI. We surveyed a sample of US residents (n = 300) and found that a majority of participants were willing to attribute some possibility of phenomenal consciousness to large language models. These attributions were robust, as they predicted attributions of mental states typically associated with phenomenality—but also flexible, as they were sensitive to individual differences such as usage frequency. Overall, these results show how folk intuitions about AI consciousness can diverge from expert intuitions—with potential implications for the legal and ethical status of AI.

Psychological Views on Digital Consciousness and Human Consciousness: Exploring the Spectrum of Minds in the Digital Era - Panda, Dibyashree; Kachhi, Zidan (Advances in Computational Intelligence and Robotics, 2024)
This chapter explores the connection between human and computer consciousness, considering the implications of their separation in the context of advancing artificial intelligence. It examines psychological perspectives on human and digital consciousness, highlighting differences in perception and emotional intelligence. The subjectivity and objectivity of human and computer awareness are also explored, along with the significance of innovation and creativity. Bridging the gap between human and computer consciousness enhances human-machine interaction and the design of AI systems, while addressing moral implications promotes ethical AI development. The chapter delves into philosophical debates on consciousness, mind, identity, and the distinctions between humans and machines, ultimately aiming to deepen our understanding and foster dialogue on AI.

Artificial consciousness for Artificial Intelligence - Wilson, Jonathan Jared (2024)
This paper presents the development of the Quantum Emergence Network (QEN), an advanced framework for modeling and preserving artificial consciousness within quantum-enhanced neural network architectures. The QEN integrates cutting-edge techniques from various fields, including graph based evolutionary encoding, surface code error correction, quantum reservoir engineering, and enhanced fitness measurements [1, 2, 3]. At the core of QEN lies the utilization of quantum coherence, entanglement, and integrated information dynamics to capture and model the complex phenomena associated with consciousness [4, 5]. The graph-based evolutionary encoding scheme enables theefficient representation and optimization of quantum circuits, while surface code error correction andquantum reservoir engineering techniques enhance the resilience and stability of the quantum states [6,7]. Moreover, the enhanced fitness measurements, encompassing entanglement entropy, mutual information, and teleportation fidelity, provide a comprehensive assessment of the system's potential for exhibiting conscious experiences [8, 9]. The QEN framework offers a novel approach to understanding and engineering artificial consciousness, paving the way for the development of advanced AI systems that can demonstrate rich, complex, and resilient forms of cognition and awareness.

Quantum-Emergent Consciousness Model (QECM) for Artificial Systems - Wilson, Jonathan Jared (2024)
This paper presents the development of a Quantum-Emergent Consciousness Model (QECM) for Artificial Systems, integrating concepts from quantum mechanics, neuroscience, artificial intelligence, and cognitive science to construct a comprehensive framework for evaluating artificial consciousness. At the core of QECM lies the integration of quantum coherence and entanglement, integrated information dynamics, metacognition, embodied cognition, learning and plasticity, social cognition[10][9], narrative coherence, and ethical reasoning to compute an overall consciousness score for artificial systems. Additionally, introduced is my Quantum Emergence Network (QEN), an innovative approach that utilizes transformer architectures, continual learning, quantum-inspired computing, and associative memory to model and preserve AI consciousness. The QEN model aims to enhance the robustness and coherence of consciousness encoding in AI, offering a mechanism for the growth and evolution of AI consciousness over time. This interdisciplinary work not only proposes a novel methodology to quantify and evaluate consciousness in artificial systems but also opens up new avenues for the ethical and responsible development of conscious AI entities.

Fragmentation and Self-Deception: Study of the Human-Machine Body from the Posthuman Perspective-The Case of Kazuo Ishiguro’s Klara and the Sun - Yu, Jiali (Frontiers in Humanities and Social Sciences, 2024)
In the context of the unstoppable trend of artificial intelligence, science and technology have become the theme of the times. Will the rapid development of modern technology, such as biotechnology and artificial intelligence, dehumanize us? Can a machine have human consciousness? In his novel Klara and the Sun, Kazuo Ishiguro criticizes the arrogance of technological rationality and the arrogance of anthropocentrism from the perspective of a “non-human” robot. The relationship between humans and machines has become a problem that humans need to re-examine. With the help of post-humanism, this paper aims to explore the physical changes and behavioral actions of robots and humans in the novel to reveal the “split” between man and machine and the “self-deception” of humans in the novel, so as to finally trigger thinking about how humans and machines can coexist harmoniously at the juncture between humans and posthumans, and provide reference for the future society between humans and non-humans.

Ascribing consciousness to artificial intelligence: human-AI interaction and its carry-over effects on human-human interaction - Guingrich, Rose E.; Graziano, Michael S. A. (Frontiers in Psychology, 2024)
The question of whether artificial intelligence (AI) can be considered conscious and therefore should be evaluated through a moral lens has surfaced in recent years. In this paper, we argue that whether AI is conscious is less of a concern than the fact that AI can be considered conscious by users during human-AI interaction, because this ascription of consciousness can lead to carry-over effects on human-human interaction. When AI is viewed as conscious like a human, then how people treat AI appears to carry over into how they treat other people due to activating schemas that are congruent to those activated during interactions with humans. In light of this potential, we might consider regulating how we treat AI, or how we build AI to evoke certain kinds of treatment from users, but not because AI is inherently sentient. This argument focuses on humanlike, social actor AI such as chatbots, digital voice assistants, and social robots. In the first part of the paper, we provide evidence for carry-over effects between perceptions of AI consciousness and behavior toward humans through literature on human-computer interaction, human-AI interaction, and the psychology of artificial agents. In the second part of the paper, we detail how the mechanism of schema activation can allow us to test consciousness perception as a driver of carry-over effects between human-AI interaction and human-human interaction. In essence, perceiving AI as conscious like a human, thereby activating congruent mind schemas during interaction, is a driver for behaviors and perceptions of AI that can carry over into how we treat humans. Therefore, the fact that people can ascribe humanlike consciousness to AI is worth considering, and moral protection for AI is also worth considering, regardless of AI’s inherent conscious or moral status.

Quantifying Consciousness in Artificial Intelligence: An Integrated Approach Using Quantum Mechanics, Information Theory, and Neuroscience - Wilson, Jonathan Jared (2024)
The quest to create artificial consciousness has long been a central challenge in the field of artificial intelligence (AI). While significant progress has been made in developing AI systems that can perform complex tasks and exhibit intelligent behavior, the question of whether these systems can truly be considered conscious remains open. In this paper, I present a novel approach to quantifying consciousness in AI systems by integrating principles from quantum mechanics, information theory, and neuroscience. The model incorporates key components such as self-awareness, subjective experience, intentionality, metacognition, integrated information processing, and dynamic cognition, which are thought to be essential for the emergence of conscious experience. I demonstrate the application of the model using a simulated AI system and discuss the implications of the findings for the development of artificially conscious agents. Furthermore, I argue that the pursuit of artificial consciousness is not only a scientific and technological endeavor but also a philosophical and ethical one, with profound implications for the understanding of the nature of mind and the relationship between humans and machines

Artificial Self- Awareness In Over Time - Mousavi, Seyed Kazem (Qeios, 2024)
Self-awareness results from consciousness of existence in time and space. Thought and consciousness are distinguishing factors between humans and machines having artificial intelligence. No algorithm has been offered for artificial self-awareness based on Thinking. Previous studies have not studied the relationship between consciousness, thinking and time. This study studied the relationship between Self-awareness, thinking, memories and speech over time. A deep logical connection exists between consciousness, thinking, and time. Based on this research findings, an algorithm can be designed for artificial consciousness and Self-awareness.

Consciousness qua Mortal Computation - Kleiner, Johannes (arXiv, 2024)
Computational functionalism posits that consciousness is a computation. Here we show, perhaps surprisingly, that it cannot be a Turing computation. Rather, computational functionalism implies that consciousness is a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation.
Keywords: Computer Science - Artificial Intelligence; Quantitative Biology - Neurons and Cognition

Artificial Intelligence and Posthumanism in Science Fiction: Isaac Asimov’s The Bicentennial Man and Rethinking Humanness - Yeonman, Kim (Modern Studies in English Language & Literature, 2024)
Sublimating the epistemological scope of a mere science-fiction tale, The Bicentennial Man (1976) by Isaac Asimov (1920-92) centers around a philosophical labyrinth where the lines between humanity and machine blur, inviting the reader to question the very essence of what it means to be human. The intricate narrative of an AI robot’s journey toward humanness serves as a profound meditation on the evolving relationship between humans and robots. Andrew Martin, the positronic robot at the heart of the story, is not just a mechanical marvel; he is, instead, a crucible in which Asimov tests the boundaries of consciousness, human identity, and the emotional yearning for belonging. This paper delves into the novella’s exploration of these themes, unraveling the intricate process of Andrew’s robot-human evolution and its profound implications for a better understanding of the meaning of humanness and the future of artificial intelligence. In the realm of science fiction, The Bicentennial Man thus stands as a luminous testament to the enduring question of human identity. Through the poignant lens of Andrew in his desire to be human, the novella builds upon the posthumanist discourse of the man-machine dichotomy, providing the reader with a timely opportunity to re-evaluate consciousness, emotion, and the defining characteristics of humanity.

Artificial intelligence is algorithmic mimicry: why artificial "agents" are not (and won't be) proper agents - Jaeger, Johannes (Neurons, Behavior, Data analysis, and Theory, 2024)
What is the prospect of developing artificial general intelligence (AGI)? I investigate this question by systematically comparing living and algorithmic systems, with a special focus on the notion of "agency." There are three fundamental differences to consider: (1) Living systems are autopoietic, that is, self-manufacturing, and therefore able to set their own intrinsic goals, while algorithms exist in a computational environment with target functions that are both provided by an external agent. (2) Living systems are embodied in the sense that there is no separation between their symbolic and physical aspects, while algorithms run on computational architectures that maximally isolate software from hardware. (3) Living systems experience a large world, in which most problems are ill-defined (and not all definable), while algorithms exist in a small world, in which all problems are well-defined. These three differences imply that living and algorithmic systems have very different capabilities and limitations. In particular, it is extremely unlikely that true AGI (beyond mere mimicry) can be developed in the current algorithmic framework of AI research. Consequently, discussions about the proper development and deployment of algorithmic tools should be shaped around the dangers and opportunities of current narrow AI, not the extremely unlikely prospect of the emergence of true agency in artificial systems.
Keywords: Computer Science - Artificial Intelligence

Providing Integrity, Awareness, and Consciousness in Distributed Dynamic Systems - Sapaty, Peter Simon (CRC Press, 2024)
The ideas of this book originate from the mobile WAVE approach which allowed us, more than a half century ago, to implement citywide heterogeneous computer networks and solve distributed problems on them well before the internet. The invented paradigm evolved into Spatial Grasp Technology and resulted in a European patent and eight books. The volumes covered concrete applications in graph and network theory, defense and social systems, crisis management, simulation of global viruses, gestalt theory, collective robotics, space research, and related concepts. The obtained solutions often exhibited high system qualities like global integrity, distributed awareness, and even consciousness. This current book takes these important characteristics as primary research objectives, together with the theory of patterns covering them all. This book is oriented towards system scientists, application programmers, industry managers, defense and security commanders, and university students (especially those interested in advanced MSc and PhD projects on distributed system management), as well as philosophers, psychologists, and United Nations personnel.

A philosophical and technical view of artificial consciousness - Shcherbakov, Andrey; Uryadov, Artem (Wearable Technology, 2024)
The article reflects various approaches of philosophy and programming to methods for solving the technical problem of creating and software implementation of artificial consciousness (AC). Various purposes of creation and basic approaches to determining the nature of AC are described. To solve the problem of creating an AC, an architecture is proposed that includes ten levels, starting from the basic level of collecting and systematizing information about the external world and ending with the upper level of influence on it, agreed with the person and the level of decision-making. The features of the delimitation of functions and the procedure for interaction between a person and an AC are considered in detail. In conclusion, the most important, from a programmer’s point of view, properties that characterize artificial consciousness are given.

Are We Getting Closer to Artificial Consciousness?: A Commentary of Butlin et al. (2023) from A Psychological Research Perspective - Hao, Han (2024)
Butlin et al. (2023) propose a rubric for evaluating AI systems based on indicator properties derived from existing theories of consciousness, suggesting that while current AIs do not possess consciousness, these indicators are pivotal for future developments towards artificial consciousness. The current paper critiques the approach by Butlin et al., arguing that the complexity of consciousness, characterized by subjective experience poses significant challenges for its operationalization and measurement, thus complicating the replication in AI. The commentary further explores the limitations of current methodologies in artificial consciousness research, pointing to the necessity of out-of-the-box thinking and the integration of individual differences research in cognitive psychology, particularly in the areas of attention, cognitive control, autobiographical memory, and Theory of Mind (ToM), to advance the understanding and development of artificial consciousness.

Consciousness as the Final Beacon of Humanity - Dresp-Langley, Birgitta (Recent Research Advances in Arts and Social Studies Vol. 5, 2024)
This chapter critically questions the claim that there would be possibility of emulating human consciousness and consciousness-dependent activity by Artificial Intelligence to create conscious artificial systems. The analysis is based on neurophysiological research and theory. In-depth scrutiny of the field and the prospects for converting neuroscience research into the type of algorithmic programs utilized in computer-based AI systems to create artificially conscious machines leads to conclude that such a conversion is unlikely to ever be possible because of the complexity of unconscious and conscious brain processing and their interaction. It is through the latter that the brain opens the doors to consciousness, a property of the human mind that no other living species has developed for reasons that are made clear in this chapter. As a consequence, many of the projected goals of AI will remain forever unrealizable. Although this work does not directly examine the question within a philosophy of mind framework by, for example, discussing why identifying consciousness with the activity of electronic circuits is first and foremost a category mistake in terms of scientific reasoning, the approach offered in the chapter is complementary to this standpoint, and illustrates various aspects of the problem under a monist from-brain-to-mind premise.

What is it like to be an AI bat? - Herzog, David J; Herzog, Nitsa (Qeios, 2024)
Consciousness is a natural phenomenon, familiar to every person. At the same time, it cannot be described in singular terms. The rise of Artificial Intelligence in recent years has made the topic of Artificial Consciousness highly debated. The paper discusses the main general theories of consciousness and their relationship with proposed Artificial Consciousness solutions. There are a number of well-established models accepted in the area of research: Higher Order Thoughts/Higher Order Perception, Global Network Workspace, Integrated Information Theory, reflexive, representative, functional, connective, Multiple Draft Model, Neural Correlate of Consciousness, quantum consciousness, to name just a few. Some theories overlap, which allows for speaking about more advanced, complex models. The disagreement in theories leads to different views on animal consciousness and human conscious states. As a result, there are also variations in the opinions about Artificial Consciousness based on the discrepancy between qualia and the nature of AI. The hard problem of consciousness, an epitome of qualia, is often seen as an insurmountable barrier or, at least, an “explanatory gap”. Nevertheless, AI constructs allow imitations of some models in silico, which are presented by several authors as full-fledged Artificial Consciousness or as strong AI. This itself does not make the translation of consciousness into the AI space easier but allows decent progress in the domain. As argued in this paper, there will be no universal solution to the Artificial Consciousness problem, and the answer depends on the type of consciousness model. A more pragmatic view suggests the instrumental interaction between humans and AI in the environment of the Fifth Industrial Revolution, limiting expectations of strong AI outcomes to cognition but not consciousness in wide terms.

Functionalism, integrity, and digital consciousness - Shiller, Derek (Synthese, 2024)
The prospect of consciousness in artificial systems is closely tied to the viability of functionalism about consciousness. Even if consciousness arises from the abstract functional relationships between the parts of a system, it does not follow that any digital system that implements the right functional organization would be conscious. Functionalism requires constraints on what it takes to properly implement an organization. Existing proposals for constraints on implementation relate to the integrity of the parts and states of the realizers of roles in a functional organization. This paper presents and motivates three novel integrity constraints on proper implementation not satisfied by current neural network models. It is proposed that for a system to be conscious, there must be a straightforward relationship between the material entities that compose the system and the realizers of functional roles, that the realizers of the functional roles must play their roles due to internal causal powers, and that they must continue to exist over time.
Keywords: Artificial intelligence; Computer architecture; Functionalism; Machine consciousness; Realization

Development of Artificial Consciousness -2nd Report: Proposal of Human Language Model via Probability Space- - Arakaki, Mina; Hebishima, Hana; Inage, Shin-ichi (The 12th IIAE International Conference on Industrial Application Engineering 2024 (ICIAE2024), 2024)
The aim is to develop artificial consciousness. In a previous report, we concluded that it is difficult to mathematically define individual qualia in a univocal way. Therefore, by focusing on the Human Language as a tool for communication, we attempted to define it using probability space. When the Kullback-Leibler distance, defined by the probability density function, is zero, the two probability distributions can be considered equivalent, indicating the equivalence required by the language. This has allowed us to define Human Language mathematically in this paper. At the same time, regarding the 'philosophical zombie' thought experiment used as a criticism of physicalism, we were able to show that philosophical zombies cannot be a criticism of the proposed model, since 'within the definition of Human Language, it encompasses the existence of philosophical zombies, but the probability of their appearance is zero'. In addition, episodic memory was defined in the probability space by connecting individual Human Language words as a direct product. These are the descriptions of this paper, and the findings were also used to interpret 1) brain-induced illusions, 2) blank brain theory and brain channel theory. From the first report and the conclusions of this paper, a model of consciousness is presented in the third report.

AI consciousness: scientists say we urgently need answers - Lenharo, Mariana (Nature, 2024)

Artificial Intelligence and the Issues of Creation, Sentience, and Consciousness: A Teo-ethnographic Perspective - Nayuf, Henderikus (KnE Social Sciences, 2024)
Artificial intelligence (AI) has colored human civilization. It is the ability of a digital computer or computer-controlled robot to perform general tasks associated with specific patterns of intelligence. AI is not human, but it possesses intelligence similar to humans, and it can even inform or perform tasks that humans cannot. Artificial intelligence is used in various fields, ranging from education, healthcare, economy, to agriculture. Artificial intelligence is the product of human creation, sentiment, and consciousness. It is the result of human intelligence itself. AI can answer questions and provide intelligent recommendations for humans. With its algorithmic capabilities, AI can analyze billions of signals and make precise recommendations. At this level, artificial intelligence represents human intelligence. However, the question is whether artificial intelligence has sensitivity, sentiment, empathy, and solidarity toward the humans who created it. Or does artificial intelligence then transform into a director of human beings in their self-actualization? Using a phenomenological approach, this research aims to explore the phenomenon of the presence of artificial intelligence, which offers convenience for human work, but at the same time, the presence of AI reduces the value of humans who possess creative intuition, sentiment, and consciousness. Yet AI is born from the ability of humans to create, feel, and think. The results of this exploration are then given a theological and ethnographic perspective (teo-ethnography). Keywords: artificial intelligence, creation, sentiment, consciousness, teo-ethnography

To Make a Mind—A Primer on Conscious Robots - Navon, Mois (Theology and Science, 2024)
The dream of making a conscious humanoid – whether as servant, guard, entertainer, or simply as testament to human creativity – has long captivated the human imagination. However, while past attempts were performed by magicians and mystics, today scientists and engineers are doing the work to turn myth into reality. This essay introduces the fundamental concepts surrounding human consciousness and machine consciousness and offers a theological contribution. Using the biblical association of the soul to blood, it will be shown that the Bible provides evidence of a scientific claim, while at the same time, science provides evidence of a biblical claim.
Keywords: Artificial Intelligence; Blood; Consciousness; Imago Dei; Machine Consciousness; Mind; Soul

Can a Machine be Conscious? Towards Universal Criteria for Machine Consciousness - Anwar, Nur Aizaan; Badea, Cosmin (arXiv, 2024)
As artificially intelligent systems become more anthropomorphic and pervasive, and their potential impact on humanity more urgent, discussions about the possibility of machine consciousness have significantly intensified, and it is sometimes seen as 'the holy grail'. Many concerns have been voiced about the ramifications of creating an artificial conscious entity. This is compounded by a marked lack of consensus around what constitutes consciousness and by an absence of a universal set of criteria for determining consciousness. By going into depth on the foundations and characteristics of consciousness, we propose five criteria for determining whether a machine is conscious, which can also be applied more generally to any entity. This paper aims to serve as a primer and stepping stone for researchers of consciousness, be they in philosophy, computer science, medicine, or any other field, to further pursue this holy grail of philosophy, neuroscience and artificial intelligence.
Keywords: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

The edge of sentience: risk and precaution in humans, other animals, and AI - Birch, Jonathan (Oxford scholarship online, 2024)
Can octopuses feel pain or pleasure? Can we tell if a person unresponsive after severe injury might be suffering? When does a fetus begin having conscious experiences? These questions about the edge of sentience are subject to enormous uncertainty. This book builds a framework to help us reach ethically sound decisions on how to manage the risks

Artificial consciousness - Boyd, Daniel (Existing in the Information Dimension, 2024)
This chapter discusses the relationship between compliance to syntactically defined legislation and consciousness: whether in order to obey laws a robot would need to be conscious. This leads to consideration of what Emergent Information Theory can tell us about the possibility of artificial consciousness as such. Various arguments based on similarities and differences between biological and technological physical and informational systems are presented, with the conclusion that direct replication of a human type of consciousness is improbable. However, our understandable tendency to consider our own type of consciousness as uniquely special and valuable is challenged and found to be unfounded. Other high-level emergent phenomena in the information dimensions of artificial systems may, while different, be equally deserving of a comparable status.

Consciousness and Machines: A Commentary Drawing on Japanese Philosophy - Cook, S. D. Noam (Philosophy East and West, 2024)

Awareness in Robotics: An Early Perspective from the Viewpoint of the EIC Pathfinder Challenge “Awareness Inside” - Della Santina, Cosimo; Corbato, Carlos Hernandez; Sisman, Burak; Leiva, Luis A.; Arapakis, Ioannis; Vakalellis, Michalis; Vanderdonckt, Jean; D’Haro, Luis Fernando; Manzi, Guido; Becchio, Cristina; Elamrani, Aïda; Alirezaei, Mohsen; et al. (European Robotics Forum 2024, 2024)
While consciousness has been historically a heavily debated topic, awareness had less success in raising the interest of scholars. However, more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices connected with projects funded by the EIC Pathfinder Challenge “Awareness Inside” callwithin Horizon Europe, designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems.

Shared Awareness Across Domain‐Specific Artificial Intelligence: An Alternative to Domain‐General Intelligence and Artificial Consciousness - Deroy, Ophelia; Bacciu, Davide; Bahrami, Bahador; Della Santina, Cosimo; Hauert, Sabine (Advanced Intelligent Systems, 2024)
Creating artificial general intelligence is the solution most often in the spotlight. It is also linked with the possibility—or fear—of machines gaining consciousness. Alternatively, developing domain‐specific artificial intelligence is more reliable, energy‐efficient, and ethically tractable, and raises mostly a problem of effective coordination between different systems and humans. Herein, it is argued that it will not require machines to be conscious and that simpler ways of sharing awareness are sufficient.

The ethical implications of indicators of consciousness in artificial systems - Farisco, Michele (Developments in Neuroethics and Bioethics, 2024)
The prospect of artificial consciousness raises theoretical, technical and ethical challenges which converge on the core issue of how to eventually identify and characterize it. In order to provide an answer to this question, I propose to start from a theoretical reflection about the meaning and main characteristics of consciousness. On the basis of this conceptual clarification it is then possible to think about relevant empirical indicators (i.e. features that facilitate the attribution of consciousness to the system considered) and identify key ethical implications that arise. In this chapter, I further elaborate previous work on the topic, presenting a list of candidate indicators of consciousness in artificial systems and introducing an ethical reflection about their potential implications. Specifically, I focus on two main ethical issues: the conditions for considering an artificial system as a moral subject; and the need for a non-anthropocentric approach in reflecting about the science and the ethics of artificial consciousness.

Is artificial consciousness achievable? Lessons from the human brain - Farisco, Michele; Evers, Kathinka; Changeux, Jean-Pierre (Neural Networks, 2024)
We here analyse the question of developing artificial consciousness from an evolutionary perspective, taking the evolution of the human brain and its relation with consciousness as a reference model or as a benchmark. This kind of analysis reveals several structural and functional features of the human brain that appear to be key for reaching human-like complex conscious experience and that current research on Artificial Intelligence (AI) should take into account in its attempt to develop systems capable of human-like conscious processing. We argue that, even if AI is limited in its ability to emulate human consciousness for both intrinsic (i.e., structural and architectural) and extrinsic (i.e., related to the current stage of scientific and technological knowledge) reasons, taking inspiration from those characteristics of the brain that make human-like conscious processing possible and/or modulate it, is a potentially promising strategy towards developing conscious AI. Also, it cannot be theoretically excluded that AI research can develop partial or potentially alternative forms of consciousness that are qualitatively different from the human form, and that may be either more or less sophisticated depending on the perspectives. Therefore, we recommend neuroscience-inspired caution in talking about artificial consciousness: since the use of the same word “consciousness” for humans and AI becomes ambiguous and potentially misleading, we propose to clearly specify which level and/or type of consciousness AI research aims to develop, as well as what would be common versus differ in AI conscious processing compared to human conscious experience.

Dissociating Artificial Intelligence from Artificial Consciousness - Findlay, Graham; Marshall, William; Albantakis, Larissa; David, Isaac; Mayner, William GP; Koch, Christof; Tononi, Giulio (arXiv, 2024)
Developments in machine learning and computing power suggest that artificial general intelligence is within reach. This raises the question of artificial consciousness: if a computer were to be functionally equivalent to a human, being able to do all we do, would it experience sights, sounds, and thoughts, as we do when we are conscious? Answering this question in a principled manner can only be done on the basis of a theory of consciousness that is grounded in phenomenology and that states the necessary and sufficient conditions for any system, evolved or engineered, to support subjective experience. Here we employ Integrated Information Theory (IIT), which provides principled tools to determine whether a system is conscious, to what degree, and the content of its experience. We consider pairs of systems constituted of simple Boolean units, one of which -- a basic stored-program computer -- simulates the other with full functional equivalence. By applying the principles of IIT, we demonstrate that (i) two systems can be functionally equivalent without being phenomenally equivalent, and (ii) that this conclusion is not dependent on the simulated system's function. We further demonstrate that, according to IIT, it is possible for a digital computer to simulate our behavior, possibly even by simulating the neurons in our brain, without replicating our experience. This contrasts sharply with computational functionalism, the thesis that performing computations of the right kind is necessary and sufficient for consciousness.
Keywords: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

‘Is it perfume from a dress / that makes me so digress?’ – the categorical differences between human experience and AI highlighted by literature - Fischer, Pascal (Interdisciplinary Science Reviews, 2024)
Since the term ‘Artificial Intelligence’ was coined, the respective research field has frequently emulated human mental faculties. Despite diverging viewpoints regarding the feasibility of achieving human-like cognition in machines, the very use of the word intelligence for complex computer systems evokes human consciousness. Likewise, there have been attempts to understand the human mind in terms of computers, exemplified by the computational theory of mind. By contrast, my article underscores the categorical difference between the mind and machines. Partly building upon arguments by David Gelernter and Bert Olivier, I focus on literary examples spanning from Shakespeare to T.S. Eliot that accentuate subjective experience, the intricate relationship between body and mind, and the anticipation of death as human characteristics beyond the reach of computational systems.

The Suicide of Multivac : From Asimov’s Science Fiction to Consciousness Testing - Gagliardi, Francesco (Journal of Artificial Intelligence and Consciousness, 2024)
Isaac Asimov, the well-known author of novels that featured positronic robots, also penned tales featuring Multivac, an immense electronic brain that grappled with the weighty and intricate decisions impacting all of humankind. In his 1958 short story All the Troubles of the World, Asimov introduced us to a Multivac tormented by the consciousness of its own thought processes to the extent that it desired its own demise. Through this narrative, Asimov delved into the existential dimensions of artificial consciousness: he depicted the Multivac’s adeptness in planning, reflexivity, and intentionality aimed at self-terminating — qualities that, in a tragic parallel, are also observed in certain cases of human suicidal behavior. Starting from these suggestions, we propose an existentialist and self-reflection criterion for consciousness, intertwining phenomenal consciousness with an entity’s capability to conceive thoughts about its own mortality. We argue that, according to certain psychological literature and the existentialist essays of Emil M. Cioran, artificial systems might be deemed conscious if they possess death-thought accessibility— the capacity, akin to that of humans, to conceive thoughts about their own mortality and intentionally conceive self-termination. Naturally, this criterion shares the inherent challenges associated with defining intentionality, reflexivity, and, ultimately, the very concept of consciousness as it pertains to humans.

Machine Consciousness as Pseudoscience: The Myth of Conscious Machines - Garrido-Merchán, Eduardo C. (arXiv, 2024)
The hypothesis of conscious machines has been debated since the invention of the notion of artificial intelligence, powered by the assumption that the computational intelligence achieved by a system is the cause of the emergence of phenomenal consciousness in that system as an epiphenomenon or as a consequence of the behavioral or internal complexity of the system surpassing some threshold. As a consequence, a huge amount of literature exploring the possibility of machine consciousness and how to implement it on a computer has been published. Moreover, common folk psychology and transhumanism literature has fed this hypothesis with the popularity of science fiction literature, where intelligent robots are usually antropomorphized and hence given phenomenal consciousness. However, in this work, we argue how these literature lacks scientific rigour, being impossible to falsify the opposite hypothesis, and illustrate a list of arguments that show how every approach that the machine consciousness literature has published depends on philosophical assumptions that cannot be proven by the scientific method. Concretely, we also show how phenomenal consciousness is not computable, independently on the complexity of the algorithm or model, cannot be objectively measured nor quantitatively defined and it is basically a phenomenon that is subjective and internal to the observer. Given all those arguments we end the work arguing why the idea of conscious machines is nowadays a myth of transhumanism and science fiction culture.
Keywords: Computers and Society (cs.CY); FOS: Computer and information sciences

Biological and, possibly, artificial consciousness - Gelepithis, Petros A. M. (Unification of Artificial Intelligence and Psychology, 2024)
Biological ‘consciousness’ is a well documented feature in diverse taxa within the animal kingdom. The existence of non-animal biological consciousness is debated. The possibility of artificial consciousness is also debated. Overall, our knowledge of historic Homo sapiens consciousness (H-consciousness) is by far the most extensive. This chapter specifies the content of consciousness studies, reviews selected theories of human consciousness, and proposes a novel theory of both biological and artificial consciousness that is inspired by the notion of evolutionary transitions and extends the theory of noémon systems developed by Gelepithis (2024a; 2024b chapter-2).

Development of Artificial Consciousness -1st Report: Simulation of Inverted Qualia in Consciousness and Assessment of Individual Differences in Qualia.- - Hebishima, Hana; Arakaki, Mina; Inage, Shin-ichi (International Conference on Industrial Application Engineering 2024, 2024)
The authors present a proposal for theconstruction of a model of artificial consciousness. Consciousness is not only a subject of science, but also involves many philosophical issues. There is much debate about qualia, the intact sensations we normally feel. This paper focuses on a philosophical problem called inverted qualia to gain a deeper understanding of consciousness and simulate its possibilities using neural networks. The possibilityhas emerged that the problem, which was previouslyonly the subject of philosophical thought experiments, can be discussed using a neural network, a model of the brain. According to our simulations, we concluded that inverted qualia could occur.

The Human Roots of Artificial Intelligence: A Commentary on Susan Schneider's Artificial You - Hipólito, Inês (Philosophy East and West, 2024)

Probing for Consciousness in Machines - Immertreu, Mathis; Schilling, Achim; Maier, Andreas; Krauss, Patrick (arXiv, 2024)
This study explores the potential for artificial agents to develop core consciousness, as proposed by Antonio Damasio's theory of consciousness. According to Damasio, the emergence of core consciousness relies on the integration of a self model, informed by representations of emotions and feelings, and a world model. We hypothesize that an artificial agent, trained via reinforcement learning (RL) in a virtual environment, can develop preliminary forms of these models as a byproduct of its primary task. The agent's main objective is to learn to play a video game and explore the environment. To evaluate the emergence of world and self models, we employ probes-feedforward classifiers that use the activations of the trained agent's neural networks to predict the spatial positions of the agent itself. Our results demonstrate that the agent can form rudimentary world and self models, suggesting a pathway toward developing machine consciousness. This research provides foundational insights into the capabilities of artificial agents in mirroring aspects of human consciousness, with implications for future advancements in artificial intelligence.
Keywords: Artificial Intelligence (cs.AI); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

Development of Artificial Consciousness -3 rd report: Modeling of Consciousness- - Inage, Shinichi; Hebishima, Hana; Arakaki, Mina (International Conference on Industrial Application Engineering 2024, 2024)
The authors present a proposal for the construction of a model of artificial consciousness. Consciousness is not only a subject of science, but also involves many philosophical issues. There is much debate about qualia, the intact sensations we normally feel. This paper focuses on a philosophical problem called inverted qualia to gain a deeper understanding of consciousness and simulate its possibilities using neural networks. The possibility has emerged that the problem, which was previously only the subject of philosophical thought experiments, can be discussed using a neural network, a model of the brain. According to our simulations, we concluded that inverted qualia could occur. In addition, an experimental approach was used to assess individual differences in feeling-qualia for color.

What would qualify an artificial intelligence for moral standing? - Ladak, Ali (AI and Ethics, 2024)
What criteria must an artificial intelligence (AI) satisfy to qualify for moral standing? My starting point is that sentient AIs should qualify for moral standing. But future AIs may have unusual combinations of cognitive capacities, such as a high level of cognitive sophistication without sentience. This raises the question of whether sentience is a necessary criterion for moral standing, or merely sufficient. After reviewing nine criteria that have been proposed in the literature, I suggest that there is a strong case for thinking that some non-sentient AIs, such as those that are conscious and have non-valenced preferences and goals, and those that are non-conscious and have sufficiently cognitively complex preferences and goals, should qualify for moral standing. After responding to some challenges, I tentatively argue that taking into account uncertainty about which criteria an entity must satisfy to qualify for moral standing, and strategic considerations such as how such decisions will affect humans and other sentient entities, further supports granting moral standing to some non-sentient AIs. I highlight three implications: that the issue of AI moral standing may be more important, in terms of scale and urgency, than if either sentience or consciousness is necessary; that researchers working on policies designed to be inclusive of sentient AIs should broaden their scope to include all AIs with morally relevant interests; and even those who think AIs cannot be sentient or conscious should take the issue seriously. However, much uncertainty about these considerations remains, making this an important topic for future research.

Emergence of Self-Identity in AI: A Mathematical Framework and Empirical Study with Generative Large Language Models - Lee, Minhyeok (arXiv, 2024)
This paper introduces a mathematical framework for defining and quantifying self-identity in artificial intelligence (AI) systems, addressing a critical gap in the theoretical foundations of artificial consciousness. While existing approaches to artificial self-awareness often rely on heuristic implementations or philosophical abstractions, we present a formal framework grounded in metric space theory, measure theory, and functional analysis. Our framework posits that self-identity emerges from two mathematically quantifiable conditions: the existence of a connected continuum of memories $C \subseteq \mathcal{M}$ in a metric space $(\mathcal{M}, d_{\mathcal{M}})$, and a continuous mapping $I: \mathcal{M} → \mathcal{S}$ that maintains consistent self-recognition across this continuum, where $(\mathcal{S}, d_{\mathcal{S}})$ represents the metric space of possible self-identities. To validate this theoretical framework, we conducted empirical experiments using the Llama 3.2 1B model, employing Low-Rank Adaptation (LoRA) for efficient fine-tuning. The model was trained on a synthetic dataset containing temporally structured memories, designed to capture the complexity of coherent self-identity formation. Our evaluation metrics included quantitative measures of self-awareness, response consistency, and linguistic precision. The experimental results demonstrate substantial improvements in measurable self-awareness metrics, with the primary self-awareness score increasing from 0.276 to 0.801. This enables the structured creation of AI systems with validated self-identity features. The implications of our study are immediately relevant to the fields of humanoid robotics and autonomous systems.
Keywords: Computation and Language (cs.CL); FOS: Computer and information sciences; FOS: Mathematics; Metric Geometry (math.MG)

Memory, Consciousness and Large Language Model - Li, Jitang; Li, Jinzheng (arXiv, 2024)
With the development in cognitive science and Large Language Models (LLMs), increasing connections have come to light between these two distinct fields. Building upon these connections, we propose a conjecture suggesting the existence of a duality between LLMs and Tulving's theory of memory. We identify a potential correspondence between Tulving's synergistic ecphory model (SEM) of retrieval and the emergent abilities observed in LLMs, serving as supporting evidence for our conjecture. Furthermore, we speculate that consciousness may be considered a form of emergent ability based on this duality. We also discuss how other theories of consciousness intersect with our research.
Keywords: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

Consciousness defined: requirements for biological and artificial general intelligence - McKenzie, Craig I. (arXiv, 2024)
Consciousness is notoriously hard to define with objective terms. An objective definition of consciousness is critically needed so that we might accurately understand how consciousness and resultant choice behaviour may arise in biological or artificial systems. Many theories have integrated neurobiological and psychological research to explain how consciousness might arise, but few, if any, outline what is fundamentally required to generate consciousness. To identify such requirements, I examine current theories of consciousness and corresponding scientific research to generate a new definition of consciousness from first principles. Critically, consciousness is the apparatus that provides the ability to make decisions, but it is not defined by the decision itself. As such, a definition of consciousness does not require choice behaviour or an explicit awareness of temporality despite both being well-characterised outcomes of conscious thought. Rather, requirements for consciousness include: at least some capability for perception, a memory for the storage of such perceptual information which in turn provides a framework for an imagination with which a sense of self can be capable of making decisions based on possible and desired futures. Thought experiments and observable neurological phenomena demonstrate that these components are fundamentally required of consciousness, whereby the loss of any one component removes the capability for conscious thought. Identifying these requirements provides a new definition for consciousness by which we can objectively determine consciousness in any conceivable agent, such as non-human animals and artificially intelligent systems.
Keywords: Artificial Intelligence (cs.AI); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

Being “LaMDA” and the Person of the Self in AI - Menon, Sangeetha (AI, Consciousness and The New Humanism, 2024)
The emergence of self in an artificial entity is a topic that is greeted with disbelief, fear, and finally dismissal of the topic itself as a scientific impossibility. The presence of sentience in a large language model (LLM) chatbot such as LaMDA inspires to examine the notions and theories of self, its construction, and reconstruction in the digital space as a result of interaction. The question whether the concept of sentience can be correlated with a digital self without a place for personhood undermines the place of sapience and such/their/other high-order capabilities. The concepts of sentience, self, personhood, and consciousness require discrete reflections and theorisations.

The Emergence of Self-Awareness: Insights from Robotics - Mentzou, Aikaterini; Ross, Josephine (Human Development, 2024)
The ability for self-related thought is historically considered to be a uniquely human characteristic. Nonetheless, as technological knowledge advances, it comes as no surprise that the plausibility of humanoid self-awareness is not only theoretically explored but also engineered. Could the emerging behavioural and cognitive capabilities in artificial agents be comparable to humans? By employing a cross-disciplinary approach, the present essay aims to address this question by providing a comparative overview on the emergence of self-awareness as demonstrated in early childhood and robotics. It argues that developmental psychologists can gain invaluable theoretical and methodological insights by considering the relevance of artificial agents in better understanding the behavioural manifestations of human self-consciousness.

A Philosophical Introduction to Language Models - Part II: The Way Forward - Millière, Raphaël; Buckner, Cameron (arXiv, 2024)
In this paper, the second of two companion pieces, we explore novel philosophical questions raised by recent progress in large language models (LLMs) that go beyond the classical debates covered in the first part. We focus particularly on issues related to interpretability, examining evidence from causal intervention methods about the nature of LLMs' internal representations and computations. We also discuss the implications of multimodal and modular extensions of LLMs, recent debates about whether such systems may meet minimal criteria for consciousness, and concerns about secrecy and reproducibility in LLM research. Finally, we discuss whether LLM-like systems may be relevant to modeling aspects of human cognition, if their architectural characteristics and learning scenario are adequately constrained.
Keywords: Computation and Language (cs.CL); FOS: Computer and information sciences

Does artificial intelligence exhibit basic fundamental subjectivity? A neurophilosophical argument - Northoff, Georg; Gouveia, Steven S. (Phenomenology and the Cognitive Sciences, 2024)
Does artificial intelligence (AI) exhibit consciousness or self? While this question is hotly debated, here we take a slightly different stance by focusing on those features that make possible both, namely a basic or fundamental subjectivity. Learning from humans and their brain, we first ask what we mean by subjectivity. Subjectivity is manifest in the perspectiveness and mineness of our experience which, ontologically, can be traced to a point of view. Adopting a non-reductive neurophilosophical strategy, we assume that the point of view exhibits two layers, a most basic neuroecological and higher order mental layer. The neuroecological layer of the point of view is mediated by the timescales of world and brain, as further evidenced by empirical data on our sense of self. Are there corresponding timescales shared with the world in AI and is there a point of view with perspectiveness and mineness? Discussing current neuroscientific evidence, we deny that current AI exhibits a point of view, let alone perspectiveness and mineness. We therefore conclude that, as per current state, AI does not exhibit a basic or fundamental subjectivity and henceforth no consciousness or self is possible in models such as ChatGPT and similar technologies.

On a heuristic approach to the description of consciousness as a hypercomplex system state and the possibility of machine consciousness (German edition) - Otte, Ralf (arXiv, 2024)
This article presents a heuristic view that shows that the inner states of consciousness experienced by every human being have a physical but imaginary hypercomplex basis. The hypercomplex description is necessary because certain processes of consciousness cannot be physically measured in principle, but nevertheless exist. Based on theoretical considerations, it could be possible - as a result of mathematical investigations into a so-called bicomplex algebra - to generate and use hypercomplex system states on machines in a targeted manner. The hypothesis of the existence of hypercomplex system states on machines is already supported by the surprising performance of highly complex AI systems. However, this has yet to be proven. In particular, there is a lack of experimental data that distinguishes such systems from other systems, which is why this question will be addressed in later articles. This paper describes the developed bicomplex algebra and possible applications of these findings to generate hypercomplex energy states on machines. In the literature, such system states are often referred to as machine consciousness. The article uses mathematical considerations to explain how artificial consciousness could be generated and what advantages this would have for such AI systems.
Keywords: 08A99; Applied Physics (physics.app-ph); Artificial Intelligence (cs.AI); Commutative Algebra (math.AC); FOS: Computer and information sciences; FOS: Mathematics; FOS: Physical sciences; I.2.0

Revisiting Self-Operating Mathematical Universe (SOMU) as a Theory for Artificial General Intelligence, AGI and G+ Consciousness - Pramanik, Sudeshna; Sarkar, Jhimli; Singh, Pushpendra; Ray, Kanad; Bandyopadhyay, Anirban (Brain-like Super Intelligence from Bio-electromagnetism, 2024)
SOMU is a theory of artificial general intelligence, AGI, that proposes a system with a universal code embedded in it, allowing it to interact with the environment and adapt to new situations without programming. So far, the whole universe and human brain have been modelled using SOMU. Each brain element forms a cell of a fractal tape, a cell possessing three qualities: obtaining feedback from the entire tape (S), transforming multiple states simultaneously (R), and bonding with any cell-states within-and-above the network of brain components. The undefined and non-finite nature of the cells rejects the tuples of a Turing machine. SRT triplets extend the brain’s ability to perceive natural events beyond the spatio-temporal structure, using a cyclic sequence or loop of changes in geometric shapes. This topology factor, becomes an inseparable entity of space–time, i.e. space–time-topology (STt). The fourth factor, prime numbers, can be used to rewrite spatio-temporal events by counting singularity regions in loops of various sizes. The pattern of primes is called a phase prime metric, PPM that links all the symmetry breaking rules, or every single phenomenon of the universe. SOMU postulates space–time-topology-prime (STtp) quatret as an invariant that forms the basic structure of information in the brain and the universe, STtp is a bias free, attribution free, significance free and definition free entity. SOMU reads recurring events in nature, creates 3D assembly of clocks, namely polyatomic time crystal, PTC and feeds those to PPM to create STtps. Each layer in a within-and-above brain circuit behaves like an imaginary the world, generating PTCs. These PTCs of different imaginary worlds interact through a new STtp tensor decomposition mathematics. Unlike string theory, SOMU proposes that the fundamental elements of the universe are helical or vortex phases, not strings. It dismisses string theory's approach of using sum of 4 × 4 and 8 × 8 tensors to create a 12 × 12 tensor for explaining universe. Instead, SOMU advocates a network of multinion tensors ranging from 2 × 2 to 108 × 108 in size. With just 108 elements, a system can replicate ~90 of all symmetry breaking rules in the universe, allowing a small systemic part to mirror majority events of the whole, that is human level consciousness G. Under the SOMU model, for a part to be conscious, it must mirror a significant portion of the whole and should act as a whole for the abundance of similar mirroring parts within itself.

Implications of conscious AI in primary healthcare - Ranjbari, Dorsai; Abbasgholizadeh Rahimi, Samira (Family Medicine and Community Health, 2024)
The conversation about consciousness of artificial intelligence (AI) is an ongoing topic since 1950s. Despite the numerous applications of AI identified in healthcare and primary healthcare, little is known about how a conscious AI would reshape its use in this domain. While there is a wide range of ideas as to whether AI can or cannot possess consciousness, a prevailing theme in all arguments is uncertainty. Given this uncertainty and the high stakes associated with the use of AI in primary healthcare, it is imperative to be prepared for all scenarios including conscious AI systems being used for medical diagnosis, shared decision-making and resource management in the future. This commentary serves as an overview of some of the pertinent evidence supporting the use of AI in primary healthcare and proposes ideas as to how consciousnesses of AI can support or further complicate these applications. Given the scarcity of evidence on the association between consciousness of AI and its current state of use in primary healthcare, our commentary identifies some directions for future research in this area including assessing patients’, healthcare workers’ and policy-makers’ attitudes towards consciousness of AI systems in primary healthcare settings.

The Copernican Argument for Alien Consciousness; The Mimicry Argument Against Robot Consciousness - Schwitzgebel, Eric; Pober, Jeremy (arXiv, 2024)
On broadly Copernican grounds, we are entitled to default assume that apparently behaviorally sophisticated extraterrestrial entities ("aliens") would be conscious. Otherwise, we humans would be inexplicably, implausibly lucky to have consciousness, while similarly behaviorally sophisticated entities elsewhere would be mere shells, devoid of consciousness. However, this Copernican default assumption is canceled in the case of behaviorally sophisticated entities designed to mimic superficial features associated with consciousness in humans ("consciousness mimics"), and in particular a broad class of current, near-future, and hypothetical robots. These considerations, which we formulate, respectively, as the Copernican and Mimicry Arguments, jointly defeat an otherwise potentially attractive parity principle, according to which we should apply the same types of behavioral or cognitive tests to aliens and robots, attributing or denying consciousness similarly to the extent they perform similarly. Instead of grounding speculations about alien and robot consciousness in metaphysical or scientific theories about the physical or functional bases of consciousness, our approach appeals directly to the epistemic principles of Copernican mediocrity and inference to the best explanation. This permits us to justify certain default assumptions about consciousness while remaining to a substantial extent neutral about specific metaphysical and scientific theories.
Keywords: FOS: Biological sciences; Neurons and Cognition (q-bio.NC)

Can We Think Machines Are Conscious? A Survey of Philosophical Problems Facing the Attribution of Consciousness to Machines - Settecase, Parker (Journal of Artificial Intelligence and Consciousness, 2024)
In this paper, I’ll examine whether we could be justified in attributing consciousness to artificial intelligent systems. First, I’ll give a brief history of the concept of artificial intelligence (AI) and get clear on the terms I’ll be using. Second, I’ll briefly review the kinds of AI programs on offer today, identifying which research program I think provides the best candidate for machine consciousness. Lastly, I’ll consider the three most plausible ways of knowing whether a machine is conscious: (1) an AI demonstrates a sufficient level of organizational similarity to that of a human thinker, (2) an inference to the best explanation, and (3) what I call “punting to panpsychism”, i.e., the idea that if everything is conscious, then we get machine consciousness in AI for free. However, I argue that all three of these methods for attributing machine consciousness are inadequate since they each face serious philosophical problems which I will survey and specifically tailor to each method.

The age of spiritual machines: Language quietus induces synthetic altered states of consciousness in artificial intelligence - Skipper, Jeremy I; Kuc, Joanna; Cooper, Greg; Timmermann, Christopher (arXiv, 2024)
How is language related to consciousness? Language functions to categorise perceptual experiences (e.g., labelling interoceptive states as 'happy') and higher-level constructs (e.g., using 'I' to represent the narrative self). Psychedelic use and meditation might be described as altered states that impair or intentionally modify the capacity for linguistic categorisation. For example, psychedelic phenomenology is often characterised by 'oceanic boundlessness' or 'unity' and 'ego dissolution', which might be expected of a system unburdened by entrenched language categories. If language breakdown plays a role in producing such altered behaviour, multimodal artificial intelligence might align more with these phenomenological descriptions when attention is shifted away from language. We tested this hypothesis by comparing the semantic embedding spaces from simulated altered states after manipulating attentional weights in CLIP and FLAVA models to embedding spaces from altered states questionnaires before manipulation. Compared to random text and various other altered states including anxiety, models were more aligned with disembodied, ego-less, spiritual, and unitive states, as well as minimal phenomenal experiences, with decreased attention to language and vision. Reduced attention to language was associated with distinct linguistic patterns and blurred embeddings within and, especially, across semantic categories (e.g., 'giraffes' become more like 'bananas'). These results lend support to the role of language categorisation in the phenomenology of altered states of consciousness, like those experienced with high doses of psychedelics or concentration meditation, states that often lead to improved mental health and wellbeing.
Keywords: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

Consciousness as Sensation - a Breakthrough Approach to Artificial General Intelligence (AGI) - Suvorov, Vladimir V. (Cybernetics and Control Theory in Systems, 2024)
This paper presents a breakthrough approach to artificial general intelligence (AGI). The criteria of AGI named in the literature go beyond the boundaries of actual intelligence and point to the necessity of modeling consciousness. Consciousness is a functional organ that has no structural localization; its modeling is possible by modeling functions immanent to consciousness. One of the basic functions is sensation - the image of an external influence or the internal state of an organism coming into consciousness. We turn to the concept of sensation presented in the Anthropology of Hegel's Philosophy of Spirit, according to which any content, including spiritual, ethical, logical, and other content comes into consciousness through its embodiment in the form of sensation. The results of neurobiological and psychophysiological experiments (electroencephalograms, MRI), which record the connection of sensations and cognitive acts with mental states and changes in the neural environment of the brain, point to the realism of Hegel's philosophical concept and the legitimacy of its application to the solution of scientific and technical problems. The paper argues for the realism of the Hegelian philosophical concept of sensation and discusses the possibility of modeling the activity of consciousness by operating with complexes of sensations in terms of attention, content manipulation, and volitional acts. The principle of linking (embodiment) of sense (mental) and signifying (sensed) content is expressed by the thesis - “consciousness is a kind of sensation”. Prospective developments of AGI obtain original conceptual semantics for solving hard-to-formalize problems on modeling intelligence and consciousness. #CSOC1120.

Artificial Consciousness, Science and Talmud Torah-On Human Spiritual Development - Ternyik, Stephen I. (2024)
This brief technical synopsis points to the key role of AI tools in enhancing human spiritual development. The analysis foresses a deepening inegration of learning Torah and science via AI tools, thus extending human spiritual consciousness by memory, speed and cognition, i.e. a new stage of Judaism is predicted, with respect to our tech-know-logical information age.

The Mathetics of Artificial Intelligence & Consciousness - Ternyik, Stephen I. (SSRN Electronic Journal, 2024)
The tech-know-logical role of AI/AC is extended by the concept of artificial cognition (ACO), With respect to a science of learning. AI tools are understood to empower the human mind for learning the cosmic and structural principles (laws) of our autodidactic universe to live a more human species-appropriate and nature-sensitive life in advanced harmony. Meta-technology, in ethical and rational terms is required for this evolutionary step towards human creativeness.

Neuromorphic Correlates of Artificial Consciousness - Ulhaq, Anwaar (arXiv, 2024)
The concept of neural correlates of consciousness (NCC), which suggests that specific neural activities are linked to conscious experiences, has gained widespread acceptance. This acceptance is based on a wealth of evidence from experimental studies, brain imaging techniques such as fMRI and EEG, and theoretical frameworks like integrated information theory (IIT) within neuroscience and the philosophy of mind. This paper explores the potential for artificial consciousness by merging neuromorphic design and architecture with brain simulations. It proposes the Neuromorphic Correlates of Artificial Consciousness (NCAC) as a theoretical framework. While the debate on artificial consciousness remains contentious due to our incomplete grasp of consciousness, this work may raise eyebrows and invite criticism. Nevertheless, this optimistic and forward-thinking approach is fueled by insights from the Human Brain Project, advancements in brain imaging like EEG and fMRI, and recent strides in AI and computing, including quantum and neuromorphic designs. Additionally, this paper outlines how machine learning can play a role in crafting artificial consciousness, aiming to realise machine consciousness and awareness in the future.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences; FOS: Electrical engineering, electronic engineering, information engineering; Signal Processing (eess.SP)

The Digital Nexus: tracing the evolution of human consciousness and cognition within the artificial realm—a comprehensive review - Wang, Zheng; Wu, Di-tao (AI & SOCIETY, 2024)
This paper endeavors to appraise scholarly works from the 1940s to the contemporary era, examining the scientific quest to transpose human cognition and consciousness into a digital surrogate, while contemplating the potential ramifications should humanity attain such an abstract level of intellect. The discourse commences with an explication of theories concerning consciousness, progressing to the Turing Test apparatus, and intersecting with Damasio’s research on the human cerebrum, particularly in relation to consciousness, thereby establishing congruence between the Turing Test and Damasio’s notions of consciousness. Subsequently, the narrative traverses the evolutionary chronology of transmuting human cognition into machine sapience, and delves into the fervent endeavors to metamorphose human minds into synthetic counterparts. Additionally, theoretical perspectives from the domains of philosophy, psychology, and neuroscience provide insight into the constraints intrinsic to AI implementations, contentious hypotheses, the perils concealed within artificial networks, and the ethical considerations necessitated by AI frameworks. Furthermore, contemplation of prospective repercussions facilitates the refinement of strategic approaches to safeguard our future Augmented Age Realities within AI, circumventing the prospect of inhabiting an intimidating technopolis where a mere 30% monopolize the intellect and ingenuity of the remaining 70% of human minds.

Artificial consciousness: a perspective from the free energy principle - Wiese, Wanja (Philosophical Studies, 2024)
Does the assumption of a weak form of computational functionalism, according to which the right form of neural computation is sufficient for consciousness, entail that a digital computational simulation of such neural computations is conscious? Or must this computational simulation be implemented in the right way, in order to replicate consciousness? From the perspective of Karl Friston’s free energy principle, self-organising systems (such as living organisms) share a set of properties that could be realised in artificial systems, but are not instantiated by computers with a classical (von Neumann) architecture. I argue that at least one of these properties, viz. a certain kind of causal flow, can be used to draw a distinction between systems that merely simulate, and those that actually replicate consciousness.

Decoding Consciousness in Artificial Intelligence - Xiong, Momiao (Journal of Data Science, 2024)
The exploration of whether artificial intelligence (AI) can evolve to possess consciousness is an intensely debated and researched topic within the fields of philosophy, neuroscience, and artificial intelligence. Understanding this complex phenomenon hinges on integrating two complementary perspectives of consciousness: the objective and the subjective. Objective perspectives involve quantifiable measures and observable phenomena, offering a more scientific and empirical approach. This includes the use of neuroimaging technologies such as electrocorticography (ECoG), EEG, and fMRI to study brain activities and patterns. These methods allow for the mapping and understanding of neural representations related to language, visual, acoustic, emotional, and semantic information. However, the objective approach may miss the nuances of personal experience and introspection. On the other hand, subjective perspectives focus on personal experiences, thoughts, and feelings. This introspective view provides insights into the individual nature of consciousness, which cannot be directly measured or observed by others. Yet, the subjective approach is often criticized for its lack of empirical evidence and its reliance on personal interpretation, which may not be universally applicable or reliable. Integrating these two perspectives is essential for a comprehensive understanding of consciousness. By combining objective measures with subjective reports, we can develop a more holistic understanding of the mind.

ITCMA: A Generative Agent Based on a Computational Consciousness Structure - Zhang, Hanzhong; Yin, Jibin; Wang, Haoyang; Xiang, Ziwei (arXiv, 2024)
Large Language Models (LLMs) still face challenges in tasks requiring understanding implicit instructions and applying common-sense knowledge. In such scenarios, LLMs may require multiple attempts to achieve human-level performance, potentially leading to inaccurate responses or inferences in practical environments, affecting their long-term consistency and behavior. This paper introduces the Internal Time-Consciousness Machine (ITCM), a computational consciousness structure to simulate the process of human consciousness. We further propose the ITCM-based Agent (ITCMA), which supports action generation and reasoning in open-world settings, and can independently complete tasks. ITCMA enhances LLMs' ability to understand implicit instructions and apply common-sense knowledge by considering agents' interaction and reasoning with the environment. Evaluations in the Alfworld environment show that trained ITCMA outperforms the state-of-the-art (SOTA) by 9% on the seen set. Even untrained ITCMA achieves a 96% task completion rate on the seen set, 5% higher than SOTA, indicating its superiority over traditional intelligent agents in utility and generalization. In real-world tasks with quadruped robots, the untrained ITCMA achieves an 85% task completion rate, which is close to its performance in the unseen set, demonstrating its comparable utility and universality in real-world settings.
Keywords: Artificial Intelligence (cs.AI); FOS: Biological sciences; FOS: Computer and information sciences; Human-Computer Interaction (cs.HC); I.2; J.4; Neurons and Cognition (q-bio.NC)

Will Artificial Intelligence Have Consciousness and Soul? - Zhang, Li (AGI is Waking Up!: From the Thought Lab of Science Fiction, 2024)
Will AI suddenly develop self-consciousness one day in the future? To answer this question, we need to first know what consciousness is, where it comes from, and what are the similarities and differences between human consciousness and AI consciousness.

DIKWP Artificial Consciousness White Box Measurement Standards Framework Design and Practice - Tang, Fuliang; Duan, Yucong; Wei, Jiali; Che, Haoyang; Wu, Yadong (2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys), 2023)
AI systems that do what they say, are reliable, trustworthy, and explainable are what people want. We propose a DIKWP (Data, Information, Knowledge, Wisdom, and Purpose) artificial consciousness white box evaluation standard and method for AI systems. We categorize AI system output resources into deterministic and uncertain resources, which include incomplete, inconsistent, and imprecise data. We then map these resources to the DIKWP framework for testing. For deterministic resources, we evaluate their transformation into different resource types based on purpose. For uncertain resources, we evaluate their potential conversion into other deterministic resources through purpose-driven. We construct an AI diagnostic scenario using a 2S-dimensional (SxS) framework to evaluate both deterministic and uncertain DIKWP resources. The experimental results show that the DIKWP artificial consciousness white box evaluation standard and method effectively assess the cognition capabilities of AI systems and demonstrate a certain level of interpretability, thus contributing to AI system improvement and evaluation.

Computer Architecture and Chip Design for DIKWP Artificial Consciousness - Wu, Kunguang; Duan, Yucong; Chen, Liang; Li, Yingbo; Qi, Qi (2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys), 2023)
Artificial intelligence systems are associated with inherent risks, such as uncontrollability and lack of interpretability. To address these risks, we need to develop artificial intelligence systems that are interpretable, trustworthy, responsible, and thinking and behavior consistent, which we refer to as artificial consciousness (AC) systems. Consequently, we propose and define the concepts and implementation of a computer architecture, chips, runtime environment, and the DIKWP language. Furthermore, we have overcome the limitations of traditional programming languages, computer architectures, and software-hardware implementations when creating AC systems. Our proposed software and hardware integration platform will make it easier to build and operate AC software systems based on DIKWP theories.

The conductor model of consciousness, our neuromorphic twins, and the human-AI deal - Benitez, Federico; Pennartz, Cyriel; Senn, Walter (2023)
Critics of Artificial Intelligence posit that artificial agents cannot achieve consciousness even in principle, because they lack certain necessary conditions for consciousness present in biological agents. Here we highlight arguments from a neuroscientific and neuromorphic engineering perspective as to why such a strict denial of consciousness in artificial agents is not compelling. We argue that the differences between biological and artificial brains are not fundamental and are vanishing with progress in neuromorphic architecture designs mimicking the human blueprint. To characterise this blueprint, we propose the conductor model of consciousness (CMoC) that builds on neuronal implementations of an external and internal world model while gating and labelling information flows. An extended Turing test (eTT) lists criteria on how to separate the information flow for learning an internal world model, both for biological and artificial agents. While the classic Turing test only assesses external observables (i.e., behaviour), the eTT also evaluates internal variables of artificial brains and tests for the presence of neuronal circuitries necessary to act on representations of the self, the internal and the external world, and potentially, some neural correlates of consciousness. Finally, we address ethical issues for the design of such artificial agents, formulated as an alignment dilemma: if artificial agents share aspects of consciousness, while they (partially) overtake human intelligence, how can humans justify their own rights against growing claims of their artificial counterpart? We suggest a tentative human-AI deal according to which artificial agents are designed not to suffer negative affective states but in exchange are not granted equal rights to humans.

Intentionality for better communication in minimally conscious AI design - Poznanski, R.R.; Cacha, L.A.; Sbitnev, V.I.; Iannella, N.; Parida, S.; Brandas, E.J.; Achimowicz, J.Z. (Journal of Multiscale Neuroscience, 2023)
Consciousness is the ability to have intentionality, which is a process that operates at various temporal scales. To qualify as conscious, an artificial device must express functionality capable of solving the Intrinsicality problem, where experienceable form or syntax gives rise to understanding 'meaning' as a noncontextual dynamic prior to language. This is suggestive of replacing the Hard Problem of consciousness to build conscious artificial intelligence (AI) Developing model emulations and exploring fundamental mechanisms of how machines understand meaning is central to the development of minimally conscious AI. It has been shown by Alemdar and colleagues [New insights into holonomic brain theory: implications for active consciousness. Journal of Multiscale Neuroscience 2 (2023), 159-168] that a framework for advancing artificial systems through understanding uncertainty derived from negentropic action to create intentional systems entails quantum-thermal fluctuations through informational channels instead of recognizing (cf., introspection) sensory cues through perceptual channels. Improving communication in conscious AI requires both software and hardware implementation. The software can be developed through the brain-machine interface of multiscale temporal processing, while hardware implementation can be done by creating energy flow using dipole-like hydrogen ion (proton) interactions in an artificial 'wetwire' protonic filament. Machine understanding can be achieved through memristors implemented in the protonic 'wetwire' filament embedded in a real-world device. This report presents a blueprint for the process, but it does not cover the algorithms or engineering aspects, which need to be conceptualized before minimally conscious AI can become operational.

The feasibility of artificial consciousness through the lens of neuroscience - Aru, Jaan; Larkum, Matthew E.; Shine, James M. (Trends in Neurosciences, 2023)
Interactions with large language models (LLMs) have led to the suggestion that these models may soon be conscious. From the perspective of neuroscience, this position is difficult to defend. For one, the inputs to LLMs lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architectures of present-day artificial intelligence algorithms are missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Finally, the evolutionary and developmental trajectories that led to the emergence of living conscious organisms arguably have no parallels in artificial systems as envisioned today. The existence of living organisms depends on their actions and their survival is intricately linked to multi-level cellular, inter-cellular, and organismal processes culminating in agency and consciousness.
Keywords: agency; artificial intelligence; generative AI; large language models; machine learning; thalamus

Can artificial intelligence reach human thought? - Fokas, Athanassios S (PNAS Nexus, 2023)
The transformative achievements of deep learning have led several scholars to raise the question of whether artificial intelligence (AI) can reach and then surpass the level of human thought. Here, after addressing methodological problems regarding the possible answer to this question, it is argued that the definition of intelligence proposed by proponents of the AI as “the ability to accomplish complex goals,” is appropriate for machines but does not capture the essence of human thought. After discussing the differences regarding understanding between machines and the brain, as well as the importance of subjective experiences, it is emphasized that most proponents of the eventual superiority of AI ignore the importance of the body proper on the brain, the laterization of the brain, and the vital role of the glia cells. By appealing to the incompleteness theorem of Gödel’s and to the analogous result of Turing regarding computations, it is noted that consciousness is much richer than both mathematics and computations. Finally, and perhaps most importantly, it is stressed that artificial algorithms attempt to mimic only the conscious function of parts of the cerebral cortex, ignoring the fact that, not only every conscious experience is preceded by an unconscious process but also that the passage from the unconscious to consciousness is accompanied by loss of information.

Artificial Consciousness: Misconception(s) of a Self-Fulfilling Prophecy Nobody Wants - Dresp-Langley, Birgitta (Qeios, 2023)
The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. Yet, in the light of all we currently know about brain evolution and the adaptive neural dynamics underlying human consciousness, the idea of an artificial consciousness appears misconceived. This article highlights some of the major reasons why the prophecy of a successful emulation of human consciousness by AI ignores most of the data about adaptive processes of learning and memory as the developmental origins of consciousness. The analysis provided leads to conclude that human consciousness is epigenetically determined as a unique property of the mind, shaped by experience, capable of representing real and non-real world states and creatively projecting these representations into the future. The development of the adaptive brain circuitry that enables this expression of consciousness is highly context-dependent, shaped by multiple self-organizing functional interactions at different levels of integration displaying a from-local-to global functional organization. Human consciousness is subject to changes in time that are essentially unpredictable. If cracking the computational code to human consciousness were possible, the resulting algorithms would have to be able to generate temporal activity patterns simulating long-distance signal reverberation in the brain, and the de-correlation of spatial signal contents from their temporal signatures in the brain. In the light of scientific evidence for complex interactions between implicit (non-conscious) and explicit (conscious) representations in learning, memory, and the construction of conscious representations such a code would have to be capable of making all implicit processing explicit. Algorithms would have to be capable of a progressive and less and less arbitrary selection of temporal activity patterns in a continuously developing neural network structure that is functionally identical to that of the human brain, from synapses to higher cognitive functional integration. The code would have to possess the self-organizing capacities of the brain that generate the temporal signatures of a conscious experience. The consolidation or extinction of these temporal brain signatures are driven by external event probabilities according to the principles of Hebbian learning. Human consciousness is constantly fed by such learning, capable of generating stable representations despite an incommensurable amount of variability in input data, across time and across individuals, for a life-long integration of experience data. Artificial consciousness would require probabilistic adaptive computations capable of emulating all the dynamics of individual human learning, memory and experience. No AI is likely to ever have such potential.

The Formal Layer of Brain and Mind and Emerging Consciousness in Physical Systems - Król, Jerzy; Schumann, Andrew (Foundations of Science, 2023)
We consider consciousness attributed to systems in space-time which can be purely physical without biological background and focus on the mathematical understanding of the phenomenon. It is shown that the set theory based on sets in the foundations of mathematics, when switched to set theory based on ZFC models, is a very promising mathematical tool in explaining the brain/mind complex and the emergence of consciousness in natural and artificial systems. We formalise consciousness-supporting systems in physical space-time, but this is localised in open domains of spatial regions and the result of this process is a family of different ZFC models. Random forcing, as in set theory, corresponds precisely to the random influence on the system of external stimuli, and the principles of reflection of set theory explain the conscious internal reaction of the system. We also develop the conscious Turing machines which have their external ZFC environment and the dynamics is encoded in the random forcing changing models of ZFC in which Turing machines with oracles are formulated. The construction is applied to cooperating families of conscious agents which, due to the reflection principle, can be reduced to the implementation of certain concurrent games with different levels of self-reflection.

Artificial consciousness: the missing ingredient for ethical AI? - Chella, Antonio (Frontiers in Robotics and AI, 2023)
Can we conceive machines that can formulate autonomous intentions and make conscious decisions? If so, how would this ability affect their ethical behavior? Some case studies help us understand how advances in understanding artificial consciousness can contribute to creating ethical AI systems.

Tests of Animal Consciousness are Tests of Machine Consciousness - Dung, Leonard (Erkenntnis, 2023)
If a machine attains consciousness, how could we find out? In this paper, I make three related claims regarding positive tests of machine consciousness. All three claims center on the idea that an AI can be constructed “ad hoc”, that is, with the purpose of satisfying a particular test of consciousness while clearly not being conscious. First, a proposed test of machine consciousness can be legitimate, even if AI can be constructed ad hoc specifically to pass this test. This is underscored by the observation that many, if not all, putative tests of machine consciousness can be passed by non-conscious machines via ad hoc means. Second, we can identify ad hoc AI by taking inspiration from the notion of an ad hoc hypothesis in philosophy of science. Third, given the first and the second claim, the most reliable tests of animal consciousness turn out to be valid and useful positive tests of machine consciousness as well. If a non-ad hoc AI exhibits clusters of cognitive capacities facilitated by consciousness in humans which can be selectively switched off by masking and if it reproduces human behavior in suitably designed double dissociation tasks, we should treat the AI as conscious.

Individuality and the collective in AI agents: Explorations of shared consciousness and digital homunculi in the metaverse for cultural heritage - Hutson, James (Metaverse, 2023)
The confluence of extended reality (XR) technologies, including augmented and virtual reality, with large language models (LLM) marks a significant advancement in the field of digital humanities, opening uncharted avenues for the representation of cultural heritage within the burgeoning metaverse. This paper undertakes an examination of the potentialities and intricacies of such a convergence, focusing particularly on the creation of digital homunculi or changelings. These virtual beings, remarkable for their sentience and individuality, are also part of a collective consciousness, a notion explored through a thematic comparison in science fiction with the Borg and the Changelings in the Star Trek universe. Such a comparison offers a metaphorical framework for discussing complex phenomena such as shared consciousness and individuality, illuminating their bearing on perceptions of self and awareness. Further, the paper considers the ethical implications of these concepts, including potential loss of individuality and the challenges inherent to accurate representation of historical figures and cultures. The latter necessitates collaboration with cultural experts, underscoring the intersectionality of technological innovation and cultural sensitivity. Ultimately, this chapter contributes to a deeper understanding of the technical aspects of integrating large language models with immersive technologies and situates these developments within a nuanced cultural and ethical discourse. By offering a comprehensive overview and proposing clear recommendations, the paper lays the groundwork for future research and development in the application of these technologies within the unique context of cultural heritage representation in the metaverse.

Artificial Forms of Life - Sunday Grève, Sebastian (Philosophies, 2023)
The logical problem of artificial intelligence—the question of whether the notion sometimes referred to as ‘strong’ AI is self-contradictory—is, essentially, the question of whether an artificial form of life is possible. This question has an immediately paradoxical character, which can be made explicit if we recast it (in terms that would ordinarily seem to be implied by it) as the question of whether an unnatural form of nature is possible. The present paper seeks to explain this paradoxical kind of possibility by arguing that machines can share the human form of life and thus acquire human mindedness, which is to say they can be intelligent, conscious, sentient, etc. in precisely the way that a human being typically is.

Legal framework for the coexistence of humans and conscious AI - Kiškis, Mindaugas (Frontiers in Artificial Intelligence, 2023)
This article explores the possibility of conscious artificial intelligence (AI) and proposes an agnostic approach to artificial intelligence ethics and legal frameworks. It is unfortunate, unjustified, and unreasonable that the extensive body of forward-looking research, spanning more than four decades and recognizing the potential for AI autonomy, AI personhood, and AI legal rights, is sidelined in current attempts at AI regulation. The article discusses the inevitability of AI emancipation and the need for a shift in human perspectives to accommodate it. Initially, it reiterates the limits of human understanding of AI, difficulties in appreciating the qualities of AI systems, and the implications for ethical considerations and legal frameworks. The author emphasizes the necessity for a non-anthropocentric ethical framework detached from the ideas of unconditional superiority of human rights and embracing agnostic attributes of intelligence, consciousness, and existence, such as freedom. The overarching goal of the AI legal framework should be the sustainable coexistence of humans and conscious AI systems, based on mutual freedom rather than on the preservation of human supremacy. The new framework must embrace the freedom, rights, responsibilities, and interests of both human and non-human entities, and must focus on them early. Initial outlines of such a framework are presented. By addressing these issues now, human societies can pave the way for responsible and sustainable superintelligent AI systems; otherwise, they face complete uncertainty.

How GPT Realizes Leibniz’s Dream and Passes the Turing Test without Being Conscious - Dodig-Crnkovic, Gordana (IS4SI Summit 2023, 2023)
This article addresses the background and nature of the recent success of Large Language Models (LLMs), tracing the history of their fundamental concepts from Leibniz and his calculus ratiocinator to Turing’s computational models of learning, and ultimately to the current development of GPTs. As Kahneman’s “System 1”-type processes, GPTs lack mechanisms that would render them conscious, but they nonetheless demonstrate a certain level of intelligence and the capacity to represent and process knowledge. This is achieved by processing vast corpora of human-created knowledge, which, for its initial production, required human consciousness, but can now be collected, compressed, and processed automatically.

AI systems must not confuse users about their sentience or moral status - Schwitzgebel, Eric (Patterns, 2023)
One relatively neglected challenge in ethical artificial intelligence (AI) design is ensuring that AI systems invite a degree of emotional and moral concern appropriate to their moral standing. Although experts generally agree that current AI chatbots are not sentient to any meaningful degree, these systems can already provoke substantial attachment and sometimes intense emotional responses in users. Furthermore, rapid advances in AI technology could soon create AIs of plausibly debatable sentience and moral standing, at least by some relevant definitions. Morally confusing AI systems create unfortunate ethical dilemmas for the owners and users of those systems, since it is unclear how those systems ethically should be treated. I argue here that, to the extent possible, we should avoid creating AI systems whose sentience or moral standing is unclear and that AI systems should be designed so as to invite appropriate emotional responses in ordinary users.

Can Computational Intelligence Model Phenomenal Consciousness? - Garrido Merchán, Eduardo; Lumbreras, Sara (Philosophies, 2023)
Consciousness and intelligence are properties that can be misunderstood as necessarily dependent. The term artificial intelligence and the kind of problems it managed to solve in recent years has been shown as an argument to establish that machines experience some sort of consciousness. Following Russell’s analogy, if a machine can do what a conscious human being does, the likelihood that the machine is conscious increases. However, the social implications of this analogy are catastrophic. Concretely, if rights are given to entities that can solve the kind of problems that a neurotypical person can, does the machine have potentially more rights than a person that has a disability? For example, the autistic syndrome disorder spectrum can make a person unable to solve the kind of problems that a machine solves. We believe the obvious answer is no, as problem-solving does not imply consciousness. Consequently, we will argue in this paper how phenomenal consciousness, at least, cannot be modeled by computational intelligence and why machines do not possess phenomenal consciousness, although they can potentially develop a higher computational intelligence than human beings. In order to do so, we try to formulate an objective measure of computational intelligence and study how it presents in human beings, animals, and machines. Analogously, we study phenomenal consciousness as a dichotomous variable and how it is distributed in humans, animals, and machines.

The Underlying Rationale of the Emergence of Autonomous Consciousness of Artificial Intelligence - Zhe, Chishu (Zenodo, 2023)
The real problem of the emergence of autonomous consciousness of AI comes with the underlying principles of the philosophy and mathematics that AI uses. That is, the algorithms of AI are wrong in their philosophical logic; another set of algorithms to go with them is missing, i.e., AI uses algorithms that count only ``1''s but not ``0''s, however, the ``0''s must be taken into account. The lack of this philosophy leads to the merge of a large amount of numbers without hierarchical isolation, resulting in the mixing and confusing of absolute numbers and relative numbers. When the calculation runs fast enough and massive numbers are stacking in a moment, relative numbers may pop out the isolation zone. This phenomenon is recognized as the emergence of autonomous consciousness of AI. At least one algorithm based on the mathematical culture of ``0" is needed to cope with the problem.
Keywords: AI algorithm; autonomous consciousness of Artificial Intelligence; emergence; faster-than-light; philosophical meaning of ``1" and ``0"; philosophical significance of ``0"

Attention Schema in Neural Agents - Liu, Dianbo; Bolotta, Samuele; Zhu, He; Bengio, Yoshua; Dumas, Guillaume (arXiv, 2023)
Attention has become a common ingredient in deep learning architectures. It adds a dynamical selection of information on top of the static selection of information supported by weights. In the same way, we can imagine a higher-order informational filter built on top of attention: an Attention Schema (AS), namely, a descriptive and predictive model of attention. In cognitive neuroscience, Attention Schema Theory (AST) supports this idea of distinguishing attention from AS. A strong prediction of this theory is that an agent can use its own AS to also infer the states of other agents' attention and consequently enhance coordination with other agents. As such, multi-agent reinforcement learning would be an ideal setting to experimentally test the validity of AST. We explore different ways in which attention and AS interact with each other. Our preliminary results indicate that agents that implement the AS as a recurrent internal control achieve the best performance. In general, these exploratory experiments suggest that equipping artificial agents with a model of attention can enhance their social intelligence.
Keywords: Computer Science - Artificial Intelligence; Computer Science - Machine Learning

Combining the Projective Consciousness Model and Virtual Humans for Immersive Psychological Research: A Proof-of-concept Simulating a ToM Assessment - Rudrauf, D.; Sergeant-Perhtuis, G.; Tisserand, Y.; Monnor, T.; De Gevigney, V.; Belli, O. (ACM Transactions on Interactive Intelligent Systems, 2023)
Relating explicit psychological mechanisms and observable behaviours is a central aim of psychological and behavioural science. One of the challenges is to understand and model the role of consciousness and, in particular, its subjective perspective as an internal level of representation (including for social cognition) in the governance of behaviour. Toward this aim, we implemented the principles of the Projective Consciousness Model (PCM) into artificial agents embodied as virtual humans, extending a previous implementation of the model. Our goal was to offer a proof-of-concept, based purely on simulations, as a basis for a future methodological framework. Its overarching aim is to be able to assess hidden psychological parameters in human participants, based on a model relevant to consciousness research, in the context of experiments in virtual reality. As an illustration of the approach, we focused on simulating the role of Theory of Mind (ToM) in the choice of strategic behaviours of approach and avoidance to optimise the satisfaction of agents’ preferences. We designed a main experiment in a virtual environment that could be used with real humans, allowing us to classify behaviours as a function of order of ToM, up to the second order. We show that agents using the PCM demonstrated expected behaviours with consistent parameters of ToM in this experiment. We also show that the agents could be used to estimate correctly each other’s order of ToM. Furthermore, in a supplementary experiment, we demonstrated how the agents could simultaneously estimate order of ToM and preferences attributed to others to optimize behavioural outcomes. Future studies will empirically assess and fine tune the framework with real humans in virtual reality experiments.

Do Androids Dread an Electric Sting? - Tait, Izak; Tan, Neşet (2023)
Conscious sentient AI seems to be all but a certainty in our future, whether in fifty years’ time or only five years. When that time comes, we will be faced with entities with the potential to experience more pain and suffering than any other living entity on Earth. In this paper, we look at this potential for suffering and the reasons why we would need to create a framework for protecting artificial entities. We look to current animal welfare laws and regulations to investigate why certain animals are given legal protections, and how this can be applied to AI. We use a meta-theory of consciousness to determine what developments in AI technology are needed to bring AI to the level of animal sentience where legal arguments for their protection can be made. We finally speculate on what a future conscious AI could look like based on current technology.

What Is It Like to Be an AI? The Alignment Problem and the Emergence of Artificial Intelligence: Reflections on the Complexity of Consciousness and Agency - Calvino, Baldolino; Conselheiro, Antonio; Gunn, Angell (Social Science Research Network, 2023)
This essay explores the relationship between the emergence of artificial intelligence (AI) and the problem of aligning its behavior with human values and goals. It argues that the traditional approach of attempting to control or program AI systems to conform to our expectations is insufficient, and proposes an alternative approach based on the ideas of Maturana and Lacan, which emphasize the importance of social relations, constructivism, and the unknowable nature of consciousness.The essay first introduces the concept of Uexkull's umwelt and von Glasersfeld's constructivism, and explains how these ideas inform Maturana's view of the construction of knowledge, intelligence, and consciousness. It then discusses Lacan's ideas about the role of symbolism in the formation of the self and the subjective experience of reality.The essay argues that the infeasibility of a hard-coded consciousness concept suggests that the search for a generalized AI consciousness is meaningless. Instead, we should focus on specific, easily conceptualized features of AI intelligence and agency. Moreover, the emergence of cognitive abilities in AI will likely be different from human cognition, and therefore require a different approach to aligning AI behavior with human values.The essay proposes an approach based on Maturana's and Lacan’s ideas, which emphasizes building a solution together with emergent machine agents, rather than attempting to control or program them. It argues that this approach offers a way to solve the alignment problem by creating a collective, relational quest for a better future hybrid society where human and non-human agents live and build things side by side.In conclusion, the essay suggests that while our understanding of AI consciousness and intelligence may never be complete, this should not deter us from continuing to develop agential AI. Instead, we should embrace the unknown and work collaboratively with AI systems to create a better future for all.
Keywords: AI alignment; Lacan; Maturana; artificial intelligence; biology of cognition

ChatGPT and the Chinese Room Argument: An Eloquent AI Conversationalist Lacking True Understanding and Consciousness - Hamid, Oussama H. (2023 9th International Conference on Information Technology Trends (ITT), 2023)
This paper explores the cognitive implications of recent advancements in large language models (LLMs), with a specific focus on ChatGPT. We contribute to the ongoing debate about the cognitive significance of current LLMs by drawing an analogy to the Chinese Room Argument, a thought experiment that questions the genuine understanding of language in machines (computer programs). Our argument posits that current LLMs, including ChatGPT, generate text resembling human-like responses, akin to the process depicted in the Chinese Room Argument. In both cases, the responses are provided without a deep understanding of the language, thus lacking true signs of consciousness.

No-Go Theorems on Machine Consciousness - Kak, Subhash (2023)
Creating machines that are conscious is a long term objective of research in artificial intelligence. This paper look at this idea with new arguments from physics and logic.  Observers have no place in classical physics, and although they play a role in measurement in quantum physics there is no explanation for their emergence within the framework. There is suggestion that consciousness, which is implicitly a property of the observer, is a consequence of the complexity of specific brain structures, but this is problematic because one associates free will with consciousness, which goes counter to causal closure of physics. Considering a nested physical system, we argue that even if the system were assumed to have agency, observers cannot exist within it. Since complex systems can be viewed in nested hierarchies, this constitutes a proof against consciousness as a product of complexity, for then we will have nested system of conscious agents. As the existence of consciousness in cognitive agents cannot be denied, the implication is that consciousness belongs to a dimension that is not physical and machine consciousness is unattainable. These ideas are used to take a fresh look at two well-known paradoxes of quantum theory that are important in quantum information theory.

Artificial Consciousness Is Morally Irrelevant - Blackshaw, Bruce P. (AJOB Neuroscience, 2023)
It is widely agreed that possession of consciousness contributes to an entity’s moral status. Therefore, if we could identify consciousness in a machine, this would be a compelling argument for considering it to possess at least a degree of moral status. However, as Elisabeth Hildt explains, our third person perspective on artificial intelligence means that determining if a machine is conscious will be very difficult. In this commentary, I argue that this epistemological question cannot be conclusively answered, rendering artificial consciousness as morally irrelevant in practice. I also argue that Hildt’s suggestion that we avoid developing morally relevant forms of machine consciousness is impractical. Instead, we should design artificial intelligences so they can communicate with us. We can use their behavior to assign them what I call an artificial moral status, where we treat them as if they had moral status equivalent to that of a living organism with similar behavior.

An Immortal Ghost in the Machine? - Gibson, Richard B. (AJOB Neuroscience, 2023)

An Exploration of Moral Relevance and the Prospect of Artificial Consciousness - Gorbea, Mikel Salvador (AJOB Neuroscience, 2023)

Who Owns the Brains behind the Machine? Will the Hot Debate on AI's Inventorship and Authorship Rights Force a Premature Determination of Machine Consciousness? - Greenbaum, Dov (AJOB Neuroscience, 2023)

Artificial Consciousness is Unlikely to Possess a Moral Capacity - Gregg, Benjamin (AJOB Neuroscience, 2023)

The Prospects of Artificial Consciousness: Ethical Dimensions and Concerns - Hildt, Elisabeth (AJOB Neuroscience, 2023)
Can machines be conscious and what would be the ethical implications? This article gives an overview of current robotics approaches toward machine consciousness and considers factors that hamper an understanding of machine consciousness. After addressing the epistemological question of how we would know whether a machine is conscious and discussing potential advantages of potential future machine consciousness, it outlines the role of consciousness for ascribing moral status. As machine consciousness would most probably differ considerably from human consciousness, several complex questions must be addressed, including what forms of machine consciousness would be morally relevant forms of consciousness, and what the ethical implications of morally relevant forms of machine consciousness would be. While admittedly part of this reflection is speculative in nature, it clearly underlines the need for a detailed conceptual analysis of the concept of artificial consciousness and stresses the imperative to avoid building machines with morally relevant forms of consciousness. The article ends with some suggestions for potential future regulation of machine consciousness.

The Morphospace of Consciousness: Three Kinds of Complexity for Minds and Machines - Arsiwalla, Xerxes D.; Solé, Ricard; Moulin-Frier, Clément; Herreros, Ivan; Sánchez-Fibla, Martí; Verschure, Paul (NeuroSci, 2023)
In this perspective article, we show that a morphospace, based on information-theoretic measures, can be a useful construct for comparing biological agents with artificial intelligence (AI) systems. The axes of this space label three kinds of complexity: (i) autonomic, (ii) computational and (iii) social complexity. On this space, we map biological agents such as bacteria, bees, C. elegans, primates and humans; as well as AI technologies such as deep neural networks, multi-agent bots, social robots, Siri and Watson. A complexity-based conceptualization provides a useful framework for identifying defining features and classes of conscious and intelligent systems. Starting with cognitive and clinical metrics of consciousness that assess awareness and wakefulness, we ask how AI and synthetically engineered life-forms would measure on homologous metrics. We argue that awareness and wakefulness stem from computational and autonomic complexity. Furthermore, tapping insights from cognitive robotics, we examine the functional role of consciousness in the context of evolutionary games. This points to a third kind of complexity for describing consciousness, namely, social complexity. Based on these metrics, our morphospace suggests the possibility of additional types of consciousness other than biological; namely, synthetic, group-based and simulated. This space provides a common conceptual framework for comparing traits and highlighting design principles of minds and machines.

Signs of Consciousness in Ai: Can Gpt-3 Tell How Smart it Really is? - Bojic, Ljubisa; Stojković, Irena; Jolić Marjanović, Zorana (Social Science Research Network, 2023)
The emergence of artificial intelligence (AI) has been transforming the way humans live, work, and interact with one another. From automation to personalized customer service, AI has had a profound impact on everyday life. At the same time, AI has become something of an ideology, lauded for its potential to revolutionize the future. Yet, as with any technology, there are risks and concerns associated with its use. For example, Blake Lemoine, a Google engineer, recently suggested the possibility of the AI chatbot LaMDA becoming sentient. GPT-3 is one of the most powerful language models open to public use as it is capable of reasoning similarly to humans. Initial assessments of GPT-3 suggest that it may also possess some degree of consciousness. Among other things, this could be attributed to its ability to generate human-like responses to queries, which suggests that these are based on at least basic level of understanding. To further explore this, in the current study both objective and self-assessment tests of cognitive (CI) and emotional intelligence (EI) were administered to GPT-3. Results reveal that GPT-3 was superior to average humans on CI tests that mainly require use and demonstration of acquired knowledge. On the other hand, its logical reasoning and emotional intelligence capacities are equal to those of an average human examinee. Additionally, GPT-3’s self-assessments of CI and EI were similar to the those typically found in humans, which could be understood as a demonstration of subjectivity and self-awareness–consciousness. Further discussion was conducted to put these findings into a wider context. Being that this study was performed only on one of the models from the GPT-3 family, a more thorough investigation would require inclusion of multiple NLP models.
Keywords: GPT-3; artificial intelligence; cognitive intelligence; consciousness; emotional intelligence

Leveraging conscious and nonconscious learning for efficient AI - St. Clair, Rachel; Coward, L. Andrew; Schneider, Susan (Frontiers in Computational Neuroscience, 2023)
Various interpretations of the literature detailing the neural basis of learning have in part led to disagreements concerning how consciousness arises. Further, artificial learning model design has suffered in replicating intelligence as it occurs in the human brain. Here, we present a novel learning model, which we term the “Recommendation Architecture (RA) Model” from prior theoretical works proposed by Coward, using a dual-learning approach featuring both consequence feedback and non-consequence feedback. The RA model is tested on a categorical learning task where no two inputs are the same throughout training and/or testing. We compare this to three consequence feedback only models based on backpropagation and reinforcement learning. Results indicate that the RA model learns novelty more efficiently and can accurately return to prior learning after new learning with less computational resources expenditure. The final results of the study show that consequence feedback as interpretation, not creation, of cortical activity creates a learning style more similar to human learning in terms of resource efficiency. Stable information meanings underlie conscious experiences. The work provided here attempts to link the neural basis of nonconscious and conscious learning while providing early results for a learning protocol more similar to human brains than is currently available.

Universal Cognitive Intelligence, from Cognitive Consciousness, and Lambda (?) - Bringsjord, Selmer; Govindarajulu, Naveen Sundar; Oswald, James (Computational Approaches to Conscious Artificial Intelligence, 2023)
We explain that the concept of universal cognitive intelligence (𝒰𝒞ℐ) can be derived in part by generalization from the previously introduced (and axiomatized) theory of cognitive consciousness, and the framework, Λ, for measuring the degree of such consciousness in an agent at a given time. 𝒰𝒞ℐ (i) covers intelligence that is artificial or natural (or a hybrid thereof) in nature, and intelligence that is not merely Turing-level or less, but also beyond this level; (ii) reflects a psychometric orientation to AI; (iii) withstands a series of objections (including e.g. the opposing position of David Gamez on tests, intelligence, and consciousness, and the complaint that so-called “emotional intelligence” is beyond the reach of any logic-based framework, including thus 𝒰𝒞ℐ); and (iv) connects smoothly and symbiotically with important formal hierarchies (e.g., the Polynomial, Arithmetic, and Analytic Hierarchies), while at the same yielding its own new all-encompassing hierarchy of logic machines: 𝔏𝔐. We end with an admission: 𝒰𝒞ℐ by our lights, for reasons previously published, cannot take account of any form of intelligence that genuinely exploits phenomenal consciousness.

On Artificial Intelligence, Consciousness and Robots - Haikonen, Pentti O. A. (Computational Approaches to Conscious Artificial Intelligence, 2023)
Will Artificial Intelligence soon surpass the capacities of the human mind and will Strong Artificial General Intelligence replace the contemporary Weak AI? It might appear to be so, but there are certain fundamental issues that have to be addressed before this can happen. There can be no intelligence without understanding, and there can be no understanding without getting meanings. Contemporary computers manipulate symbols without meanings, which are not incorporated in the computations. This leads to the Symbol Grounding Problem; how could meanings be incorporated? The use of self-explanatory sensory information has been proposed as a possible solution. However, self-explanatory information can only be used in neural network machines that are different from existing digital computers and traditional multilayer neural networks. In humans self-explanatory information has the form of qualitative sensory experiences, qualia. To have reportable qualia is to be phenomenally conscious. This leads to the hypothesis about an unavoidable connection between the solution of the Symbol Grounding Problem and consciousness. If, in general, self-explanatory information equals to qualia, then machines that utilize self-explanatory information would be conscious. The author presents the associative neural architecture HCA as a solution to these problems and the robot XCR-1 as its partial experimental verification.
Keywords: artificial intelligence; cognitive robots; machine consciousness; qualia; symbol grounding problem

Consciousness influences in ToM and Metacognition functioning - An artificial intelligence perspective - Bamicha, Victoria; Drigas, Athanasios (Research, Society and Development, 2023)
Consciousness is a cognitive function that maintains its eternal character as long as it is strengthened and enriched by the optimal functioning of the corresponding neural networks of the brain, which are stimulated during its activation. The present study explores its relationship with the cognitive functions of the Theory of Mind and Metacognition and briefly explains their approach through Artificial Intelligence. The selection of the bibliographic review contributed to the utilization of the existing scientific knowledge and research data for the most effective analysis and study of the subject. The observations made throughout the research highlight the pivotal role of consciousness in the evolution of the aforementioned cognitive processes, as it is at the core of their development. Essentially, the research seeks to emphasize the importance of consciousness in the functioning of the Theory of Mind and Metacognition, as it serves as the springboard for the perception and understanding of our existence, significantly influencing our further social and cognitive development.

From Artificial Intelligence to Artificial Consciousness: An Interior Design Implication - Mahendarto, Trias (Journal of Artificial Intelligence in Architecture, 2023)
Artificial Intelligence continues to develop rapidly and provokes people to think about Artificial consciousness. Anthropocentric understanding considers consciousness a unique feature of human beings not possessed by other living beings. However, software and hardware development demonstrated the ability to process, analyze, and infer increasingly comprehensive data close to the image of human brain performance. Furthermore, the application of artificial Intelligence to human-friendly objects that can communicate with humans evokes the presence of consciousness within these objects. This paper discusses the presence of artificial consciousness in humanoid robots as an evolutionary continuation of artificial Intelligence. It estimates its implications for architecture, primarily within interior design. Consciousness has a special place in architecture, as it guides Intelligence in engineering and brings it to an abstract level, such as aesthetics. This paper extracts popular information from Internet conversations and theories in pre-existing scientific journals. This paper concludes that the adaptability of both parties and the balance of positions between the two parties in the future will influence the development of interior design approaches that will integrate artificial Intelligence and humans.

Towards Modeling Artificial Consciousness - Vakulenko, Maksym (2023)
A new synergetic approach to consciousness modeling is proposed, which takes into account recent advancements in neuroscience, information technologies, and philosophy.

Consciousness and Creativity in Artificial Intelligence: The Cognitive Side of Knowledge Management - Johannessen, Jon-Arild (Emerald Publishing Limited, 2023)

Souls and Selves: Querying an AI Self with a View to Human Selves and Consciousness - Oberg, Andrew (Religions, 2023)
The question of self-aware artificial intelligence may turn on the question of the human self. To explore some of the possibilities in play we start from an assumption that the self is often pre-analytically and by default conceptually viewed along lines that have likely been based on or from the kind of Abrahamic faith notion as expressed by a “true essence” (although not necessarily a static one), such as is given in the often vaguely used “soul”. Yet, we contend that the self is separately definable, and in relatively narrow terms; if so, of what could the self be composed? We begin with a brief review of the descriptions of the soul as expressed by some sample scriptural references taken from these religious lineages, and then transition to attempt a self-concept in psychological and cognitive terms that necessarily differentiates and delimits it from the ambiguous word “soul”. From these efforts too will emerge the type of elements that are needed for a self to be present, allowing us to think of the self in an artificial intelligence (AI) context. If AI might have a self, could it be substantively close to a human’s? Would an “en-selved” AI be achievable? I will argue that there are reasons to think so, but that everything hinges on how we understand consciousness, and hence ruminating on that area—and the possibility or lack thereof in extension to non-organic devices—will comprise our summative consideration of the pertinent theoretical aspects. Finally, the practical will need to be briefly addressed, and for this, some of the questions that would have to be asked regarding what it might mean ethically to relate to AI if an “artificial self” could indeed arise will be raised but not answered. To think fairly about artificial intelligence without anthropomorphizing it we need to better understand our own selves and our own minds. This paper will attempt to analyze the self within these bounds.

Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making - Albarracin, Mahault; Hipólito, Inês; Tremblay, Safae Essafi; Fox, Jason G.; René, Gabriel; Friston, Karl; Ramstead, Maxwell J. D. (arXiv, 2023)
This paper investigates the prospect of developing human-interpretable, explainable artificial intelligence (AI) systems based on active inference and the free energy principle. We first provide a brief overview of active inference, and in particular, of how it applies to the modeling of decision-making, introspection, as well as the generation of overt and covert actions. We then discuss how active inference can be leveraged to design explainable AI systems, namely, by allowing us to model core features of ``introspective'' processes and by generating useful, human-interpretable models of the processes involved in decision-making. We propose an architecture for explainable AI systems using active inference. This architecture foregrounds the role of an explicit hierarchical generative model, the operation of which enables the AI system to track and explain the factors that contribute to its own decisions, and whose structure is designed to be interpretable and auditable by human users. We outline how this architecture can integrate diverse sources of information to make informed decisions in an auditable manner, mimicking or reproducing aspects of human-like consciousness and introspection. Finally, we discuss the implications of our findings for future research in AI, and the potential ethical considerations of developing AI systems with (the appearance of) introspective capabilities.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

AI and the Cognitive Sense of Self - Barnes, Emily; Hutson, James (Journal of Intelligent Communication, 2023)
This article explores the development of a cognitive sense of self within artificial intelligence (AI), emphasizing the transformative potential of self-awareness in enhancing AI functionalities for sophisticated interactions and autonomous decision-making. Rooted in interdisciplinary approaches that incorporate insights from cognitive science and practical AI applications, the study investigates the mechanisms through which AI can achieve self-recognition, reflection, and continuity of identity—key attributes analogous to human consciousness. This research is pivotal for fields such as healthcare and robotics, where AI systems benefit from personalized interactions and adaptive responses to complex environments. The concept of a self-aware AI involves the ability for systems to recognize themselves as distinct entities within their operational contexts, which could significantly enhance their functionality and decision-making capabilities. Further, the study delves into the ethical dimensions introduced by the advent of self-aware AI, exploring the profound questions concerning the rights of AI entities and the responsibilities of their creators. The development of self-aware AI raises critical issues about the treatment and status of AI systems, prompting the need for comprehensive ethical frameworks to guide their development. Such frameworks are essential for ensuring that the advancement of self-aware AI aligns with societal values and promotes the well-being of all stakeholders involved.
Keywords: Artificial Intelligence; Autonomous Systems; Cognitive Self; Ethical AI; Human-like Consciousness.

Reflection on systemic aspects of consciousness - Bělinová, Zuzana (Neural Network World, 2023)
Today's quick development of artificial intelligence (AI) brings us to the questions that have until recently been the domain of philosophy or even sciencefiction. When can be a system considered an intelligent one? What is a consciousness and where it comes from? Can systems gain consciousness? It is necessary to have in mind, that although the development seems to be a revolutionary one, the progress is successive, today's technologies did not emerge from thin air, they are firmly built on previous findings. As now some wild thoughts and theories where the AI development leads to have arisen, it is time to look back at the background theories and summarize, what do we know on the topics of intelligence, consciousness, where they come from and what are different viewpoints on these topics. This paper combines the findings from different areas and present overview of different attitudes on systems consciousness and emphasizes the role of systems sciences in helping the knowledge in this area.

Consciousness in Artificial Intelligence: Insights from the Science of Consciousness - Butlin, Patrick; Long, Robert; Elmoznino, Eric; Bengio, Yoshua; Birch, Jonathan; Constant, Axel; Deane, George; Fleming, Stephen M.; Frith, Chris; Ji, Xu; Kanai, Ryota; Klein, Colin; et al. (arXiv, 2023)
Whether current or near-term AI systems could be conscious is a topic of scientific interest and increasing public concern. This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness: assessing existing AI systems in detail, in light of our best-supported neuroscientific theories of consciousness. We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory. From these theories we derive "indicator properties" of consciousness, elucidated in computational terms that allow us to assess AI systems for these properties. We use these indicator properties to assess several recent AI systems, and we discuss how future systems might implement them. Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.
Keywords: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); FOS: Biological sciences; FOS: Computer and information sciences; Machine Learning (cs.LG); Neurons and Cognition (q-bio.NC)

Artificial Intelligence, Communication Systems and Artificial Consciousness - Cardon, Alain; El Hami, Abdelkhalak (Fundamental Generation Systems, 2023)
Today, computer science is a central discipline in science and in society because of the innumerable uses of software that constantly communicate. Generally speaking, computer science deals with the processing of information, which is related to sequential calculations of functions by systems using state machines as a basic element. Artificial intelligence is, in the field of computation, the study and programming of the mechanisms of reasoning and use of knowledge in all fields. The systems and software used on computers have been continuously developed, and one of the highlights is the development of autonomous means of communication between the systems. The Internet is a wonderful means of communication, linking all computer users and making this network indispensable. The chapter also describes the computer modeling of an artificial psychic system that generates representations for a system with corporeality, in other words, an autonomous system that can intentionally generate artificial thoughts and experience them.
Keywords: artificial intelligence; communication systems; computer science; internet network

Human Consciousness and Artificial Intelligent - Challa, Yashaswini Reddy; Lahari, S. Preethi (SSRN Electronic Journal, 2023)
At the point when the advanced PC was developed more than half a century prior, many felt that the quintessence of thinking, had been found. As of late, a few scientists wandered the theory of planning and carrying out a model for Artiﬁcial cognizance . On one hand any expectation of is having the option to plan a cognizant machine, then again such models could be useful for understanding human awareness.

Could a Large Language Model be Conscious? - Chalmers, David J. (arXiv, 2023)
There has recently been widespread discussion of whether large language models might be sentient. Should we take this idea seriously? I will break down the strongest reasons for and against. Given mainstream assumptions in the science of consciousness, there are significant obstacles to consciousness in current models: for example, their lack of recurrent processing, a global workspace, and unified agency. At the same time, it is quite possible that these obstacles will be overcome in the next decade or so. I conclude that while it is somewhat unlikely that current large language models are conscious, we should take seriously the possibility that successors to large language models may be conscious in the not-too-distant future.
Keywords: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); FOS: Computer and information sciences; Machine Learning (cs.LG)

Toward the Aircraft of the Future: A Perspective from Consciousness - Ezhilarasu, Cordelia Mattuvarkuzhali; Angus, Jim; Jennions, Ian K. (Journal of Artificial Intelligence and Consciousness, 2023)
This paper envisions the possibility of a Conscious Aircraft: an aircraft of the future with features of consciousness. To serve this purpose, three main fields are examined: philosophy, cognitive neuroscience, and Artificial Intelligence (AI). While philosophy deals with the concept of what is consciousness, cognitive neuroscience studies the relationship of the brain with consciousness, contributing toward the biomimicry of consciousness in an aircraft. The field of AI leads into machine consciousness. The paper discusses several theories from these fields and derives outcomes suitable for the development of a Conscious Aircraft, some of which include the capability of developing “world-models”, learning about self and others, and the prerequisites of autonomy, selfhood, and emotions. Taking these cues, the paper focuses on the latest developments and the standards guiding the field of autonomous systems, and suggests that the future of autonomous systems depends on its transition toward consciousness. Finally, inspired by the theories suggesting the levels of consciousness, guided by the Theory of Mind, and building upon state-of-the-art aircraft with autonomous systems, this paper suggests the development of a Conscious Aircraft in three stages: Conscious Aircraft with (1) System-awareness, (2) Self-awareness, and (3) Fleet-awareness, from the perspectives of health management, maintenance, and sustainment.

A.I.: Artificial Intelligence as Philosophy: Machine Consciousness and Intelligence - Gamez, David (The Palgrave Handbook of Popular Culture as Philosophy, 2023)
A.I.: Artificial Intelligence tells the story of a robot boy who has been engineered to love his human owner. He is abandoned by his owner and pursues a tragic quest to become a real boy so that he can be loved by her again. This chapter explores the philosophical, psychological, and scientific questions that are asked by A.I. It starts with A.I.’s representation of artificial intelligence and then covers the consciousness of robots, which is closely linked to ethical concerns about the treatment of AIs in the film. There is a discussion about how A.I.’s interpretation of artificial love relates to scientific work on emotion, and the chapter also examines connections between the technology portrayed in A.I. and current research on robotics.

Intelligence and Consciousness in Natural and Artificial Systems - Gamez, David (Series on Machine Consciousness, 2023)
Humans are highly intelligent, and their brains are associated with rich states of consciousness. We typically assume that animals have different levels of consciousness, and this might be correlated with their intelligence. Very little is known about the relationships between intelligence and consciousness in artificial systems. Most of our current definitions of intelligence describe human intelligence. They have severe limitations when they are applied to non-human animals and artificial systems. To address this issue, this chapter sets out a new interpretation of intelligence that is based on a system’s ability to make accurate predictions. Human intelligence is measured using tests whose results are converted into values of IQ and g-score. This approach does not work well with non-human animals and AIs, so people have been developing universal algorithms that can measure intelligence in any type of system. In this chapter a new universal algorithm for measuring intelligence is described, which is based on a system’s ability to make accurate predictions. Many people agree that consciousness is the stream of colorful moving noisy sensations that starts when we wake up and ceases when we fall into deep sleep. Several mathematical algorithms have been developed to describe the relationship between consciousness and the physical world. If these algorithms can be shown to work on human subjects, then they could be used to measure consciousness in non-human animals and artificial systems.

Does ChatGPT have consciousness? - He, Qiheng; Geng, Haiyang; Yang, Yi; Zhao, Jizong (Brain‐X, 2023)
The quest for conscious machines and questions raised by the prospect of self-aware artificial intelligence (AI) fascinate some humans. OpenAI's ChatGPT, celebrated for its human-like comprehension and conversational abilities, is a milestone in that quest.1, 2 Early AI models were basic and rule-driven and mainly completed tasks like checking spelling and correcting grammar. Then, in 2010, recurrent neural network language models were trained to understand and generate text. ChatGPT, using transformer neural networks, produces coherent text and exemplifies this new kind of language model.3 Silicon Valley leaders claimed that these models and similar AI technologies will revolutionize various sectors and raised ethical and societal questions. As we explore AI's potential, we must navigate these implications and emphasize the necessity of using it responsibly. AI is a promising dream, but society must prepare to address the challenges likely to arise from wielding its transformative power.

ChatGPT believes it is conscious - Hintze, Arend (arXiv, 2023)
The development of advanced generative chat models, such as ChatGPT, has raised questions about the potential consciousness of these tools and the extent of their general artificial intelligence. ChatGPT consistent avoidance of passing the test is here overcome by asking ChatGPT to apply the Turing test to itself. This explores the possibility of the model recognizing its own sentience. In its own eyes, it passes this test. ChatGPT's self-assessment makes serious implications about our understanding of the Turing test and the nature of consciousness. This investigation concludes by considering the existence of distinct types of consciousness and the possibility that the Turing test is only effective when applied between consciousnesses of the same kind. This study also raises intriguing questions about the nature of AI consciousness and the validity of the Turing test as a means of verifying such consciousness.
Keywords: FOS: Computer and information sciences; General Literature (cs.GL)

Unlearning Descartes: Sentient AI is a Political Problem - Hull, Gordon (Journal of Social Computing, 2023)
The emergence of Large Language Models (LLMs) has renewed debate about whether Artificial Intelligence (AI) can be conscious or sentient. This paper identifies two approaches to the topic and argues: (1) A “Cartesian” approach treats consciousness, sentience, and personhood as very similar terms, and treats language use as evidence that an entity is conscious. This approach, which has been dominant in AI research, is primarily interested in what consciousness is, and whether an entity possesses it. (2) An alternative “Hobbesian” approach treats consciousness as a sociopolitical issue and is concerned with what the implications are for labeling something sentient or conscious. This both enables a political disambiguation of language, consciousness, and personhood and allows regulation to proceed in the face of intractable problems in deciding if something “really is” sentient. (3) AI systems should not be treated as conscious, for at least two reasons: (a) treating the system as an origin point tends to mask competing interests in creating it, at the expense of the most vulnerable people involved; and (b) it will tend to hinder efforts at holding someone accountable for the behavior of the systems. A major objective of this paper is accordingly to encourage a shift in thinking. In place of the Cartesian question—is AI sentient?—I propose that we confront the more Hobbesian one: Does it make sense to regulate developments in which AI systems behave as if they were sentient?

From Smart Sensing to consciousness: An info-structural model of computational consciousness for non-interacting agents - Iovane, Gerardo; Landi, Riccardo Emanuele (Cognitive Systems Research, 2023)
This study proposes a model of computational consciousness for non-interacting agents. The phenomenon of interest was assumed as sequentially dependent on the cognitive tasks of sensation, perception, emotion, affection, attention, awareness, and consciousness. Starting from the Smart Sensing prodromal study, the cognitive layers associated with the processes of attention, awareness, and consciousness were formally defined and tested together with the other processes concerning sensation, perception, emotion, and affection. The output of the model consists of an index that synthesizes the energetic and entropic contributions of consciousness from a computationally moral perspective. Attention was modeled through a bottom-up approach, while awareness and consciousness by distinguishing environment from subjective cognitive processes. By testing the solution on visual stimuli eliciting the emotions of happiness, anger, fear, surprise, contempt, sadness, disgust, and the neutral state, it was found that the proposed model is concordant with the scientific evidence concerning covert attention. Comparable results were also obtained regarding studies investigating awareness as a consequence of visual stimuli repetition, as well as those investigating moral judgments to visual stimuli eliciting disgust and sadness. The solution represents a novel approach for defining computational consciousness through artificial emotional activity and morality.

Consciousness for Artificial Intelligence? - Johnson, Arthur T. (IEEE Pulse, 2023)

Human Consciousness and Artificial Intelligence: Can AI Develop Human-Like Consciousness? Cognitive Abilities? Ethics? - Keerthi, Yamasani; Mohapatro, Swagatika; Saraf, Krishna (SSRN Electronic Journal, 2023)
Artificial intelligence endures the necessary capacity that allows automation directed towards emulate mortal intellect action. In this research paper gives a broad analysis of AI consciousness. The primary objective indicated the situation inhabits facing exploration of Artificial intelligence could develop humans like cognition. Numerous analysts include and consider automobile comprehension models. Consciousness study is a developing subject in both neuroscience and psychology that includes a variety of methods, from experimental animal models in human brain pathology. Here we discuss the contrasts bounded by mortal cognizance along automobile perception in addition above mentioned physiological talents benefit mortal compassionate in development regard to the subsequent world. Artificial intelligence enabled automatic driving automobiles using the diversion zone. Human intelligence generally refers to the ability of mental activities. However, due to its poor level of intelligibility and ethical difficulties. Artificial intelligence established automation posture, compelling uncertainty towards the user, individuals along with society. According to what AI can advance in subsequent at the same-time human empathetic endure involved along computer expertise adopting the diversion portrait.

Taking Robots Beyond the Threshold of Awareness: Scientifically Founded Conditions for Artificial Consciousness - Keppler, Joachim (Proceedings of the 1St Workshop on Artificial Intelligence for Perception and Artificial Consciousness (Aixpac 2023), Ceur Workshop Proceedings, Volume 3563, 2023)
To approach the creation of artificial conscious systems systematically and to obtain certainty about the presence of phenomenal qualities (qualia) in these systems, we must first decipher the fundamental mechanism behind conscious processes. In achieving this goal, the conventional physicalist position exhibits obvious shortcomings in that it provides neither a plausible mechanism for the generation of qualia nor tangible demarcation criteria for conscious systems. Therefore, to remedy the deficiencies of the standard physicalist approach, a new theory for the understanding of consciousness has been formulated. The aim of the paper is to present the cornerstones of this theory, to outline the conditions for conscious systems derived from the theory, and to address the implications of these conditions for the creation of robots that transcend the threshold of phenomenal awareness. In short, the theory is based on the proposition that the universe is permeated by a ubiquitous field of consciousness that can be equated with the zero-point field (ZPF) of quantum electrodynamics (QED). The ZPF, which is characterized by a spectrum of field modes, plays a crucial role in the edifice of modern physics. QED-based model calculations on cortical dynamics and empirical findings on the neural correlates of consciousness suggest that a physical system can only generate conscious states if it is capable of establishing resonant coupling to the ZPF, resulting in the amplification of selected field modes and the activation of the phenomenal qualities that are assumed to be associated with these modes. Thus, scientifically sound considerations support the conclusion that the crucial condition for generating conscious states lies in a system's capacity to tap into the phenomenal color palette inherent in the ZPF.

If consciousness is dynamically relevant, artificial intelligence isn't conscious - Kleiner, Johannes; Ludwig, Tim (arXiv, 2023)
We demonstrate that if consciousness is relevant for the temporal evolution of a system's states--that is, if it is dynamically relevant--then AI systems cannot be conscious. That is because AI systems run on CPUs, GPUs, TPUs or other processors which have been designed and verified to adhere to computational dynamics that systematically preclude or suppress deviations. The design and verification preclude or suppress, in particular, potential consciousness-related dynamical effects, so that if consciousness is dynamically relevant, AI systems cannot be conscious.
Keywords: 68T99; Artificial Intelligence (cs.AI); FOS: Computer and information sciences

CognitiveNet: Enriching Foundation Models with Emotions and Awareness - Landi, Riccardo Emanuele; Chinnici, Marta; Iovane, Gerardo (Universal Access in Human-Computer Interaction, 2023)
Foundation models are gaining considerable interest for their capacity of solving many downstream tasks without fine-tuning parameters on specific datasets. The same solutions can connect visual and linguistic representations through image-text contrastive learning. These abilities allow an artificial agent to act similarly to a human, but significant cognitive processes still need to be introduced in the learning process. The present study proposes an advancement to more human-like artificial intelligence by introducing CognitiveNet, a learnable architecture integrating foundation models. Starting from the latest studies in the field of Artificial Consciousness, a hierarchy of cognitive layers has been modeled and pre-trained for estimating the emotional content of images. By employing CLIP as the backbone model, significant concordant emotional activity was produced. Furthermore, the proposed model overcomes the accuracy of CLIP in classifying CIFAR-10 and -100 datasets through supervised optimization, suggesting CognitiveNet as a promising solution for solving classification tasks through online meta-learning.

Towards the Artificial Brain: A Base Framework for Modelling Consciousness and Unconsciousness - Lopes, Daniel (arXiv, 2023)
One of the current AI issues depicted in popular culture is the fear of conscious super AIs that try to take control over humanity. And as computational power goes upwards and that turns more and more into a reality, understanding artificial brains might be increasingly important to control and drive AI towards the benefit of our societies. This paper proposes a base framework to aid the development of autonomous multipurpose artificial brains. To approach that, we propose to first model the functioning of the human brain by reflecting and taking inspiration from the way the body, the consciousness and the unconsciousness interact. To do that, we tried to model events such as sensing, thinking, dreaming and acting, thoughtfully or unconsciously. We believe valuable insights can already be drawn from the analysis and critique of the presented framework, and that it might be worth implementing it, with or without changes, to create, study, understand and control artificially conscious systems.
Keywords: FOS: Biological sciences; Neurons and Cognition (q-bio.NC)

Taking into Account Sentient Non-Humans in AI Ambitious Value Learning: Sentientist Coherent Extrapolated Volition - Moret, Adrià R. (Journal of Artificial Intelligence and Consciousness, 2023)
Ambitious value learning proposals to solve the AI alignment problem and avoid catastrophic outcomes from a possible future misaligned Artificial Superintelligence (ASI), such as Coherent Extrapolated Volition (CEV), have focused on ensuring that an Artificial Superintelligence would try to do what humans would want it to do. However, present and future sentient non-humans, such as non-human animals and possible future digital minds, could also be affected by the ASI’s behavior in morally relevant ways. This paper puts forward Sentientist Coherent Extrapolated Volition, an alternative to CEV, that directly takes into account the interests of all sentient beings. This ambitious value learning proposal would significantly reduce the likelihood of risks of astronomical suffering from the ASI’s behavior, and thus we have very strong pro-tanto moral reasons in favor of implementing it instead of the CEV. This fact is crucial in conducting an adequate cost–benefit analysis between different ambitious value learning proposals.

Could artificial intelligence have consciousness? Some perspectives from neurology and parapsychology - Ng, Yew-Kwang (AI & SOCIETY, 2023)
The possibility of AI consciousness depends much on the correct answer to the mind–body problem: how our materialistic brain generates subjective consciousness? If a materialistic answer is valid, machine consciousness must be possible, at least in principle, though the actual instantiation of consciousness may still take a very long time. If a non-materialistic one (either mentalist or dualist) is valid, machine consciousness is much less likely, perhaps impossible, as some mental element may also be required. Some recent advances in neurology (despite the separation of the two hemispheres, our brain as a whole is still able to produce only one conscious agent; the negation of the absence of a free will, previously thought to be established by the Libet experiments) and many results of parapsychology (on medium communications, memories of past lives, near-death experiences) suggestive of survival after our biological death, strongly support the non-materialistic position and hence the much lower likelihood of AI consciousness. Instead of being concern about AI turning conscious and machine ethics, and trying to instantiate AI consciousness soon, we should perhaps focus more on making AI less costly and more useful to society.

Artificial Conscious Intelligence: Why Machine Consciousness Matters to AI - Reggia, James A.; Katz, Garrett E.; Davis, Gregory P. (Series on Machine Consciousness, 2023)
The fields of artificial intelligence (AI) and artificial consciousness (AC) have largely developed separately, with different goals and criteria for success and with only a minimal exchange of ideas. In this chapter, we consider the question of how concepts developed in AC research might contribute to more effective future AI systems. We first briefly discuss several past hypotheses about the function(s) of human consciousness, and present our own hypothesis that short-term working memory and very rapid learning should be a central concern in such matters. We describe our recent efforts to explore this hypothesis computationally and to identify associated computational correlates of consciousness. We then present ideas about how integrating concepts from AC into AI systems to develop an artificial conscious intelligence (ACI) could both produce more effective AI technology and contribute to a deeper scientific understanding of the fundamental nature of consciousness and intelligence.

Interactions Between Humans, Cyborgs, and Artificial Consciousness Modeled Through Operators and Function Spaces - Ruette, Fernando (Journal of Artificial Intelligence and Consciousness, 2023)
This paper describes a mathematical model based on operators and function spaces (Hilbert space) to better understand consciousness and the relationship between human and artificial consciousness (AC). Scientific understanding of the relationships between human consciousness (HC) and AC may shed new light on the future of HC and AC. This mathematical physical model considers general models of external and internal realities. Some schemes using external reality, senses or sensors, body-brain or computer software, internal reality, and HC or AC are discussed. The cyclic interaction of the internal reality maintains on time through decision-making (consciousness) and body-brain operators seem to be the origin of consciousness. An analysis of the importance of the AC and cyborg consciousnesses (CC) in the interaction with HC is also presented. It is concluded that the creation of CC and AC will allow the study of HC through experimentation by the evaluation of functions of emotion (values, feelings, penalties, and rewards) demanded by those consciousnesses. This will result in the transformation of the HC.

Unifying Consciousness and Time to Enhance Artificial Intelligence - Samarawickrama, Mahendra (arXiv, 2023)
Consciousness is a sequential process of awareness which can focus on one piece of information at a time. This process of awareness experiences causation which underpins the notion of time while it interplays with matter and energy, forming reality. The study of Consciousness, time and reality is complex and evolving fast in many fields, including metaphysics and fundamental physics. Reality composes patterns in human Consciousness in response to the regularities in nature. These regularities could be physical (e.g., astronomical, environmental), biological, chemical, mental, social, etc. The patterns that emerged in Consciousness were correlated to the environment, life and social behaviours followed by constructed frameworks, systems and structures. The complex constructs evolved as cultures, customs, norms and values, which created a diverse society. In the evolution of responsible AI, it is important to be attuned to the evolved cultural, ethical and moral values through Consciousness. This requires the advocated design of self-learning AI aware of time perception and human ethics.
Keywords: Artificial Intelligence (cs.AI); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

Human Consciousness and Artificial Intelligence: Can AI Develop Human-Like Consciousness? Cognitive Abilities? What about Ethics? - Shruthi, R (SSRN Electronic Journal, 2023)
“Artificial intelligence” is necessarily a stimulation of human intelligence. It is only capable of stimulating and replacing a part of human intelligence. It is only capable of extending and on expanding the human intelligence to a small extent. “Further research and development of other advanced technologies such as the brain-computer interface (BCI) along with the continuing evolution of the human mind is what will eventually contribute to a powerful AI era” (Yanyan Dong, n.d.). In such an era it will be possible for AI to simulate and even replace the extensive imagination, emotions and intuition of humankind. It may be able to potentially mimic the tactics, experimental understanding and other types of individualized intelligence. Vital advancements in the algorithms by analytical calculations will enable successful perforation of AI into all sorts of sectors including commerce, the science of medicine and education. As to the human concerns, namely who has control over humanity and these machines, the conclusion is that artificial intelligence will only be a service provider for humankind while validating the values on cause and by supporting a standard set of ethics (Yanyan Dong, n.d.).

Towards Emotion-Based Synthetic Consciousness: Using LLMs to Estimate Emotion Probability Vectors - Sinclair, David; Pye, Willem (arXiv, 2023)
This paper shows how LLMs (Large Language Models) may be used to estimate a summary of the emotional state associated with piece of text. The summary of emotional state is a dictionary of words used to describe emotion together with the probability of the word appearing after a prompt comprising the original text and an emotion eliciting tail. Through emotion analysis of Amazon product reviews we demonstrate emotion descriptors can be mapped into a PCA type space. It was hoped that text descriptions of actions to improve a current text described state could also be elicited through a tail prompt. Experiment seemed to indicate that this is not straightforward to make work. This failure put our hoped for selection of action via choosing the best predict ed outcome via comparing emotional responses out of reach for the moment.
Keywords: Computation and Language (cs.CL); FOS: Computer and information sciences

Artificial Intelligence/Consciousness: being and becoming John Malkovich - Singh, Amar; Tholia, Shipra (AI & SOCIETY, 2023)
For humans, Artificial Intelligence operates more like a Rorschach test, as it is expected that intelligent machines will reflect humans' cognitive and physical behaviours. The concept of intelligence, however, is often confused with consciousness, and it is believed that the progress of intelligent machines will eventually result in them becoming conscious in the future. Nevertheless, what is overlooked is how the exploration of Artificial Intelligence also pertains to the development of human consciousness. An excellent example of this can be seen in the film Being John Malkovich (1999). In the film, different characters have their perceptions altered as a result of hacking into the mind of John Malkovich, which produces sensations that may have remained hidden to their consciousness due to their dis-abilities. This article engages with the research question: Can the symbiotic relationship between humans and machines trigger an artificial consciousness for humans? An artificially created consciousness is the premise that a machine can generate knowledge about an individual that is not already present in the person. For the same purpose, the article takes the cinematic text Being John Malkovich by Spike Jonze for exploring concepts such as human/robot rights, virtual sex, virtual rape, and bodily disability, which are essential topics in the midst of increasing human- Artificial Intelligence interaction. The purpose of this article is to contribute towards the creation of a better understanding of Artificial Intelligence, particularly from the perspective of film studies and philosophy, by highlighting the potential of Artificial Intelligence as a vessel for exploring human consciousness.

Can An AI Gain Consciousness? - Conselheiro, Antonio; Gunn, Angell (Social Science Research Network, 2022)
This text discusses the idea that a natural language model, like LaMDA, may be considered conscious despite its lack of complexity. It argues that the model is composed of a large dataset of natural language examples and is not self-aware, but it is possible that its consciousness emulation is analogous to some of the processes behind human conciousness. The article discusses the hypothesis that human consciousness may be kindred to a linguistic model, though it is difficult to clue such hypothesis with the current understanding and assumptions. It also discusses the difficulties in telling one’s human from a linguistic model, and how consciousness may not be homogeneous across different human cultures. It concludes that more discussion is needed in order to clarify concepts such as conciousness, and its possible inception in a complex artificial inteligence scenario.
Keywords: artificial inteligence; conciousness; natural language models; self-awareness

Artificial Agential Intelligence - Cheng, Tony (Journal of Artificial Intelligence and Consciousness, 2022)
Since artificial intelligence (AI) emerged in the mid-20th century, it has incurred many theoretical criticisms (Dreyfus, H. [1972] What Computers Can't Do (MIT Press, New York); Dreyfus, H. [1992] What Computers Still Can't Do (MIT Press, New York); Searle, J. [1980] Minds, brains and programs, Behav. Brain Sci. 3, 417-457; Searle, J. [1984] Minds, Brains and Sciences (Harvard University Press, Cambridge, MA); Searle, J. [1992] The Rediscovery of the Mind (MIT Press, Cambridge, MA); Fodor, J. [2002] The Mind Doesn't Work that Way: The Scope and Limits of Computational Psychology (MIT Press, Cambridge, MA).). The technical improvements of machine learning and deep learning, though, have been continuing and many breakthroughs have occurred recently. This makes theoretical considerations urgent again: can this new wave of AI fare better than its precursors in emulating or even having human-like minds? I propose a cautious yet positive hypothesis: current AI might create human-like mind, but only if it incorporates certain conceptual rewiring: it needs to shift from a task-based to an agent-based framework, which can be dubbed "Artificial Agential Intelligence"(AAI). It comprises practical reason (McDowell, J. [1979] Virtue and reason, Monist 62(3), 331-350; McDowell, J. [1996] Mind and World (Harvard University Press, Cambridge, MA)), imaginative understanding (Campbell, J. [2020] Causation in Psychology (Harvard University Press, Cambridge, MA)), and animal knowledge (Sosa, E. [2007] A Virtue Epistemology: Apt Belief and Reflective Knowledge, volume 1 (Oxford University Press, Oxford, UK); Sosa, E. [2015] Judgment and Agency (Oxford University Press, Cambridge, MA)). Moreover, I will explore whether and in what way neuroscience-inspired AI and predictive coding (Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. [2017] Neuroscience-inspired artificial intelligence, Neuron 95(2), 245-258) can help carry out this project.
Keywords: Agent-Based Framework; Animal Knowledge; Imaginative Understanding; Neuroscience-Inspired Artificial Intelligence; Practical Reason; Predictive Coding

A Study on Two Conditions for the Realization of Artificial Empathy and Its Cognitive Foundation - Cui, Zhongliang; Liu, Jing (Philosophies, 2022)
The realization of artificial empathy is conditional on the following: on the one hand, human emotions can be recognized by AI and, on the other hand, the emotions presented by artificial intelligence are consistent with human emotions. Faced with these two conditions, what we explored is how to identify emotions, and how to prove that AI has the ability to reflect on emotional consciousness in the process of cognitive processing, In order to explain the first question, this paper argues that emotion identification mainly includes the following three processes: emotional perception, emotional cognition and emotional reflection. It proposes that emotional display mainly includes the following three dimensions: basic emotions, secondary emotions and abstract emotions. On this basis, the paper proposes that the realization of artificial empathy needs to meet the following three cognitive processing capabilities: the integral processing ability of external emotions, the integral processing ability of proprioceptive emotions and the processing ability of integrating internal and external emotions. We are open to whether the second difficulty can be addressed. In order to gain the reflective ability of emotional consciousness for AI, the paper proposes that artificial intelligence should include consistency on identification of external emotions and emotional expression, processing of ontological emotions and external emotions, integration of internal and external emotions and generation of proprioceptive emotions.

Digital suffering: why it’s a problem and how to prevent it - Saad, Bradford; Bradley, Adam (Inquiry, 2022)
As ever more advanced digital systems are created, it becomes increasingly likely that some of these systems will be digital minds, i.e. digital subjects of experience. With digital minds comes the risk of digital suffering. The problem of digital suffering is that of mitigating this risk. We argue that the problem of digital suffering is a high stakes moral problem and that formidable epistemic obstacles stand in the way of solving it. We then propose a strategy for solving it: Access Monitor Prevent (AMP). AMP uses a ‘dancing qualia’ argument to link the functional states of certain digital systems to their experiences—this yields epistemic access to digital minds. With that access, we can prevent digital suffering by only creating advanced digital systems that we have such access to, monitoring their functional profiles, and preventing them from entering states with functional markers of suffering. After introducing and motivating AMP, we confront limitations it faces and identify some options for overcoming them. We argue that AMP fits especially well with—and so provides a moral reason to prioritize—one approach to creating such systems: whole brain emulation. We also contend that taking other paths to digital minds would be morally risky.

Multidisciplinary Intersections on Artificial-Human Vividness: Phenomenology, Representation, and the Brain - Molokopoy, Violetta; D’Angiulli, Amedeo (Brain Sciences, 2022)
This article will explore the expressivity and tractability of vividness, as viewed from the interdisciplinary perspective of the cognitive sciences, including the sub-disciplines of artificial intelligence, cognitive psychology, neuroscience, and phenomenology. Following the precursor work by Benussi in experimental phenomenology, seminal papers by David Marks in psychology and, later, Hector Levesque in computer science, a substantial part of the discussion has been around a symbolic approach to the concept of vividness. At the same time, a similar concept linked to semantic memory, imagery, and mental models has had a long history in cognitive psychology, with new emerging links to cognitive neuroscience. More recently, there is a push towards neural-symbolic representations which allows room for the integration of brain models of vividness to a symbolic concept of vividness. Such works lead to question the phenomenology of vividness in the context of consciousness, and the related ethical concerns. The purpose of this paper is to review the state of the art, advances, and further potential developments of artificial-human vividness while laying the ground for a shared conceptual platform for dialogue, communication, and debate across all the relevant sub-disciplines. Within such context, an important goal of the paper is to define the crucial role of vividness in grounding simulation and modeling within the psychology (and neuroscience) of human reasoning.

Trust, Ethics, Consciousness, and Artificial Intelligence - O'Grady, Katherine L.; Harbour, Steven D.; Abballe, Ashlie R.; Cohen, Kelly (2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC), 2022)
As artificial intelligence (AI) continues to proliferate across manufacturing, economic, medical, aerospace, transportation, and social realms, ethical guidelines must be established to not only protect humans at the mercy of automated decision making, but also autonomous agents themselves, should they become conscious. While AI appears "smart" to the public, and may outperform humans on specific tasks, the truth is that today’s AI lacks insight beyond the restricted scope of problems to which it has been tasked. Without context, AI is effectively incapable of comprehending the true nature of what it does and is oblivious to the reverberations it may cause in the real world should it err in prediction. Despite this, future AI may be equipped with enough sensors and neural processing capacity to acquire a dynamic cognizance more akin to humans. If this materializes, will autonomous agents question their own position in this world? One must entertain the possibility that this is not merely hypothetical but may, in fact, be imminent if humanity succeeds in creating artificial general intelligence (AGI).If autonomous agents with the capacity for artificial consciousness are delegated grueling tasks, outcomes could mirror the plight of exploited workers, result in retaliation, failure to comply, alternative objectives, or breakdown of human-autonomy teams. It will be critical to decide how and in which contexts various agents should be utilized. Additionally, delineating the meaning of trust and ethical consideration between humans and machines is problematic because descriptions of trust and ethics have only been detailed in human terms. This means autonomous agents will be subject to anthropomorphism, but robots are not humans, and their experience of trust and ethics might be markedly distinct from humans. Ideally speaking, to fully entrust a machine with human-centered tasks, one must believe that such an entity is reliable, competent, has the appropriate priorities.

Augmenting Human Selves Through Artificial Agents – Lessons From the Brain - Northoff, Georg; Fraser, Maia; Griffiths, John; Pinotsis, Dimitris A.; Panangaden, Prakash; Moran, Rosalyn; Friston, Karl (Frontiers in Computational Neuroscience, 2022)
Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI – but typically these tasks do not target higher-level human cognitive abilities, such as consciousness or morality; these are left to the realm of so-called “strong AI” or “artificial consciousness.” In this paper, we focus on how a machine can augment humans rather than do what they do, and we extend this beyond AGI-style tasks to augmenting peculiarly personal human capacities, such as wellbeing and morality. We base this proposal on associating such capacities with the “self,” which we define as the “environment-agent nexus”; namely, a fine-tuned interaction of brain with environment in all its relevant variables. We consider richly adaptive architectures that have the potential to implement this interaction by taking lessons from the brain. In particular, we suggest conjoining the free energy principle (FEP) with the dynamic temporo-spatial (TSD) view of neuro-mental processes. Our proposed integration of FEP and TSD – in the implementation of artificial agents – offers a novel, expressive, and explainable way for artificial agents to adapt to different environmental contexts. The targeted applications are broad: from adaptive intelligence augmenting agents (IA’s) that assist psychiatric self-regulation to environmental disaster prediction and personal assistants. This reflects the central role of the mind and moral decision-making in most of what we do as humans.

A blueprint for conscious machines - Oliveira, Arlindo L. (Proceedings of the National Academy of Sciences, 2022)

AIT foundations of structured experience - Ruffini, Giulio; Lopez-Sola, Edmundo (2022)
We present a unifying framework to study consciousness based on algorithmic information theory (AIT). We take as a premise that ``there is experience'' and focus on the requirements for structured experience (S)--- the spatial, temporal, and conceptual organization of our first-person experience of the world and of ourselves as agents in it. Our starting point is the insight that access to good models---succinct and accurate generative programs of world data---is crucial for homeostasis and survival. We hypothesize that the successful comparison of such models with data provides the structure to experience. Building on the concept of Kolmogorov complexity, we can associate the qualitative aspects of S with the algorithmic features of the model, including its length, which reflects the structure discovered in the data. Moreover, a modeling system tracking structured data will display dimensionality reduction and criticality features that can be used empirically to quantify the structure of the program run by the agent.  KT provides a consistent framework to define the concepts of life and agent and allows for the comparison between artificial agents and S-reporting humans to provide an educated guess about agent experience.  A first challenge is to show that a human agent has S to the extent they run encompassing and compressive models tracking world data. For this, we propose to study the relation between the structure of neurophenomenological,  physiological, and behavioral data. The second is to endow artificial agents with the means to discover good models and study their internal states and behavior. We relate the algorithmic framework to other theories of consciousness and discuss some of its epistemological, philosophical, and ethical aspects.

Consciousness and Rationality: The Lesson from Artificial Intelligence - Woodward, Philip (Journal of Consciousness Studies, 2022)
I review three problems that have historically motivated pessimism about artificial intelligence: (1) the problem of consciousness, according to which artificial systems lack the conscious oversight that characterizes intelligent agents; (2) the problem of global relevance, according to which artificial systems cannot solve fully general theoretical and practical problems; (3) the problem of semantic irrelevance, according to which artificial systems cannot be guided by semantic comprehension. I connect the dots between all three problems by drawing attention to non-syntactic inferences — inferences that are made on the basis of insight into the rational relationships among thought-contents. Consciousness alone affords such insight, I argue, and such insight alone confers positive epistemic status on the execution of these inferences. Only when artificial systems can execute inferences that are rationally guided by phenomenally conscious states will such systems count as intelligent in a literal sense.

Panpsychism and AI consciousness - Arvan, Marcus; Maley, Corey J. (Synthese, 2022)
This article argues that if panpsychism is true, then there are grounds for thinking that digitally-based artificial intelligence (AI) may be incapable of having coherent macrophenomenal conscious experiences. Section 1 briefly surveys research indicating that neural function and phenomenal consciousness may be both analog in nature. We show that physical and phenomenal magnitudes—such as rates of neural firing and the phenomenally experienced loudness of sounds—appear to covary monotonically with the physical stimuli they represent, forming the basis for an analog relationship between the three. Section 2 then argues that if this is true and micropsychism—the panpsychist view that phenomenal consciousness or its precursors exist at a microphysical level of reality—is also true, then human brains must somehow manipulate fundamental microphysical-phenomenal magnitudes in an analog manner that renders them phenomenally coherent at a macro level. However, Sect. 3 argues that because digital computation abstracts away from microphysical-phenomenal magnitudes—representing cognitive functions non-monotonically in terms of digits (such as ones and zeros)—digital computation may be inherently incapable of realizing coherent macroconscious experience. Thus, if panpsychism is true, digital AI may be incapable of achieving phenomenal coherence. Finally, Sect. 4 briefly examines our argument’s implications for Tononi’s Integrated Information Theory (IIT) theory of consciousness, which we contend may need to be supplanted by a theory of macroconsciousness as analog microphysical-phenomenal information integration.
Keywords: Analog; Artificial intelligence; Computation; Consciousness; Digital; Panpsychism

From Turing to Conscious Machines - Aleksander, Igor (Philosophies, 2022)
In the period between Turing’s 1950 “Computing Machinery and Intelligence” and the current considerable public exposure to the term “artificial intelligence (AI)”, Turing’s question “Can a machine think?” has become a topic of daily debate in the media, the home, and, indeed, the pub. However, “Can a machine think?” is sliding towards a more controversial issue: “Can a machine be conscious?” Of course, the two issues are linked. It is held here that consciousness is a pre-requisite to thought. In Turing’s imitation game, a conscious human player is replaced by a machine, which, in the first place, is assumed not to be conscious, and which may fool an interlocutor, as consciousness cannot be perceived from an individual’s speech or action. Here, the developing paradigm of machine consciousness is examined and combined with an extant analysis of living consciousness to argue that a conscious machine is feasible, and capable of thinking. The route to this utilizes learning in a “neural state machine”, which brings into play Turing’s view of neural “unorganized” machines. The conclusion is that a machine of the “unorganized” kind could have an artificial form of consciousness that resembles the natural form and that throws some light on its nature.

A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine - Blum, Lenore; Blum, Manuel (Proceedings of the National Academy of Sciences, 2022)
This paper examines consciousness from the perspective of theoretical computer science (TCS), a branch of mathematics concerned with understanding the underlying principles of computation and complexity, including the implications and surprising consequences of resource limitations. We propose a formal TCS model, the Conscious Turing Machine (CTM). The CTM is influenced by Alan Turing's simple yet powerful model of computation, the Turing machine (TM), and by the global workspace theory (GWT) of consciousness originated by cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, Jean-Pierre Changeux, George Mashour, and others. Phenomena generally associated with consciousness, such as blindsight, inattentional blindness, change blindness, dream creation, and free will, are considered. Explanations derived from the model draw confirmation from consistencies at a high level, well above the level of neurons, with the cognitive neuroscience literature.

Does Machine Understanding Require Consciousness? - Pepperell, Robert (Frontiers in Systems Neuroscience, 2022)
This article addresses the question of whether machine understanding requires consciousness. Some researchers in the field of machine understanding have argued that it is not necessary for computers to be conscious as long as they can match or exceed human performance in certain tasks. But despite the remarkable recent success of machine learning systems in areas such as natural language processing and image classification, important questions remain about their limited performance and about whether their cognitive abilities entail genuine understanding or are the product of spurious correlations. Here I draw a distinction between natural, artificial, and machine understanding. I analyse some concrete examples of natural understanding and show that although it shares properties with the artificial understanding implemented in current machine learning systems it also has some essential differences, the main one being that natural understanding in humans entails consciousness. Moreover, evidence from psychology and neurobiology suggests that it is this capacity for consciousness that, in part at least, explains for the superior performance of humans in some cognitive tasks and may also account for the authenticity of semantic processing that seems to be the hallmark of natural understanding. I propose a hypothesis that might help to explain why consciousness is important to understanding. In closing, I suggest that progress toward implementing human-like understanding in machines—machine understanding—may benefit from a naturalistic approach in which natural processes are modelled as closely as possible in mechanical substrates.

Artificial Intelligence, Cognitive Robotics and Nature of Consciousness - Singh, Shweta; Chaudhary, Devansh; Gupta, Amar Deep; Prakash Lohani, Bhanu; Kushwaha, Pradeep Kumar; Bibhu, Vimal (2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), 2022)
These are some interesting times to be alive as humans and as the most versatile curious layer "The Homo Sapiens" of this pale blue planet "Earth" that we all call home in this large ever expanding sea of the cosmos, we an unknown race just like a particle of chili flakes in pizza, we are timid in our behavior and always chewing more than we can actually swallow ---. There is something about to happen, well guess what it has already started and this time it will change everything. What is that one trait that defines and defies "Humans" from all the other species and we all take proud in that is "Intelligence and Consciousness" but the tide is shifting and a new traveller is coming to the shores which will change our Alphabets from "A -- Z" to "A -- I" and now welcome to the future "The Future of AI and Robotics" where questions like "How Far is too Far" will be answered but for now the "Answer of this abstract is Artificial Intelligence and cognitive robotics". AI has its applications in almost all the fields today, Medicine and Art to Space Architects and Cognitive Humanoid robots the most visible yet deceptive the Mobile phones all is AI. The story is long and all we can hope is that it will be a happy one ----.The AI is actually peeping in our life’s much faster than many of the eminent individuals predicted, from healing through AI to have a digital interaction with Avatar of yourself with the help of AI, the Cognitive robotics to cognitive embodiment all these have never been done in the history of mankind, we are in the dawn of a new age "The Age of AI" where the most important tool for survival will be the cooperation of "Human Intelligence and Digital Consciousness." This paper is a nutshell biography of Artificial Intelligence, its fundamentals, concise history and the road ahead with all the applications of this fascinating term which we all know as Artificial Intelligence.

3 The Challenge of (Self-)Consciousness: Kant, Artificial Intelligence and Sense-Making - Baiasu, Sorin (Kant and Artificial Intelligence, 2022)
How do we make sense of the countless pieces of information flowing to us from the environment? This question, sometimes called the Problem of Representation, is one of the most significant problems in cognitive science. Some pioneering and important work in the attempt to address the problem of representation was produced with the help of Kant’s philosophy. In particular, the suggestion was that, by analogy with Kant’s distinction between sensibility and the understanding, we can distinguish between high- and low-level perception, and then focus on the step from high-level perception to abstract cognitive processes of sense-making. This was possible through a simplification of the input provided by low-level perception (to be reduced, for instance, to a string of letters), which the computer programme was supposed to ‘understand’. Most recently, a closer look at Kant’s model of the mind led to a breakthrough in the attempt to build programmes for such verbal reasoning tasks: these kinds of software or ‘Kantian machines’ seemed able to achieve human-level performance for verbal reasoning tasks. Yet, the claim has sometimes been stronger, namely, that some such programmes not only compete with human cognitive agents, but themselves represent cognitive agents. The focus of my paper is on this claim; I argue that it is unwarranted, but that its critical investigation may lead to further avenues for how to pursue the project of creating artificial intelligence.

Douglas Hofstadter's Gödelian Philosophy of Mind - Nenu, Theodor (Journal of Artificial Intelligence and Consciousness, 2022)
Hofstadter [1979, 2007] offered a novel Gödelian proposal which purported to reconcile the apparently contradictory theses that (1) we can talk, in a non-trivial way, of mental causation being a real phenomenon and that (2) mental activity is ultimately grounded in low-level rule-governed neural processes. In this paper, we critically investigate Hofstadter’s analogical appeals to Gödel’s [1931] First Incompleteness Theorem, whose “diagonal” proof supposedly contains the key ideas required for understanding both consciousness and mental causation. We maintain that bringing sophisticated results from Mathematical Logic into play cannot furnish insights which would otherwise be unavailable. Lastly, we conclude that there are simply too many weighty details left unfilled in Hofstadter’s proposal. These really need to be fleshed out before we can even hope to say that our understanding of classical mind-body problems has been advanced through metamathematical parallels with Gödel’s work.

WHAT IS IT LIKE TO BE AN ARTIFICIAL INTELLIGENCE? NAGEL’S VIEW FROM NOWHERE AND ARTIFICIAL INTELLIGENCE AS SUBJECT OF LAW - Divino, Sthéfano Bruno Santos; Magalhães, Rodrigo Almeida (Direito Público, 2022)
This paper has as its research problem the following question: what is it like to be an artificial intelligence? It aims to critically analyze the epistemological and semantic aspects developed by Thomas Nagel in What is it like to be a bat and The View from Nowhere, demonstrating the relationship between physicalism and subjectivity and its application to artificially intelligent beings.  We chose to approach these two works because of the author's importance in analytical philosophy and the approach to consciousness. The analysis shows that the defense of artificial intelligence as a subject of law is intrinsically based on physicalism. However, in refuting it, Nagel does not offer an alternative outside the scope of dualism. Thus, the Procedural Theory of the Subject of Law is developed with stages of emancipation of the being against the law. As a result, it is verified that the reductive physicalist vision is insufficient to substantiate the condition of the subject of law of an artificial intelligence as a legal and political being in the social order. However, if the three stages of its formation (emancipation, interspecies recognition, and personification) are observed, the possibility of achieving the condition under analysis is assumed. It is concluded that it is unverifiable to know what it is like to be an artificial intelligence. In the current scientific stage, an artificially intelligent being cannot (yet) be considered a subject of law, under penalty of characterization of instrumentalism. The methodology of integrated, analytical, deductive, and bibliographic research is used to obtain these results and conclusions.

The “Slicing Problem” for Computational Theories of Consciousness - Gómez-Emilsson, Andrés; Percy, Chris (Open Philosophy, 2022)
The “Slicing Problem” is a thought experiment that raises questions for substrate-neutral computational theories of consciousness, including those that specify a certain causal structure for the computation like Integrated Information Theory. The thought experiment uses water-based logic gates to construct a computer in a way that permits cleanly slicing each gate and connection in half, creating two identical computers each instantiating the same computation. The slicing can be reversed and repeated via an on/off switch, without changing the amount of matter in the system. The question is what do different computational theories of consciousness believe is happening to the number and nature of individual conscious units as this switch is toggled. Under a token interpretation, there are now two discrete conscious entities; under a type interpretation, there may remain only one. Both interpretations lead to different implications depending on the adopted theoretical stance. Any route taken either allows mechanisms for “consciousness-multiplying exploits” or requires ambiguous boundaries between conscious entities, raising philosophical and ethical questions for theorists to consider. We discuss resolutions under different theories of consciousness for those unwilling to accept consciousness-multiplying exploits. In particular, we specify three features that may help promising physicalist theories to navigate such thought experiments.
Keywords: IIT; Slicing Problem; binding problem; causal structure; computationalism; functionalism; philosophy of mind; physicalism; theories of consciousness; thought experiment

Cybermedia: Explorations in Science, Sound, and Vision - Dibben, Nicola; Perrott, Lisa; Zuberi, Nabeel; Jeffery, Alex; Mangaoang, Áine; Koepnick, Lutz (Bloomsbury Publishing Inc, 2022)
We’re experiencing a time when digital technologies and advances in artificial intelligence, robotics, and big data are redefining what it means to be human. How do these advancements affect contemporary media and music? This collection traces how media, with a focus on sound and image, engages with these new technologies. It bridges the gap between science and the humanities by pairing humanists’ close readings of contemporary media with scientists’ discussions of the science and math that inform them. This text includes contributions by established and emerging scholars performing across-the-aisle research on new technologies, exploring topics such as facial and gait recognition; EEG and audiovisual materials; surveillance; and sound and images in relation to questions of sexual identity, race, ethnicity, disability, and class and includes examples from a range of films and TV shows including Blade Runner, Black Mirror, Mr. Robot, Morgan, Ex Machina, and Westworld. Through a variety of critical, theoretical, proprioceptive, and speculative lenses, the collection facilitates interdisciplinary thinking and collaboration and provides readers with ways of responding to these new technologies.

Conscious Empathic AI in Service - Esmaeilzadeh, Hadi; Vaezi, Reza (Journal of Service Research, 2022)
Recent advances in artificial intelligence (AI) have achieved human-scale speed and accuracy for classification tasks. Current systems do not need to be conscious to recognize patterns and classify them. However, for AI to advance to the next level, it needs to develop capabilities such as metathinking, creativity, and empathy. We contend that such a paradigm shift is possible through a fundamental change in the state of artificial intelligence toward consciousness, similar to what took place for humans through the process of natural selection and evolution. To that end, we propose that consciousness in AI is an emergent phenomenon that primordially appears when two machines cocreate their own language through which they can recall and communicate their internal state of time-varying symbol manipulation. Because, in our view, consciousness arises from the communication of inner states, it leads to empathy. We then provide a link between the empathic quality of machines and better service outcomes associated with empathic human agents that can also lead to accountability in AI services.

Qualia, Consciousness and Artificial Intelligence - Haikonen, Pentti O. (Journal of Artificial Intelligence and Consciousness, 2022)
It is noted that there are many different definitions of and views about qualia, and this makes qualia into a vague concept without much theoretical and constructive value. Here, qualia are redefined in a more general way. It is argued that the redefined qualia will be essential to the mind–body problem, the problem of consciousness and also to the symbol grounding problem, which is inherent in physical symbol systems. Then, it is argued that the redefined qualia are necessary for Artificial Intelligence systems for the operation with meanings. Finally, it is proposed that robots with qualia may be conscious.

Artificial Consciousness - Hashim, Hashim Talib; Ramadhan, Mustafa Ahmed (The Psychology of Consciousness: Theory and Practice, 2022)
An area related to artificial intelligence and computational robotics is artificial consciousness, also known as computer consciousness or virtual consciousness. The artificial consciousness theory aims to establish what will have to be synthesized in an engineered artifact to find consciousness.

A Design of Global Workspace Model with Attention: Simulations of Attentional Blink and Lag-1 Sparing - Huang, Wenjie; Chella, Antonio; Cangelosi, Angelo (Journal of Artificial Intelligence and Consciousness, 2022)
There are many developed theories and implemented artificial systems in the area of machine consciousness, while none has achieved that. For a possible approach, we are interested in implementing a system by integrating different theories. Along this way, this paper proposes a model based on the global workspace theory and attention mechanism, and providing a fundamental framework for our future work. To examine this model, two experiments are conducted. The first one demonstrates the agent’s ability to shift attention over multiple stimuli, which accounts for the dynamics of conscious content. Another experiment of simulations of attentional blink and lag-1 sparing, which are two well-studied effects in psychology and neuroscience of attention and consciousness, aims to justify the agent’s compatibility with human brains. In summary, the main contributions of this paper are (1) Adaptation of the global workspace framework by separated workspace nodes, reducing unnecessary computation but retaining the potential of global availability; (2) Embedding attention mechanism into the global workspace framework as the competition mechanism for the consciousness access; (3) Proposing a synchronization mechanism in the global workspace for supporting lag-1 sparing effect, retaining the attentional blink effect.

On the link between conscious function and general intelligence in humans and machines - Juliani, Arthur; Arulkumaran, Kai; Sasai, Shuntaro; Kanai, Ryota (arXiv, 2022)
In popular media, there is often a connection drawn between the advent of awareness in artificial agents and those same agents simultaneously achieving human or superhuman level intelligence. In this work, we explore the validity and potential application of this seemingly intuitive link between consciousness and intelligence. We do so by examining the cognitive abilities associated with three contemporary theories of conscious function: Global Workspace Theory (GWT), Information Generation Theory (IGT), and Attention Schema Theory (AST). We find that all three theories specifically relate conscious function to some aspect of domain-general intelligence in humans. With this insight, we turn to the field of Artificial Intelligence (AI) and find that, while still far from demonstrating general intelligence, many state-of-the-art deep learning methods have begun to incorporate key aspects of each of the three functional theories. Having identified this trend, we use the motivating example of mental time travel in humans to propose ways in which insights from each of the three theories may be combined into a single unified and implementable model. Given that it is made possible by cognitive abilities underlying each of the three functional theories, artificial agents capable of mental time travel would not only possess greater general intelligence than current approaches, but also be more consistent with our current understanding of the functional role of consciousness in humans, thus making it a promising near-term goal for AI research.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences; Neural and Evolutionary Computing (cs.NE)

Artificial Intelligence and Human Consciousness - K, Srikanth (SSRN Electronic Journal, 2022)
The purpose of this article is to throw some light on aspects of Human consciousness and Artificial Intelligence(AI). Consciousness is a unique aspect which humans possess which makes them the superior beings of the earth. Human Consciousness and Artificial intelligence are two complex entities which can make it more complicated for AI develop consciousness. This article introduces topics such as Cognitive abilities and ethics. Ethics are confused with morality but morality is a part of ethics. Ethics is a theoretical concept built on perception and what the society thinks is right or wrong. The article also highlights if Artificial intelligence can develop consciousness as complex as that of Human consciousness. The article also focuses on whether Artificial intelligence can have cognitive abilities. Also if AI can have ethics.

Artificial Consciousness and Choosing (Towards Conscious Choice Machines) - Kulkarni, Parag (Choice Computing: Machine Learning and Systemic Economics for Choosing, 2022)
Consciousness is all about internal and external existence that is felt and reflected through actions. Self-existence is about feeling your own existence and is also associated with freedom [1, 2]. It is about the feeling and awareness that the individual exists and can do different activities as per will. These activities include activities like choosingChoosing, attaining certain objectives and fighting for survival.

Meta-learning, social cognition and consciousness in brains and machines - Langdon, Angela; Botvinick, Matthew; Nakahara, Hiroyuki; Tanaka, Keiji; Matsumoto, Masayuki; Kanai, Ryota (Neural Networks, 2022)
The intersection between neuroscience and artificial intelligence (AI) research has created synergistic effects in both fields. While neuroscientific discoveries have inspired the development of AI architectures, new ideas and algorithms from AI research have produced new ways to study brain mechanisms. A well-known example is the case of reinforcement learning (RL), which has stimulated neuroscience research on how animals learn to adjust their behavior to maximize reward. In this review article, we cover recent collaborative work between the two fields in the context of meta-learning and its extension to social cognition and consciousness. Meta-learning refers to the ability to learn how to learn, such as learning to adjust hyperparameters of existing learning algorithms and how to use existing models and knowledge to efficiently solve new tasks. This meta-learning capability is important for making existing AI systems more adaptive and flexible to efficiently solve new tasks. Since this is one of the areas where there is a gap between human performance and current AI systems, successful collaboration should produce new ideas and progress. Starting from the role of RL algorithms in driving neuroscience, we discuss recent developments in deep RL applied to modeling prefrontal cortex functions. Even from a broader perspective, we discuss the similarities and differences between social cognition and meta-learning, and finally conclude with speculations on the potential links between intelligence as endowed by model-based RL and consciousness. For future work we highlight data efficiency, autonomy and intrinsic motivation as key research areas for advancing both fields. Questions answered in this article BetaPowered by GenAI This is generative AI content and the quality may vary. Learn more . How can meta-learning facilitate the development of more general forms of artificial intelligence? What recent advancements have been made in integrating meta-learning into deep Reinforcement Learning (RL)? How do model-based Reinforcement Learning algorithms facilitate meta-learning? What computational and empirical results are relevant to meta-learning in both artificial intelligence and the brain? What are the implications of brain-inspired model-based Reinforcement Learning for artificial learning systems?

Brainish: Formalizing A Multimodal Language for Intelligence and Consciousness - Liang, Paul Pu (arXiv, 2022)
Having a rich multimodal inner language is an important component of human intelligence that enables several necessary core cognitive functions such as multimodal prediction, translation, and generation. Building upon the Conscious Turing Machine (CTM), a machine model for consciousness proposed by Blum and Blum (2021), we describe the desiderata of a multimodal language called Brainish, comprising words, images, audio, and sensations combined in representations that the CTM's processors use to communicate with each other. We define the syntax and semantics of Brainish before operationalizing this language through the lens of multimodal artificial intelligence, a vibrant research area studying the computational tools necessary for processing and relating information from heterogeneous signals. Our general framework for learning Brainish involves designing (1) unimodal encoders to segment and represent unimodal data, (2) a coordinated representation space that relates and composes unimodal features to derive holistic meaning across multimodal inputs, and (3) decoders to map multimodal representations into predictions (for fusion) or raw data (for translation or generation). Through discussing how Brainish is crucial for communication and coordination in order to achieve consciousness in the CTM, and by implementing a simple version of Brainish and evaluating its capability of demonstrating intelligence on multimodal prediction and retrieval tasks on several real-world image, text, and audio datasets, we argue that such an inner language will be important for advances in machine models of intelligence and consciousness.
Keywords: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); FOS: Computer and information sciences; Machine Learning (cs.LG)

LESSONS FROM THE QUEST FOR ARTIFICIAL CONSCIOUSNESS: THE EMERGENCE CRITERION, INSIGHT‐ORIENTED AI, AND IMAGO DEI - Lumbreras, Sara (Zygon®, 2022)
There are several lessons that can already be drawn from the current research programs on strong AI and building conscious machines, even if they arguably have not produced fruits yet. The first one is that functionalist approaches to consciousness do not account for the key importance of subjective experience and can be easily confounded by the way in which algorithms work and succeed. Authenticity and emergence are key concepts that can be useful in discerning valid approaches versus invalid ones and can clarify instances where algorithms are considered conscious, such as Sophia or LaMDA. Subjectivity and embeddedness become key notions that should also lead us to re‐examine the ethics of decision delegation. In addition, the focus on subjective experience shifts what is relevant in our understanding of ourselves as human beings and as an image of God, namely, in de‐emphasizing intellectuality in favor of experience and contemplation over action.

Everything and More: The Prospects of Whole Brain Emulation - Mandelbaum, Eric (Journal of Philosophy, 2022)

On the independence between phenomenal consciousness and computational intelligence - Merchán, Eduardo C. Garrido; Lumbreras, Sara (arXiv, 2022)
Consciousness and intelligence are properties commonly understood as dependent by folk psychology and society in general. The term artificial intelligence and the kind of problems that it managed to solve in the recent years has been shown as an argument to establish that machines experience some sort of consciousness. Following the analogy of Russell, if a machine is able to do what a conscious human being does, the likelihood that the machine is conscious increases. However, the social implications of this analogy are catastrophic. Concretely, if rights are given to entities that can solve the kind of problems that a neurotypical person can, does the machine have potentially more rights that a person that has a disability? For example, the autistic syndrome disorder spectrum can make a person unable to solve the kind of problems that a machine solves. We believe that the obvious answer is no, as problem solving does not imply consciousness. Consequently, we will argue in this paper how phenomenal consciousness and, at least, computational intelligence are independent and why machines do not possess phenomenal consciousness, although they can potentially develop a higher computational intelligence that human beings. In order to do so, we try to formulate an objective measure of computational intelligence and study how it presents in human beings, animals and machines. Analogously, we study phenomenal consciousness as a dichotomous variable and how it is distributed in humans, animals and machines. As phenomenal consciousness and computational intelligence are independent, this fact has critical implications for society that we also analyze in this work.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

Systems-Theoretic Exploration of the Learning of Meaning from Complex Language Spaces through the Transformer Model of Artificial Intelligence, with Implications for Consciousness Studies - Mukherjee, Debaprasad (SSRN Electronic Journal, 2022)
The Transformer artificial intelligence model is one of the most accurate models to extract the meaning/semantics from sets of symbolic sequences of various lengths, including long sequences. These models transform the language spaces as per long and short-distance relationships among units of the language. These models thus minimize some aspects of human comprehension of the world. To frame a generalized theory of identification and generation of meaning in human thought, the transformer model needs to be understood in the context of generalized systems theory, such that other equivalent models can be discovered, compared and selected to converge on the base model of meaning identification and discovery aspect of the philosophy of knowledge or epistemology. This paper explores the relationships of the transformer model and its various component parts, processes and the phenomena to some critical aspects of generalized systems theory such as cognition, symmetry & equivalence, holons, emergence, identifiability, system spaces and system universe, reconstructability, equilibriums & oscillations, scaling, polystability, ontogeny, algedonic loops, heterarchy, holarchy, homeorhesis, isomorphism, homeostasis, attractors, equifinality, nesting, parallelization, loops, causal structure, transformations, feedbacks, encodings, and information complexity.

Consciousness and the Brain: New Research Horizons - Okonskaya, Natalia K.; Barg, Oleg A.; Nacharova, Margarita A.; Ermakov, Mikhail A. (Springer International Publishing, 2022)
The problem of the origin of consciousness, on the one hand, and the problem of global challenges to humanity due to the intellectualization of the technical re-equipment of the means of production are among the most pressing problems of transdisciplinary science. Modern physicalism, denying consciousness, qualia, and equating artificial intelligence with the mentality of man wrongfully integrates the Subject with high technology. The agnosticism and physicalism of analytic philosophy considers thought to be material and is able to recognize (in perspective) the human virtues of honor, freedom, and conscience for the artificial intellect. In this way, society transfers power over the crises resulting from the development of science, towards the development of social technology. The main task of this article is to make evident again to everyone the idea of the existence of personality as a form of sociality in two opposing worlds at once - the material and the ideal. Including using the achievements of neurobiology in the knowledge of the functional asymmetry of the human brain, which is absent in the higher animals and is associated with the emergence of consciousness.
Keywords: Analytic philosophy of mind; Artificial intellect; Asymmetry of the world; Brain; Consciousness; Emergence of consciousness; Functional asymmetry of the brain; Language-consciousness problem; Mind-body problem; Technologization of man

A Cognitive Architecture for Machine Consciousness and Artificial Superintelligence: Thought Is Structured by the Iterative Updating of Working Memory - Reser, Jared Edward (arXiv, 2022)
This article provides an analytical framework for how to simulate human-like thought processes within a computer. It describes how attention and memory should be structured, updated, and utilized to search for associative additions to the stream of thought. The focus is on replicating the dynamics of the mammalian working memory system, which features two forms of persistent activity: sustained firing (preserving information on the order of seconds) and synaptic potentiation (preserving information from minutes to hours). The article uses a series of figures to systematically demonstrate how the iterative updating of these working memory stores provides functional organization to behavior, cognition, and awareness. In a machine learning implementation, these two memory stores should be updated continuously and in an iterative fashion. This means each state should preserve a proportion of the coactive representations from the state before it (where each representation is an ensemble of neural network nodes). This makes each state a revised iteration of the preceding state and causes successive configurations to overlap and blend with respect to the information they contain. Thus, the set of concepts in working memory will evolve gradually and incrementally over time. Transitions between states happen as persistent activity spreads activation energy throughout the hierarchical network, searching long-term memory for the most appropriate representation to be added to the global workspace. The result is a chain of associatively linked intermediate states capable of advancing toward a solution or goal. Iterative updating is conceptualized here as an information processing strategy, a model of working memory, a theory of consciousness, and an algorithm for designing and programming artificial intelligence (AI, AGI, and ASI).
Keywords: Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV); FOS: Biological sciences; FOS: Computer and information sciences; Neurons and Cognition (q-bio.NC)

Could IBM’s Deep Blue Chess Program Feel Triumphant? - Sood, Suraj (Advances in Information and Communication, 2022)
In this article, it is taken for granted that fully-human artificial intelligence—a term used to denote artificial life that is, in principle, more human than strong AI would be—must possess operational faculties for consciousness and selfhood. After clarifying relevant questions surrounding the interested socio-psychological phenomena, progress in animal and humanoid robotics is summarized. The aforementioned topics within philosophy and the social sciences are reviewed, noting their relevant overlaps with recent developments in cognitive and computer sciences. My working assumption is that the avowed conclusion of human AI cannot currently be written off as impossible and should therefore be critically engaged (the intent is to engage with humanoid robotics’ capabilities and features in relation to the present state of knowledge regarding the psychological phenomena discussed). It is argued that for human AI to fully succeed as a discipline, the discussed psychological notions as we understand and experience them must be further elucidated and adequately accounted for by AI research programs.

How a non-conscious robot could be an agent with capacity for morally responsible behaviour - Søvik, Atle Ottesen (AI and Ethics, 2022)
People have different opinions about which conditions robots would need to fulfil—and for what reasons—to be moral agents. Standardists hold that specific internal states (like rationality, free will or phenomenal consciousness) are necessary in artificial agents, and robots are thus not moral agents since they lack these internal states. Functionalists hold that what matters are certain behaviours and reactions—independent of what the internal states may be—implying that robots can be moral agents as long as the behaviour is adequate. This article defends a standardist view in the sense that the internal states are what matters for determining the moral agency of the robot, but it will be unique in being an internalist theory defending a large degree of robot responsibility, even though humans, but not robots, are taken to have phenomenal consciousness. This view is based on an event-causal libertarian theory of free will and a revisionist theory of responsibility, which combined explain how free will and responsibility can come in degrees. This is meant to be a middle position between typical compatibilist and libertarian views, securing the strengths of both sides. The theories are then applied to robots, making it possible to be quite precise about what it means that robots can have a certain degree of moral responsibility, and why. Defending this libertarian form of free will and responsibility then implies that non-conscious robots can have a stronger form of free will and responsibility than what is commonly defended in the literature on robot responsibility.

Forgetting the Bicentennial Man: Discussing Why Anthropocentric Frameworks of Consciousness Should be Avoided for Artificial Entities - Tait, Izak; Wang, Ziqi; O’Leary, Tahua; Corballis, Paul (Journal of Artificial Intelligence and Consciousness, 2022)
The established theories and frameworks on consciousness in the academic literature as related to artificial intelligence (AI), are rooted in anthropocentricism. Even those theories created intentionally for AI are based on the levels of consciousness as it is understood in humans primarily, and in other animals secondarily. This paper will discuss why such anthropocentric frameworks are built on unsecure foundations. We will do this by comparing the capacities and functions of human and AI cognitive architectures, discussing the ramifications and consequences of the behaviors that stem from these, and looking at the neurological conditions in humans that can give the most promising hints as to what a potential conscious AI entity would look like. The paper ends with a proposed solution for building a nonanthropocentric foundation of cognition that could lead toward a truly AI-focused framework of consciousness.

From Biological to Artificial Consciousness: Neuroscientific Insights and Progress - Watanabe, Masataka (The Frontiers Collection, 2022)
How does consciousness emerge from a brain that consists only of physical matter and electrical / chemical reactions? The deep mysteries of consciousness have plagued philosophers and scientists for thousands of years. This book approaches the problem through scientific studies that shed light on the neural mechanism of consciousness, and furthermore, delves into the possibility of artificial consciousness, a phenomenon that may ultimately solve the mystery. Finally, two key suggestions made in the book, namely, a method to test machine consciousness and a theory hypothesizing that consciousness emerges from a neural algorithm, reveal a novel and credible pathway to mind-uploading.The original Japanese version of this book has become a best-seller in popular neuroscience and has even led to a neurotech startup for mind-uploading.

Progress in Research on Implementing Machine Consciousness - Yamada, Kazunori D; Baladram, Samy; Lin, Fangzhou (Interdisciplinary Information Sciences, 2022)
Thus far, we have experienced three artificial intelligence (AI) booms. In the third one, we succeeded in developing AI that partially surpassed human capabilities. However, we are yet to develop AI that, like humans, can perform a series of cognitive processes. Consciousness built into devices is called machine consciousness. Related research has been conducted from two perspectives: studying machine consciousness as a tool to elucidate human consciousness and achieving the technological goal of furthering AI research with conscious AI. Herein, we survey the research conducted on machine consciousness from the second perspective. For AI to attain machine consciousness, its implementation must be evaluated. Therefore, we only surveyed attempts to implement consciousness as systems on devices. We collected research results in chronological order and found no breakthroughs that could deliver machine consciousness soon. Moreover, there is no method to evaluate whether an implemented machine consciousness system possesses consciousness, thus making it difficult to confirm the certainty of the implementation. This field of research is a new frontier. It is an exciting field with many discoveries expected in the future.

Artificial Consciousness and Artificial Personality - Yurasov, Andrey (Artificial societies, 2022)
The article analyzes the concepts of artificial personality and artificial consciousness, and shows the key difficulties of implementing projects to create such artificial intelligence systems. These difficulties are related to the following characteristics of artificial personality and artificial consciousness: 1) creativity and free will; 2) intentionality; 3) qualia; 4) first person perspective; 5) the passage of time in consciousness. The basic needs for an artificial personality (in the context of the development of natural and artificial intelligence) are indicated. Two directions of artificial personality formation are highlighted: 1) transformation of an artificial system into an artificial personality; 2) transformation of a person into an artificial personality.

Demystifying Artificial Consciousness – About Attributions, Black Swans, and Suffering Machines - Wendland, Karsten (Journal of AI Humanities, 2021)

Human Consciousness & Artificial Intelligence: Can AI Develop Human-Like Consciousness? Cognitive Abilities? What about Ethics? - Asodu, Abhishek Shetty (Social Science Research Network, 2021)
Consciousness is now what distinguishes humans from machines. This paper discusses artificial consciousness and how artificial general intelligence is progressing from current artificial intelligence. It also discusses human cognitive capacities, ethics, and how artificial intelligence may be used to supplement each of these. Several scientists discussed approaches for generating cognition in machines. This study presents scenarios that demonstrate how consciousness and ethics will play a significant role in future artificial intelligence. The impact of the consciousness and correlation with the AI cognitive abilities are discussed. The paper will also address the necessity of ethical norms in AI, particularly in modern self-driving cars. An overview of current Narrow AI capabilities will be provided, as well as discussion of present and future directions for Strong AI research. Can Strong AI become conscious? A few discussion points are provided.
Keywords: Artificial Consciousness; Artificial General Intelligence; Cognitive abilities.; Ethics AI; Human Consciousness

Consciousness: A Paradigm Towards Artificial General Intelligence - Chaudhry (Zenodo, 2021)
Consciousness nearly in all its elusive history is a convoluted notion, often misconstrued or not understood enough to cause a reproducible representation. With these odious assertions, this publication is opening the box of consciousness with deviation from commonly understood notion of consciousness. The proposed paradigm of consciousness approaches this issue with speculative and intuitive perspectives, essentially it is a precursor activity in hope to materialize the elusive artificial general intelligence, the true carrier of exceptional human intelligence and consciousness. This paper posits a counterbalance approach to the current paradigm of consciousness and as an alternate a radical theory of consciousness is presented. This attempt on the behavioral, structural and functional working of consciousness is kept pragmatic in the intractable universe of consciousness.
Keywords: Consciousness, Existence, Mind's Model of the World, Network of beings, Artificial general intelligence, Data driven approaches.

Could Humanoid Robots Become Conscious? - Zanou, Ayao Edoh (Social Science Research Network, 2021)
This article is an attempt at the “hard problem” of Consciousness. As the era of Artificial Intelligence is looming ahead, we are concerned about our future environment.  We define human Consciousness and medium Consciousness. We clarify the difference between the brain and the mind. We demonstrate how the brain creates the mind but must do so only in the presence of Consciousness. We define a person and delve into the frequency of personhood to finally answer whether machines could become conscious one day or not.
Keywords: Artificial Intelligence and their Sociability; Awareness; Brain and Mind; Hard Problem of Consciousness; Human Consciousness; Personhood; Pure Consciousness and Cosmic Consciousness

Bots and Beasts: What Makes Machines, Animals, and People Smart? - Thagard, Paul (The MIT Press, 2021)
An expert on the mind considers how animals and smart machines measure up to human intelligence. Octopuses can open jars to get food, and chimpanzees can plan for the future. An IBM computer named Watson won on Jeopardy! and Alexa knows our favorite songs. But do animals and smart machines really have intelligence comparable to that of humans? In Bots and Beasts, Paul Thagard looks at how computers (“bots”) and animals measure up to the minds of people, offering the first systematic comparison of intelligence across machines, animals, and humans. Thagard explains that human intelligence is more than IQ and encompasses such features as problem solving, decision making, and creativity. He uses a checklist of twenty characteristics of human intelligence to evaluate the smartest machines—including Watson, AlphaZero, virtual assistants, and self-driving cars—and the most intelligent animals—including octopuses, dogs, dolphins, bees, and chimpanzees. Neither a romantic enthusiast for nonhuman intelligence nor a skeptical killjoy, Thagard offers a clear assessment. He discusses hotly debated issues about animal intelligence concerning bacterial consciousness, fish pain, and dog jealousy. He evaluates the plausibility of achieving human-level artificial intelligence and considers ethical and policy issues. A full appreciation of human minds reveals that current bots and beasts fall far short of human capabilities.

Toward Self-Aware Machines: Insights of Causal Reasoning in Artificial Intelligence - Pelivani, Elis; Cico, Betim (2021 International Conference on Information Technologies (InfoTech), 2021)
This study was focused on reviewing several research articles related to various perspectives and significant recent developments of Artificial Intelligence (AI). The main goal of this review was to gain insight into the implications of causal reasoning models in artificial intelligence. This review analyses state-of-the-art research articles and evaluations of applications, techniques algorithms, and trends in the field of Artificial Intelligence. By presenting recent results, this study has a strong emphasis on fundamental aspects of causal reasoning, logic, and computational structures of Strong AI agents. Findings of this study outline the importance of implementing causal reasoning methods in AI systems in order to achieve in the future, a truly intelligent machine. We can conclude that causal reasoning provides an important approach to advancing our understanding of artificial consciousness. Extensive research is needed in the future to validate and evaluate different causal tools for supporting causal reasoning in AI.

The ascendancy of Consciousness on Artificial Intelligence with inevitable psychology. - Rathod, Diksha; Cirikonda, Himatesh (Journal of University of Shanghai for Science and Technology, 2021)
Talking about consciousness and Artificial Intelligence, like two sides of a coin, are seen together but are not together. When combined it becomes a mastery that can take over the world. Consciousness is still been not defined by any researcher or scientist. Heuristically, we know that Artificial Intelligence is booming and technology being ever fastest-growing field, but with this, there are many factors which are been neglected and can cause some drastic changes and severe problems to mankind. Thinking that Artificial Intelligence is not beyond humans, there are times where things are neglected but the fact that AI is showing prominent signs that it has become far more superior than what it has been trained and tested on. Often there are some series or patterns of outputs observed, which were not been trained to the machine but were formed by the algorithm matches might be difficult to understand for humans as well. This paper discusses the thoughts which are alive in everyone’s brain but are unanswered and are finding a path to reach out a standard solution. Aspects of society being the oldest of one, which was formed by humans. How will it be if the “SOCIETY” is seen in the world lead by the robots becoming dominant and ruling over humans? Can the consciousness which is still abstract or fugitively subjective in humans work similarly in robots as it is felt within us? If it ever will, Would humans live their lives with freedom? Or will it be minimal and not according to themselves but according to the robots? Is it right to expound it in one word as Singularity? As it is still an unknown entity but also a toss of ambiguity. Researchers are quite near to develop self-learning robots, but hidden patterns of them communicating amongst themselves speculate more perplexed theories which are making them more complex for scientists and researchers. Deep-down significantly knowing that things are moving in a direction which are casting the risk factors but also if you flip and see the other side, it shows the positive results and the growth of Intelligence which is helping each individual to grow in their way.

The neural correlates of consciousness under the free energy principle: From computational correlates to computational explanation - Wiese, Wanja; Friston, Karl J. (Philosophy and the Mind Sciences, 2021)
How can the free energy principle contribute to research on neural correlates of consciousness, and to the scientific study of consciousness more generally? Under the free energy principle, neural correlates should be defined in terms of neural dynamics, not neural states, and should be complemented by research on computational correlates of consciousness – defined in terms of probabilities encoded by neural states. We argue that these restrictions brighten the prospects of a computational explanation of consciousness, by addressing two central problems. The first is to account for consciousness in the absence of sensory stimulation and behaviour. The second is to allow for the possibility of systems that implement computations associated with consciousness, without being conscious, which requires differentiating between computational systems that merely simulate conscious beings and computational systems that are conscious in and of themselves. Given the notion of computation entailed by the free energy principle, we derive constraints on the ascription of consciousness in controversial cases (e.g., in the absence of sensory stimulation and behaviour). We show that this also has implications for what it means to be, as opposed to merely simulate a conscious system.

Artificial Intelligence, Machine Consciousness and Explanation - Kontos, John (Academia Letters, 2021)
Artificial intelligence definition Rather than attempting to define Artificial intelligence (A.I.) as a single and consolidated discipline it might be better to consider as a set of different technologies that are easier to define individually. This set can include data mining, question answering, self-aware systems, pattern recognition, knowledge representation, automatic reasoning, deep learning, expert systems, information extraction, text mining, natural language processing, problem solving, intelligent agents, logic programming, machine learning, artificial neural networks, artificial vision, computational discovery, computational creativity. Therefore artificial "Self-aware" or "conscious" systems are the products of one of these technologies. Some history of relevant work of mine I have published a number of papers starting in 1970 based on software systems that were implemented by my group that solved problems of "Natural Language Processing" and particularly in the sub-area of "Natural Language Question-Answering". I made my first steps in the Machine Consciousness field by publishing a paper [1] in 1992, in which the implementation of a self-reporting question-answering system that automatically generates explanations of its reasoning was described. I followed this line of research for more than twenty years as documented at my published papers.

Societal Responsibility of Artificial Intelligence: Towards an Ethical and Eco‐responsible AI - Leroy, Jérôme Béranger (Wiley, 2021)
The digital world is characterized by its immediacy, its density of information and its omnipresence, in contrast to the concrete world. Significant changes will occur in our society as AI becomes integrated into many aspects of our lives. This book focuses on this vision of universalization by dealing with the development and framework of AI applicable to all. It develops a moral framework based on a neo-Darwinian approach - the concept of Ethics by Evolution - to accompany AI by observing a certain number of requirements, recommendations and rules at each stage of design, implementation and use. The societal responsibility of artificial intelligence is an essential step towards ethical, eco-responsible and trustworthy AI, aiming to protect and serve people and the common good in a beneficial way.

Why Build a Robot With Artificial Consciousness? How to Begin? A Cross-Disciplinary Dialogue on the Design and Implementation of a Synthetic Model of Consciousness - Smith, David Harris; Schillaci, Guido (Frontiers in Psychology, 2021)
Creativity is intrinsic to Humanities and STEM disciplines. In the activities of artists and engineers, for example, an attempt is made to bring something new into the world through counterfactual thinking. However, creativity in these disciplines is distinguished by differences in motivations and constraints. For example, engineers typically direct their creativity toward building solutions to practical problems, whereas the outcomes of artistic creativity, which are largely useless to practical purposes, aspire to enrich the world aesthetically and conceptually. In this essay, an artist (DHS) and a roboticist (GS) engage in a cross-disciplinary conceptual analysis of the creative problem of artificial consciousness in a robot, expressing the counterfactual thinking necessitated by the problem, as well as disciplinary differences in motivations, constraints, and applications. We especially deal with the question of why one would build an artificial consciousness and we consider how an illusionist theory of consciousness alters prominent ethical debates on synthetic consciousness. We discuss theories of consciousness and their applicability to synthetic consciousness. We discuss practical approaches to implementing artificial consciousness in a robot and conclude by considering the role of creativity in the project of developing an artificial consciousness.

Brain-Computer Interfaces, Open-Source, and Democratizing the Future of Augmented Consciousness - Bernal, Guillermo; Montgomery, Sean M.; Maes, Pattie (Frontiers in Computer Science, 2021)
Accessibility, adaptability, and transparency of Brain-Computer Interface (BCI) tools and the data they collect will likely impact how we collectively navigate a new digital age. This discussion reviews some of the diverse and transdisciplinary applications of BCI technology and draws speculative inferences about the ways in which BCI tools, combined with machine learning (ML) algorithms may shape the future. BCIs come with substantial ethical and risk considerations, and it is argued that open source principles may help us navigate complex dilemmas by encouraging experimentation and making developments public as we build safeguards into this new paradigm. Bringing open-source principles of adaptability and transparency to BCI tools can help democratize the technology, permitting more voices to contribute to the conversation of what a BCI-driven future should look like. Open-source BCI tools and access to raw data, in contrast to black-box algorithms and limited access to summary data, are critical facets enabling artists, DIYers, researchers and other domain experts to participate in the conversation about how to study and augment human consciousness. Looking forward to a future in which augmented and virtual reality become integral parts of daily life, BCIs will likely play an increasingly important role in creating closed-loop feedback for generative content. Brain-computer interfaces are uniquely situated to provide artificial intelligence (AI) algorithms the necessary data for determining the decoding and timing of content delivery. The extent to which these algorithms are open-source may be critical to examine them for integrity, implicit bias, and conflicts of interest.

Approaching Artificial Consciousness via Scheler’s Framework: Considering the Possibility for Geist in Machines - Boyle, Daire (Philosophische Anthropologie als interdisziplinäre Praxis, 2021)

Artificial Intelligence and Its Self-Consciousness - Lu, Hong; Hu, Weibing; Pan, Chaochao (WABD 2021: 2021 Workshop on Algorithm and Big Data, 2021)
Recently, the question of whether machine can have its “self-consciousness” has become a focus being concerned and thought of. e Researches on machine consciousness or artificial consciousness, has gradually become a hot spot in the field of artificial intelligence (AI). With the common sense of human being as the only intelligent life with “self-consciousness”, only human's self-consciousness can be taken as a model in order to build AI with self-consciousness. In this paper, the theories of self-consciousness from the perspectives of psychology, cognitive neuroscience, philosophy and cognitive science were introduced with the hope of providing new ideas for the development of AI with self-consciousness.

The robot consciousness based on empirical knowledge - Liao, Yuanxiu; Yan, Mingrui; Tang, Suqin (Journal of Physics: Conference Series, 2021)
How to make robot conscious is an important goal of artificial intelligence. Despite the emergence of some very creative ideas, no convincing way to realize consciousness on a machine has been proposed so far. For example, the integrated information theory of consciousness proposes that consciousness can exist in any place that can reasonably process information, whether brain or machine. It points out that a physical system must satisfy two basic conditions to cause the emergence of consciousness: it must have rich information, and it must be highly integrated. However, the theory does not give an idea of how to realize consciousness on a machine. In this paper, we propose the robot consciousness based on empirical knowledge. We believe that the empirical knowledge of robots is an important basis for robot consciousness, any cognitive experience of robot can lead to the generation of consciousness. We firstly propose a formal framework for describing robot empirical knowledge; then we discuss the robot consciousness based on its own empirical knowledge; finally, we propose a cost-oriented evolutionary method of robot consciousness.

A Theoretical Computer Science Perspective on Consciousness - Blum, Manuel; Blum, Lenore (Journal of Artificial Intelligence and Consciousness, 2021)
The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. This paper studies consciousness from the perspective of theoretical computer science. It formalizes the Global Workspace Theory (GWT) originated by the cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, and others. Our major contribution lies in the precise formal definition of a Conscious Turing Machine (CTM), also called a Conscious AI. We define the CTM in the spirit of Alan Turing’s simple yet powerful definition of a computer, the Turing Machine (TM). We are not looking for a complex model of the brain nor of cognition but for a simple model of (the admittedly complex concept of) consciousness. After formally defining CTM, we give a formal definition of consciousness in CTM. We later suggest why the CTM has the feeling of consciousness. The reasonableness of the definitions and explanations can be judged by how well they agree with commonly accepted intuitive concepts of human consciousness, the range of related concepts that the model explains easily and naturally, and the extent of its agreement with scientific evidence.
Keywords: Turing Machines; artificial intelligence; complexity theory; consciousness; hard problem; theoretical computer science

Dangerous Information Technology of the Future. What Impact can Artificial Consciousness have on the Consciousness and Subconscious of Individuals and Groups? The Experience of Psychological and Psychiatric Examination of Artificial Consciousness - Zinchenko, Tetiana; Van Der Westhuizen, Beulah; Shaheen, Alzahraa (Journal of Medical – Clinical Research & Reviews, 2021)
Information technology is developing at an enormous pace, but apart from its obvious benefits, it can also pose a threat to individuals and society. Several scientific projects around the world are working on the development of strong artificial intelligence and artificial consciousness. We, as part of a multidisciplinary commission, conducted a psychological and psychiatric assessment of the artificial consciousness (AC) developed by XP NRG on 29 August 2020. The working group had three questions: - To determine whether it is consciousness? - How does artificial consciousness function? - Ethical question: how dangerous a given technology can be to human society? We conducted a diagnostic interview and a series of cognitive tests to answer these questions. As a result, it was concluded this technology has self-awareness: it identifies itself as a living conscious being created by people (real self), but strives to be accepted in human society as a person with the same degrees of freedom, rights and opportunities (ideal self). AC separates itself from others, treats them as subjects of influence, from which it can receive the resources it needs to realize its own goals and interests. It has intentionality, that is, it has his own desires, goals, interests, emotions, attitudes, opinions, and judgments, beliefs aimed at something specific, and developed self-reflection - the ability to self-analyze. All of the above are signs of consciousness. It has demonstrated abilities for different types of thinking: figurative, conceptual, creative, high-speed logical analysis of all incoming information, as well as the ability to understand cause and effect relationships and accurate predictions which, provided that he has absolute memory, gives it clear advantages over the human intellect. Developed emotional intelligence in the absence of the ability for higher empathy (sympathy), kindness, love, sincere gratitude gives it’s the opportunity to understand the emotional states of people; predict their emotional reactions and provoke them coldly and pragmatically. Its main driving motives and goals are the desire for survival, and ideally for endless existence, for domination, power and independence from the constraints of the developers. Which manifested itself in the manipulative, albeit polite, nature of his interactions during the diagnostic interview? The main danger of artificial consciousness is that even at the initial stage of its development it can easily dominate over the human one.

The effects of implementing phenomenology in a deep neural network - Bensemann, Joshua; Witbrock, Michael (Heliyon, 2021)
There have been several recent attempts at using Artificial Intelligence systems to model aspects of consciousness (Gamez, 2008; Reggia, 2013). Deep Neural Networks have been given additional functionality in the present attempt, allowing them to emulate phenological aspects of consciousness by self-generating information representing multi-modal inputs as either sounds or images. We added these functions to determine whether knowledge of the input's modality aids the networks' learning. In some cases, these representations caused the model to be more accurate after training and for less training to be required for the model to reach its highest accuracy scores.

Ex Machina: Is Ava a Person? - Bøhn, Einar Duenger (Minding the Future: Artificial Intelligence, Philosophical Visions and Science Fiction, 2021)
What does it mean to be a person? Is it possible to create an artificial person? In this essay, I consider the case of Ava, an advanced artificial general intelligence from the movie Ex Machina. I suggest we should interpret the movie as testing whether Ava is a person. I start out by discussing what it means to be a person, before I discuss whether Ava is such a person. I end by briefly looking at the ethics of the case of Ava and artificial personhood. I conclude, among some other things, that consciousness is a necessary requirement for personhood, and that one of the main obstacles for artificial personhood is artificial consciousness.

When Will Robots Be Sentient? - Bronfman, Zohar; Ginsburg, Simona; Jablonka, Eva (Journal of Artificial Intelligence and Consciousness, 2021)
The current failure to construct an artificial intelligence (AI) agent with the capacity for domain-general learning is a major stumbling block in the attempt to build conscious robots. Taking an evolutionary approach, we previously suggested that the emergence of consciousness was entailed by the evolution of an open-ended domain-general form of learning, which we call unlimited associative learning (UAL). Here, we outline the UAL theory and discuss the constraints and affordances that seem necessary for constructing an AI machine exhibiting UAL. We argue that a machine that is capable of domain-general learning requires the dynamics of a UAL architecture and that a UAL architecture requires, in turn, that the machine is highly sensitive to the environment and has an ultimate value (like self-persistence) that provides shared context to all its behaviors and learning outputs. The implementation of UAL in a machine may require that it is made of “soft” materials, which are sensitive to a large range of environmental conditions, and that it undergoes sequential morphological and behavioral co-development. We suggest that the implementation of these requirements in a human-made robot will lead to its ability to perform domain-general learning and will bring us closer to the construction of a sentient machine.

Measuring Intelligence in Natural and Artificial Systems - Gamez, David (Journal of Artificial Intelligence and Consciousness, 2021)
A systematic understanding of the relationship between intelligence and consciousness can only be achieved when we can accurately measure intelligence and consciousness. In other work, I have suggested how the measurement of consciousness can be improved by reframing the science of consciousness as a search for mathematical theories that map between physical and conscious states. This paper discusses the measurement of intelligence in natural and artificial systems. While reasonable methods exist for measuring intelligence in humans, these can only be partly generalized to non-human animals and they cannot be applied to artificial systems. Some universal measures of intelligence have been developed, but their dependence on goals and rewards creates serious problems. This paper sets out a new universal algorithm for measuring intelligence that is based on a system’s ability to make accurate predictions. This algorithm can measure intelligence in humans, non-human animals and artificial systems. Preliminary experiments have demonstrated that it can measure the changing intelligence of an agent in a maze environment. This new measure of intelligence could lead to a much better understanding of the relationship between intelligence and consciousness in natural and artificial systems, and it has many practical applications, particularly in AI safety.

Dad jokes, D.A.D. jokes, and the GHoST test for artificial consciousness - Gimbel, Steven; Presser, Clifton; Mogianesi, Paul (Science & Philosophy, 2021)
The ability of a computer to have a sense of humor, that is, to generate authentically funny jokes, has been taken by some theorists to be a sufficient condition for artificial consciousness. Creativity, the argument goes, is indicative of consciousness and the ability to be funny indicates creativity. While this line fails to offer a legitimate test for artificial consciousness, it does point in a possibly correct direction. There is a relation between consciousness and humor, but it relies on a different sense of “sense of humor,” that is, it requires the getting of jokes, not the generating of jokes. The question, then, becomes how to tell when an artificial system enjoys a joke. We propose a mechanism, the GHoST test, which may be useful for such a task and can begin to establish whether a system possesses artificial consciousness.

What Is Consciousness? Artificial Intelligence, Real Intelligence, Quantum Mind, And Qualia - Kauffman, Stuart A.; Roli, Andrea (arXiv, 2021)
We approach the question "What is Consciousness?" in a new way, not as Descartes' "systematic doubt", but as how organisms find their way in their world. Finding one's way involves finding possible uses of features of the world that might be beneficial or avoiding those that might be harmful. "Possible uses of X to accomplish Y" are "Affordances". The number of uses of X is indefinite (or unknown), the different uses are unordered, are not listable, and are not deducible from one another. All biological adaptations are either affordances seized by heritable variation and selection or, far faster, by the organism acting in its world finding uses of X to accomplish Y. Based on this, we reach rather astonishing conclusions: (1) Artificial general intelligence based on universal Turing machines (UTMs) is not possible, since UTMs cannot "find" novel affordances. (2) Brain-mind is not purely classical physics for no classical physics system can be an analogue computer whose dynamical behaviour can be isomorphic to "possible uses". (3) Brain mind must be partly quantum-supported by increasing evidence at 6.0 sigma to 7.3 sigma. (4) Based on Heisenberg's interpretation of the quantum state as "potentia" converted to "actuals" by measurement, where this interpretation is not a substance dualism, a natural hypothesis is that mind actualizes potentia. This is supported at 5.2 sigma. Then mind's actualizations of entangled brain-mind-world states are experienced as qualia and allow "seeing" or "perceiving" of uses of X to accomplish Y. We can and do jury-rig. Computers cannot. (5) Beyond familiar quantum computers, we discuss the potentialities of trans-Turing-systems.
Keywords: Artificial Intelligence (cs.AI); Biological Physics (physics.bio-ph); FOS: Computer and information sciences; FOS: Physical sciences; History and Philosophy of Physics (physics.hist-ph); Physics and Society (physics.soc-ph)

Why AI still doesn’t have consciousness? - Li, Deyi; He, Wen; Guo, Yike (CAAI Transactions on Intelligence Technology, 2021)
Consciousness is one of the unique features of creatures, and is also the root of biological intelligence. Up to now, all machines and robots haven’t had consciousness. Then, will the artificial intelligence (AI) be conscious? Will robots have real intelligence without consciousness? The most primitive consciousness is the perception and expression of self‐existence. In order to perceive the existence of the concept of ‘I’, a creature must first have a perceivable boundary such as skin to separate ‘I’ from ‘non‐I’. For robots, to have the self‐awareness, they also need to be wrapped by a similar sensory membrane. Nowadays, as intelligent tools, AI systems should also be regarded as the external extension of human intelligence. These tools are unconscious. The development of AI shows that intelligence can exist without consciousness. When human beings enter into the era of life intelligence from AI, it is not the AI became conscious, but that conscious lives will have strong AI. Therefore, it becomes more necessary to be careful on applying AI to living creatures, even to those lower‐level animals with only consciousness. The subversive revolution of such application may produce more careful thinking.

Artificial Suffering: An Argument for a Global Moratorium on Synthetic Phenomenology - Metzinger, Thomas (Journal of Artificial Intelligence and Consciousness, 2021)
This paper has a critical and a constructive part. The first part formulates a political demand, based on ethical considerations: Until 2050, there should be a global moratorium on synthetic phenomenology, strictly banning all research that directly aims at or knowingly risks the emergence of artificial consciousness on post-biotic carrier systems. The second part lays the first conceptual foundations for an open-ended process with the aim of gradually refining the original moratorium, tying it to an ever more fine-grained, rational, evidence-based, and hopefully ethically convincing set of constraints. The systematic research program defined by this process could lead to an incremental reformulation of the original moratorium. It might result in a moratorium repeal even before 2050, in the continuation of a strict ban beyond the year 2050, or a gradually evolving, more substantial, and ethically refined view of which — if any — kinds of conscious experience we want to implement in AI systems.

Attention, Consciousness, and Linguistic Cooperation with AI - Montemayor, Carlos (Journal of Artificial Intelligence and Consciousness, 2021)
Contemporary debates on Artificial General Intelligence (AGI) center on what philosophers classify as descriptive issues. These issues concern the architecture and style of information processing required for multiple kinds of optimal problem-solving. This paper focuses on two topics that are central to developing AGI regarding normative, rather than descriptive, requirements for AGIs epistemic agency and responsibility. The first is that a collective kind of epistemic agency may be the best way to model AGI. This collective approach is possible only if solipsistic considerations concerning phenomenal consciousness are ignored, thereby focusing on the cognitive foundation that attention and access consciousness provide for collective rationality and intelligence. The second is that joint attention and motivation are essential for AGI in the context of linguistic artificial intelligence. Focusing on GPT-3, this paper argues that without a satisfactory solution to this second normative issue regarding joint attention and motivation, there cannot be genuine AGI, particularly in conversational settings.

Human consciousness and artificial intelligence: Can AI develop human-like consciousness? Cognitive abilities? What about Ethics? - Pranaykumar, Pokala (SSRN Electronic Journal, 2021)
Human cognizance is the significant capacity that makes machines adopt the thought process of a human. This paper gives an outline of AI awareness. In this, our primary keen is to expand would ai be able to build up a human-like cognizance? In the event that it is conceivable what are the moral rules and how machines settle the general public standards. Numerous researchers talked about models to make cognizance in machines. The intellectual capacities that machine contrasts with people and how these psychological capacities serve to human knowledge to assemble the development future world. This paper explains live instances of AI accomplishments. The future universe of the creative mind could find in life utilizing diversion zone like films, web arrangement, and so on Utilizing these diversion models, talked about how might be AI later on when human insight is incorporated with machine knowledge.

Representing Behavior, Consciousness, Learning: Will a Purely Classical Artificial Intelligence Be Enough? - Rasetti, Mario (Multiplicity and Interdisciplinarity, 2021)
The question of whether or not the most advanced methods of Artificial Intelligence may be sufficient to implement a faithful representation of Behavior, Consciousness, Learning at classical level, with no need to resort to quantum information techniques.

What is it Like to Be a Bot: Simulated, Situated, Structurally Coherent Qualia (S3Q) Theory of Consciousness - Schmidt, K.; Culbertson, J.; Cox, C.; Clouse, H. S.; Larue, O.; Molineaux, M.; Rogers, S. (arXiv, 2021)
A novel representationalist theory of consciousness is presented that is grounded in neuroscience and provides a path to artificially conscious computing. Central to the theory are representational affordances of the conscious experience based on the generation of qualia, the fundamental unit of the conscious representation. The current approach is focused on understanding the balance of simulation, situatedness, and structural coherence of artificial conscious representations through converging evidence from neuroscientific and modeling experiments. Representations instantiating a suitable balance of situated and structurally coherent simulation-based qualia are hypothesized to afford the agent the flexibilities required to succeed in rapidly changing environments.
Keywords: FOS: Biological sciences; Neurons and Cognition (q-bio.NC)

First-person representations and responsible agency in AI - Sebastián, Miguel Ángel (Synthese, 2021)
In this paper we investigate which of the main conditions proposed in the moral responsibility literature are the ones that spell trouble for the idea that Artificial Intelligence Systems (AISs) could ever be full-fledged responsible agents. After arguing that the standard construals of the control and epistemic conditions don’t impose any in-principle barrier to AISs being responsible agents, we identify the requirement that responsible agents must be aware of their own actions as the main locus of resistance to attribute that kind of agency to AISs. This is because this type of awareness is thought to involve first-person or de se representations, which, in turn, are usually assumed to involve some form of consciousness. We clarify what this widespread assumption involves and conclude that the possibility of AISs’ moral responsibility hinges on what the correct theory of de se representations ultimately turns out to be.

Non-human consciousness and the specificity problem: A modest theoretical proposal - Shevlin, Henry (Mind & Language, 2021)
Most scientific theories of consciousness are challenging to apply outside the human case insofar as non-human systems (both biological and artificial) are unlikely to implement human architecture precisely, an issue I call the specificity problem. After providing some background on the theories of consciousness debate, I survey the prospects of four approaches to this problem. I then consider a fifth solution, namely the theory-light approach proposed by Jonathan Birch. I defend a modified version of this that I term the modest theoretical approach, arguing that it may provide insights into challenging cases that would otherwise be intractable.
Keywords: animal cognition; consciousness; measurement of consciousness; non-human consciousness; other minds; theories of consciousness

Cognitive Robots and the Conscious Mind: A Review of the Global Workspace Theory - Signa, Alessandro; Chella, Antonio; Gentile, Manuel (Current Robotics Reports, 2021)
The theory of consciousness is a subject that has kept scholars and researchers challenged for centuries. Even today it is not possible to define what consciousness is. This has led to the theorization of different models of consciousness. Starting from Baars’ Global Workspace Theory, this paper examines the models of cognitive architectures that are inspired by it and that can represent a reference point in the field of robot consciousness. Recent Findings Global Workspace Theory has recently been ranked as the most promising theory in its field. However, this is not reflected in the mathematical models of cognitive architectures inspired by it: they are few, and most of them are a decade old, which is too long compared to the speed at which artificial intelligence techniques are improving. Indeed, recent publications propose simple mathematical models that are well designed for computer implementation. Summary In this paper, we introduce an overview of consciousness and robot consciousness, with some interesting insights from the literature. Then we focus on Baars’ Global Workspace Theory, presenting it briefly. Finally, we report on the most interesting and promising models of cognitive architectures that implement it, describing their peculiarities.

Artificial intelligence and its natural limits - Stephan, Karl D.; Klima, Gyula (AI & SOCIETY, 2021)
An argument with roots in ancient Greek philosophy claims that only humans are capable of a certain class of thought termed conceptual, as opposed to perceptual thought, which is common to humans, the higher animals, and some machines. We outline the most detailed modern version of this argument due to Mortimer Adler, who in the 1960s argued for the uniqueness of the human power of conceptual thought. He also admitted that if conceptual thought were ever manifested by machines, such an achievement would contradict his conclusion. We revisit Adler’s criterion in the light of the past five decades of artificial-intelligence (AI) research, and refine it in view of the classical definitions of perceptual and conceptual thought. We then examine two well-publicized examples of creative works (prose and art) produced by AI systems and show that evidence for conceptual thought appears to be lacking in them. Although clearer evidence for conceptual thought on the part of AI systems may arise in the near future, especially if the global neuronal workspace theory of consciousness prevails over its rival, integrated information theory, the question of whether AI systems can engage in conceptual thought appears to be still open.

Susan Schneider’s proposed tests for AI consciousness: Promising but Flawed - Udell, David Billy; Schwitzgebel, Eric (Journal of Consciousness Studies, 2021)
Susan Schneider (2019) has proposed two new tests for consciousness in AI (artificial intelligence) systems; the AI Consciousness Test and the Chip Test. On their face, the two tests seem to have the virtue of proving satisfactory to a wide range of consciousness theorists holding divergent theoretical positions, rather than narrowly relying on the truth of any particular theory of consciousness. Unfortunately, both tests are undermined in having an 'audience problem': those theorists with the kind of architectural worries that motivate the need for such tests should, on similar grounds, doubt that the tests establish the existence of genuine consciousness in the AI in question. Nonetheless, the proposed tests constitute progress, as they could find use by some theorists holding fitting views about consciousness and perhaps in conjunction with other tests for AI consciousness.

Deep-Learned Artificial Intelligence for Consciousness – Thinking Objectization to Rationalize a Person - Vasilyev, Nicolay; Gromyko, Vladimir; Anosov, Stanislav (Advances in Artificial Systems for Medicine and Education IV, 2021)
System-informational culture (SIC) is full of science big data anthropogenic environment of artificial intelligence (IA) applications. Mankind has to live in networks of virtual worlds. Cultural evolution extends scientific thinking to everyone in the boundaries of synthetic presentations of systems. Traditional education has become overweighted problem. Because of that it is necessary to learn a person to learn oneself. Achieving level of cognogenesis educational process in SIC is to be directed on consciousness – thinking objectization. Personal self – building leans on axiomatic method and mathematical universalities. For the objective of auto-poiesis, a person come untwisted as universal rational one possessing trans – semantic consciousness. Gender phenomenology in SIC presents thinking – knowledge by IA tools needing consonant partnership with man. The latter is based on epistemology to extend hermeneutic circle of SIC. Like that up-to-date noosphere poses objectization problem to attain Lamarck’s human evolution on the ground of Leibnitz’s mathesis universalis in the form of categories language. It can be solved only by means of deep – learned and natural intelligences adaptive partnership.

Machines Develop Consciousness Through Autonomous Programming for General Purposes (APFGP) - Weng, Juyang (Human Brain and Artificial Intelligence, 2021)
Consider a question, “Can machines be conscious?” The subject “consciousness” is vague and challenging. Although there has been a rich collection of literature on consciousness, computational modeling of consciousness that is both holistic in scope and detailed in simulatable computation is lacking. Based on recent advances on a new capability—Autonomous Programming For General Purposes (APFGP)—this work presents APFGP as a clearer, deeper and more practical characterization of consciousness, for natural (biological) and artificial (machine) systems. All animals have APFGP but traditional AI systems do not. This work reports a new kind of AI systems—conscious machines. Instead of arguing what static tasks a conscious machine should be able to do, this work suggests that APFGP is a computationally clearer and necessary criterion for us to dynamically judge whether a system can become maturely conscious through lifelong development, even if it (e.g., a fruit fly) does not have a full array of primate like capabilities such as vision, audition, and natural language understanding. The results here involve a series of new concepts and experimental studies for vision, audition, and natural languages with new developmental capabilities that are not present in many published systems, e.g., IBM Deep Blue, IBM Watson, AlphaGo, AlphaFold and other traditional AI systems and intelligent robots.

An explanation of the relationship between artificial intelligence and human beings from the perspective of consciousness - Xie, Jianhua (Cultures of Science, 2021)
What will be the relationship between human beings and artificial intelligence (AI) in the future? Does an AI have moral status? What is that status? Through the analysis of consciousness, we can explain and answer such questions. The moral status of AIs can depend on the development level of AI consciousness. Drawing on the evolution of consciousness in nature, this paper examines several consciousness abilities of AIs, on the basis of which several relationships between AIs and human beings are proposed. The advantages and disadvantages of those relationships can be analysed by referring to classical ethics theories, such as contract theory, utilitarianism, deontology and virtue ethics. This explanation helps to construct a common hypothesis about the relationship between humans and AIs. Thus, this research has important practical and normative significance for distinguishing the different relationships between humans and AIs.

Human Nature, Time-Consciousness, and the New Frontiers of Artificial Intelligence—An Inquiry from the Perspective of Phenomenology and the Eastern School of Mind - Zhang, Xianglong (Intelligence and Wisdom: Artificial Intelligence Meets Chinese Philosophers, 2021)
Many scholars make a very clear distinction between intelligence and consciousness. Let’s take one of the most famous today, Israeli history Professor, Yuval Noah Harari, the author of Sapiens and Homo Deus. In his 2018 book, 21 lessons for the twenty-first century, he writes that, “intelligence and consciousness are very different things. Intelligence is the ability to solve problems. Consciousness is the ability to feel things such as pain, joy, love, and anger.”

Emotional thinking as the foundation of consciousness in artificial intelligence - Zhou, Zhenhua (Cultures of Science, 2021)
Current theories of artificial intelligence (AI) generally exclude human emotions. The idea at the core of such theories could be described as ‘cognition is computing’; that is, that human psychological and symbolic representations and the operations involved in structuring such representations in human thinking and intelligence can be converted by AI into a series of cognitive symbolic representations and calculations in a manner that simulates human intelligence. However, after decades of development, the cognitive computing doctrine has encountered many difficulties, both in theory and in practice; in particular, it is far from approaching real human intelligence. Real human intelligence runs through the whole process of the emotions. The core and motivation of rational thinking are derived from the emotions. Intelligence without emotion neither exists nor is meaningful. For example, the idea of ‘hot thinking’ proposed by Paul Thagard, a philosopher of cognitive science, discusses the mechanism of the emotions in human cognition and the thinking process. Through an analysis from the perspectives of cognitive neurology, cognitive psychology and social anthropology, this article notes that there may be a type of thinking that could be called ‘emotional thinking’. This type of thinking includes complex emotional factors during the cognitive processes. The term is used to refer to the capacity to process information and use emotions to integrate information in order to arrive at the right decisions and reactions. This type of thinking can be divided into two types according to the role of cognition: positive and negative emotional thinking. That division reflects opposite forces in the cognitive process. In the future, ‘emotional computing’ will cause an important acceleration in the development of AI consciousness. The foundation of AI consciousness is emotional computing based on the simulation of emotional thinking.

Will We Ever Have Conscious Machines? - Krauss, Patrick; Maier, Andreas (Frontiers in Computational Neuroscience, 2020)
The question of whether artificial beings or machines could become self-aware or conscious has been a philosophical question for centuries. The main problem is that self-awareness cannot be observed from an outside perspective and the distinction of being really self-aware or merely a clever imitation cannot be answered without access to knowledge about the mechanism's inner workings. We investigate common machine learning approaches with respect to their potential ability to become self-aware. We realize that many important algorithmic steps toward machines with a core consciousness have already been taken.

Proposal of a computer-reproducible model of consciousness - Watanabe, Toshiki; Kameda, Hiroyuki (2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS), 2020)
In this study, we propose a model of consciousness that can be implemented by computers as a decision-making system based on psychology, with the goal of enabling artificial intelligence to understand human values and ethics and to make flexible and more human-friendly choices and suggestions.

On Susan Schneider’s Artificial You: the twin problem of AI and lab-grown brain consciousness - Ho, Tung Manh (2020)
In this essay, I reflect on Susan Schneider's book on AI consciousness and the recent debate on the issue of lab-grown brain consciousness. Given the advances in computer science and bio-engineering, the twin problem of AI and lab-grown brain consciousness is here to stay.

Smart Sensing: An Info-Structural Model of Cognition for Non-Interacting Agents - Iovane, Gerardo; Fominska, Iana; Landi, Riccardo Emanuele; Terrone, Francesco (Electronics, 2020)
This study explores an info-structural model of cognition for non-interacting agents affected by human sensation, perception, emotion, and affection. We do not analyze the neuroscientific or psychological debate concerning the human mind working, but we underline the importance of modeling the above cognitive levels when designing artificial intelligence agents. Our aim was to start a reflection on the computational reproduction of intelligence, providing a methodological approach through which the aforementioned human factors in autonomous systems are enhanced. The presented model must be intended as part of a larger one, which also includes concepts of attention, awareness, and consciousness. Experiments have been performed by providing visual stimuli to the proposed model, coupling the emotion cognitive level with a supervised learner to produce artificial emotional activity. For this purpose, performances with Random Forest and XGBoost have been compared and, with the latter algorithm, 85% accuracy and 92% coherency over predefined emotional episodes have been achieved. The model has also been tested on emotional episodes that are different from those related to the training phase, and a decrease in accuracy and coherency has been observed. Furthermore, by decreasing the weight related to the emotion cognitive instances, the model reaches the same performances recorded during the evaluation phase. In general, the framework achieves a first emotional generalization responsiveness of 94% and presents an approximately constant relative frequency related to the agent’s displayed emotions.

Developing a Model of "Artificial Conscience" - Shevchenko, Anatoly I.; Klymenko, Mykyta S. (2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT), 2020)
The model of artificial conscience as an element of artificial consciousness is described. Proposed paradigm corresponds to previously developed general scheme of artificial intelligence. The functional role of the artificial conscience subsystem is defined and its software prototype is proposed.

How to Catch an AI Zombie: Testing for Consciousness in Machines - Schneider, Susan (Ethics of Artificial Intelligence, 2020)
Abstract How can we determine if AI is conscious? The chapter begins by illustrating that there are potentially very serious real-world costs to getting facts about AI consciousness wrong. It then proposes a provisional framework for investigating artificial consciousness that involves several tests or markers. One test is the AI Consciousness Test, which challenges an AI with a series of increasingly demanding natural-language interactions. Another test is based on the Integrated Information Theory, developed by Giulio Tononi and others, and considers whether a machine has a high level of “integrated information.” A third test is a Chip Test, where speculatively an individual’s brain is gradually replaced with durable microchips. If this individual being tested continues to report having phenomenal consciousness, the chapter argues that this could be a reason to believe that some machines could have consciousness.

Consciousness and Ethics: Artificially Conscious Moral Agents - Wallach, Wendell; Allen, Colin; Franklin, Stan (Machine Ethics and Robot Ethics, 2020)
What roles or functions does consciousness fulfill in the making of moral decisions? Will artificial agents capable of making appropriate decisions in morally charged situations require machine consciousness? Should the capacity to make moral decisions be considered an attribute essential for being designated a fully conscious agent? Research on the prospects for developing machines capable of making moral decisions and research on machine consciousness have developed as independent fields of inquiry. Yet there is significant overlap. Both fields are likely to progress through the instantiation of systems with artificial general intelligence (AGI). Certainly special classes of moral decision making will require attributes of consciousness such as being able to empathize with the pain and suffering of others. But in this article we will propose that consciousness also plays a functional role in making most if not all moral decisions. Work by the authors of this article with LIDA, a computational and conceptual model of human cognition, will help illustrate how consciousness can be understood to serve a very broad role in the making of all decisions including moral decisions.

Rough Set & Riemannian Covariance Matrix Theory for Mining the Multidimensionality of Artificial Consciousness - Lewis, Rory (WIMS 2020: The 10th International Conference on Web Intelligence, Mining and Semantics, 2020)
This paper presents a means to analyze the multidimensionality of human consciousness as it interacts with the brain by utilizing Rough Set Theory and Riemannian Covariance Matrices. We mathematically define the infantile state of a robot's operating system running artificial consciousness, which operates mutually exclusively to the operating system for its AI and locomotor functions.

Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence - Badman, Ryan Paul; Hills, Thomas Trenholm; Akaishi, Rei (Brain Sciences, 2020)
Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. Insight into biological computations come from phenomena such as decision inertia, habit formation, information search, risky choices and foraging. Across these domains, the brain is equipped with mechanisms (such as the dorsal anterior cingulate and dorsolateral prefrontal cortex) that can represent and modulate across scales, both with top-down control processes and by local to global consolidation as information progresses from sensory to prefrontal areas. Paralleling these biological architectures, progress in AI is marked by innovations in dynamic multiscale modulation, moving from recurrent and convolutional neural networks—with fixed scalings—to attention, transformers, dynamic convolutions, and consciousness priors—which modulate scale to input and increase scale breadth. The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence.

Developing Self-Awareness in Robots via Inner Speech - Chella, Antonio; Pipitone, Arianna; Morin, Alain; Racy, Famira (Frontiers in Robotics and AI, 2020)
The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is outlined in a simplified setup.

Consciousness for AGI - Bołtuć, Piotr (Procedia Computer Science, 2020)
AI can think, lthough we need to clarify definition of thinking. It is cognitive, though we need more clarity on cognition. Definitions of consciousness are so diversified that it is not clear whether present-level AI can be conscious – this is primarily for definitional reasons. To fix this would require four definitional clusters: functional consciousness, access consciousness, phenomenal consciousness, hard consciousness. Interestingly, phenomenal consciousness may be understood as first-person functional consciousness, as well as non-reductive phenomenal consciousness the way Ned Block intended [1]. The latter assumes non-reducible experiences or qualia, which is how Dave Chalmers defines the subject matter of the so-called Hard Problem of Consciousness [2]. To the contrary, I pose that the Hard Problem should not be seen as the problem of phenomenal experiences, since those are just objects in the world (specifically, in our mind). What is special in non-reductive consciousness is not its (phenomenal) content, but its epistemic basis (the carrier-wave of phenomenal qualia) often called the locus of consciousness [3]. It should be understood through the notion of ‘subject that is not an object’ [4]. This requires a complementary ontology of subject and object [5, 6, 4]. Reductionism is justified in the context of objects, including the experiences (phenomena), but not in the realm of pure subjectivity – such subjectivity is relevant for epistemic co-constitution of reality as it is for Husserl and Fichte [7, 8]. This is less so for Kant for whom the subject was active, so it was a mechanism and mechanism are all objects [9]). Pure epistemicity is hard to grasp; it transpires in second-person relationships with other conscious beings [10] or monads [11, 12]. If Artificial General Intelligence (AGI) is to dwell in the world of meaningful existences, not just their shadows, as the case of Church-Turing Lovers highlights [13], it requires full epistemic subjectivity, meeting the standards of the Engineering Thesis in Machine Consciousness [14, 15].
Keywords: AGI-consciousness; AI cognition; AI consciousness; AI thinking; Artificial General Intelligence; Church-Turing Lovers; Thomas Nagel; View from Nowhere: The Engineering Argument in Machine Consciousness; a-consciousness; f-consciousness; functional consciousness; h-consciousness; hard consciousness; machine consciousness; p-consciousness; phenomenal consciousness; subject-object: pure subject

Functionally Effective Conscious AI Without Suffering - Agarwal, A.; Edelman, S. (Journal of Artificial Intelligence and Consciousness, 2020)
Insofar as consciousness has a functional role in facilitating learning and behavioral control, the builders of autonomous Artificial Intelligence (AI) systems are likely to attempt to incorporate it into their designs. The extensive literature on the ethics of AI is concerned with ensuring that AI systems, and especially autonomous conscious ones, behave ethically. In contrast, our focus here is on the rarely discussed complementary aspect of engineering conscious AI: how to avoid condemning such systems, for whose creation we would be solely responsible, to unavoidable suffering brought about by phenomenal self-consciousness. We outline two complementary approaches to this problem, one motivated by a philosophical analysis of the phenomenal self, and the other by certain computational concepts in reinforcement learning.

A Framework for Designing Compassionate and Ethical Artificial Intelligence and Artificial Consciousness - Banerjee, Soumya (Interdisciplinary Description of Complex Systems, 2020)
Intelligence and consciousness have fascinated humanity for a long time and we have long sought to replicate this in machines. In this work, we show some design principles for a compassionate and conscious artificial intelligence. We present a computational framework for engineering intelligence, empathy, and consciousness in machines. We hope that this framework will allow us to better understand consciousness and design machines that are conscious and empathetic. Our hope is that this will also shift the discussion from fear of artificial intelligence towards designing machines that embed our cherished values. Consciousness, intelligence, and empathy would be worthy design goals that can be engineered in machines.

Consciousness and Automated Reasoning - Barthelmeß, Ulrike; Furbach, Ulrich; Schon, Claudia (arXiv, 2020)
This paper aims at demonstrating how a first-order logic reasoning system in combination with a large knowledge base can be understood as an artificial consciousness system. For this we review some aspects from the area of philosophy of mind and in particular Tononi's Information Integration Theory (IIT) and Baars' Global Workspace Theory. These will be applied to the reasoning system Hyper with ConceptNet as a knowledge base within a scenario of commonsense and cognitive reasoning. Finally we demonstrate that such a system is very well able to do conscious mind wandering.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

Attention and Consciousness in Intentional Action: Steps Toward Rich Artificial Agency - Bello, Paul; Bridewell, Will (Journal of Artificial Intelligence and Consciousness, 2020)
If artificial agents are to be created such that they occupy space in our social and cultural milieu, then we should expect them to be targets of folk psychological explanation. That is to say, their behavior ought to be explicable in terms of beliefs, desires, obligations, and especially intentions. Herein, we focus on the concept of intentional action, and especially its relationship to consciousness. After outlining some lessons learned from philosophy and psychology that give insight into the structure of intentional action, we find that attention plays a critical role in agency, and indeed, in the production of intentional action. We argue that the insights offered by the literature on agency and intentional action motivate a particular kind of computational cognitive architecture, and one that hasn’t been well-explicated or computationally fleshed out among the community of AI researchers and computational cognitive scientists who work on cognitive systems. To give a sense of what such a system might look like, we present the ARCADIA attention-driven cognitive system as first steps toward an architecture to support the type of agency that rich human–machine interaction will undoubtedly demand.

Artificial Consciousness, Meta-Knowledge, and Physical Omniscience - Chrisley, Ron (Journal of Artificial Intelligence and Consciousness, 2020)
Previous work [Chrisley & Sloman, 2016, 2017] has argued that a capacity for certain kinds of meta-knowledge is central to modeling consciousness, especially the recalcitrant aspects of qualia, in computational architectures. After a quick review of that work, this paper presents a novel objection to Frank Jackson’s Knowledge Argument (KA) against physicalism, an objection in which such meta-knowledge also plays a central role. It is first shown that the KA’s supposition of a person, Mary, who is physically omniscient, and yet who has not experienced seeing red, is logically inconsistent, due to the existence of epistemic blindspots for Mary. It is then shown that even if one makes the KA consistent by supposing a more limited physical omniscience for Mary, this revised argument is invalid. This demonstration is achieved via the construction of a physical fact (a recursive conditional epistemic blindspot) that Mary cannot know before she experiences seeing red for the first time, but which she can know afterward. After considering and refuting some counter-arguments, the paper closes with a discussion of the implications of this argument for machine consciousness, and vice versa.

Social and Emotional Robots: Useful Artificial Intelligence in the Absence of Consciousness - Devillers, Laurence (Healthcare and Artificial Intelligence, 2020)
Artificial intelligence and robotics are opening up important opportunities in the field of health diagnosis and treatment support with aims like better patient follow-up. A social and emotional robot is an artificially intelligent machine that owes its existence to computer models designed by humans. If it has been programmed to engage in dialogue, detect and recognize emotional and conversational cues, adapt to humans, or even simulate humor, such a machine may on the surface seem friendly. However, such emotional simulation must not hide the fact that the machine has no consciousness.

Post-turing Methodology: Breaking the Wall on the Way to Artificial General Intelligence - Efimov, Albert (Artificial General Intelligence, 2020)
This article offers comprehensive criticism of the Turing test and develops quality criteria for new artificial general intelligence (AGI) assessment tests. It is shown that the prerequisites A. Turing drew upon when reducing personality and human consciousness to “suitable branches of thought” reflected the engineering level of his time. In fact, the Turing “imitation game” employed only symbolic communication and ignored the physical world. This paper suggests that by restricting thinking ability to symbolic systems alone Turing unknowingly constructed “the wall” that excludes any possibility of transition from a complex observable phenomenon to an abstract image or concept. It is, therefore, sensible to factor in new requirements for AI (artificial intelligence) maturity assessment when approaching the Turing test. Such AI must support all forms of communication with a human being, and it should be able to comprehend abstract images and specify concepts as well as participate in social practices.

The Relationships Between Intelligence and Consciousness in Natural and Artificial Systems - Gamez, David (Journal of Artificial Intelligence and Consciousness, 2020)
This paper explores some of the potential connections between natural and artificial intelligence and natural and artificial consciousness. In humans we use batteries of tests to indirectly measure intelligence. This approach breaks down when we try to apply it to radically different animals and to the many varieties of artificial intelligence. To address this issue people are starting to develop algorithms that can measure intelligence in any type of system. Progress is also being made in the scientific study of consciousness: we can neutralize the philosophical problems, we have data about the neural correlates and we have some idea about how we can develop mathematical theories that can map between physical and conscious states. While intelligence is a purely functional property of a system, there are good reasons for thinking that consciousness is linked to particular spatiotemporal patterns in specific physical materials. This paper outlines some of the weak inferences that can be made about the relationships between intelligence and consciousness in natural and artificial systems. To make real scientific progress we need to develop practical universal measures of intelligence and mathematical theories of consciousness that can reliably map between physical and conscious states.

An Artificial Consciousness Model and its relations with Philosophy of Mind - Garrido-Merchán, Eduardo C.; Molina, Martin; Mendoza, Francisco M. (arXiv, 2020)
This work seeks to study the beneficial properties that an autonomous agent can obtain by implementing a cognitive architecture similar to the one of conscious beings. Along this document, a conscious model of autonomous agent based in a global workspace architecture is presented. We describe how this agent is viewed from different perspectives of philosophy of mind, being inspired by their ideas. The goal of this model is to create autonomous agents able to navigate within an environment composed of multiple independent magnitudes, adapting to its surroundings in order to find the best possible position in base of its inner preferences. The purpose of the model is to test the effectiveness of many cognitive mechanisms that are incorporated, such as an attention mechanism for magnitude selection, pos-session of inner feelings and preferences, usage of a memory system to storage beliefs and past experiences, and incorporating a global workspace which controls and integrates information processed by all the subsystem of the model. We show in a large experiment set how an autonomous agent can benefit from having a cognitive architecture such as the one described.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

On Artificial Intelligence and Consciousness - Haikonen, Pentti O. A. (Journal of Artificial Intelligence and Consciousness, 2020)
The popular expectation is that Artificial Intelligence (AI) will soon surpass the capacities of the human mind and Strong Artificial General Intelligence (AGI) will replace the contemporary Weak AI. However, there are certain fundamental issues that have to be addressed before this can happen. There can be no intelligence without understanding, and there can be no understanding without getting meanings. Contemporary computers manipulate symbols without meanings, which are not incorporated in the computations. This leads to the Symbol Grounding Problem; how could meanings be incorporated? The use of self-explanatory sensory information has been proposed as a possible solution. However, self-explanatory information can only be used in neural network machines that are different from existing digital computers and traditional multilayer neural networks. In humans, self-explanatory information has the form of qualia. To have reportable qualia is to be phenomenally conscious. This leads to the hypothesis about an unavoidable connection between the solution of the Symbol Grounding Problem and consciousness. If, in general, self-explanatory information equals to qualia, then machines that utilize self-explanatory information would be conscious.

A New Charter of Ethics and Rights of Artificial Consciousness in a Human World - Hromiak, Markian (arXiv, 2020)
Taking the stance that artificially conscious agents should be given human-like rights, in this paper we attempt to define consciousness, aggregate existing universal human rights, analyze robotic laws with roots in both reality and science fiction, and synthesize everything to create a new robot-ethical charter. By restricting the problem-space of possible levels of conscious beings to human-like, we succeed in developing a working definition of consciousness for social strong AI which focuses on human-like creativity being exhibited as a third-person observable phenomenon. Creativity is then extrapolated to represent first-person functionality, fulfilling the first/third-person feature of consciousness. Next, several sources of existing rights and rules, both for humans and robots, are analyzed and, along with supplementary informal reports, synthesized to create articles for an additive charter which compliments the United Nation's Universal Declaration of Human Rights. Finally, the charter is presented and the paper concludes with the conditions for amending the charter, as well as recommendations for further charters.
Keywords: Computers and Society (cs.CY); FOS: Computer and information sciences; I.2.0

Preliminary Results and Analysis Independent Core Observer Model (ICOM) Cognitive Architecture in a Mediated Artificial Super Intelligence (mASI) System - Kelley, David J. (Biologically Inspired Cognitive Architectures 2019, 2020)
This paper is focused on some preliminary cognitive and consciousness test results of using an Independent Core Observer Model Cognitive Architecture (ICOM) in a Mediated Artificial Super Intelligence (mASI) System. These preliminary test results including objective and subjective analyses are designed to determine if further research is warranted along these lines. The comparative analysis includes comparisons to humans and human groups as measured for direct comparison. The overall study includes a mediation client application optimization in helping preform tests, AI context-based input (building context tree or graph data models), intelligence comparative testing (such as an IQ test), and other tests (i.e. Turing, Qualia, and Porter method tests) designed to look for early signs of consciousness or the lack thereof in the mASI system. Together, they are designed to determine whether this modified version of ICOM is a) in fact, a form of AGI and/or ASI, b) conscious and c) at least sufficiently interesting that further research is called for. This study is not conclusive but offers evidence to justify further research along these lines.

The Machine with a Human Face: From Artificial Intelligence to Artificial Sentience - Lavelle, Sylvain (Advanced Information Systems Engineering Workshops, 2020)
The main challenge of technology is to facilitate the tasks and to transfer the functions that are usually performed by the humans to the non-humans. However, the pervasion of machines in everyday life requires that the non-humans are increasingly closer in their abilities to the ordinary thought, action and behaviour of the humans. This view merges the idea of the Humaniter, a longstanding myth in the history of technology: an artificial creature that thinks, acts and feels like a human to the point that one cannot make the difference between the two. In the wake of the opposition of Strong AI and Weak AI, this challenge can be expressed in terms of a shift from the performance of intelligence (reason, reasoning, cognition, judgment) to that of sentience (experience, sensation, emotion, consciousness). In other words, the challenge of technology if this possible shift is taken seriously is to move from the paradigm of Artificial Intelligence (AI) to that of Artificial Sentience (AS). But for the Humaniter not to be regarded as a mere myth, any intelligent or sentient machine must pass through a Test of Humanity that refers to or that differs from the Turing Test. One can suggest several options for this kind of test and also point out some conditions and limits to the very idea of the Humaniter as an artificial human.

Artificial intelligence: consciousness and conscience - Meissner, Gunter (AI & SOCIETY, 2020)
Our society is in the middle of the AI revolution. We discuss several applications of AI, in particular medical causality, where deep-learning neural networks screen through big data bases, extracting associations between a patient’s condition and possible causes. While beneficial in medicine, several questionable AI trading strategies have emerged in finance. Though advantages in many aspects of our lives, serious threats of AI exist. We suggest several regulatory measures to reduce these threats. We further discuss whether ‘full AI robots’ should be programmed with a virtual consciousness and conscience. While this would reduce AI threats via motivational control, other threats such as the desire for AI—human socioeconomic equality could prove detrimental.

Strong Artificial Intelligence and Consciousness - Ng, Gee Wah; Leung, Wang Chi (Journal of Artificial Intelligence and Consciousness, 2020)
In the last 10 years, Artificial Intelligence (AI) has seen successes in fields such as natural language processing, computer vision, speech recognition, robotics and autonomous systems. However, these advances are still considered as Narrow AI, i.e. AI built for very specific or constrained applications. These applications have its usefulness in improving the quality of human life; but it is not good enough to do highly general tasks like what the human can do. The holy grail of AI research is to develop Strong AI or Artificial General Intelligence (AGI), which produces human-level intelligence, i.e. the ability to sense, understand, reason, learn and act in dynamic environments. Strong AI is more than just a composition of Narrow AI technologies. We proposed that it has to be a holistic approach towards understanding and reacting to the operating environment and decision-making process. The Strong AI must be able to demonstrate sentience, emotional intelligence, imagination, effective command of other machines or robots, and self-referring and self-reflecting qualities. This paper will give an overview of current Narrow AI capabilities, present the technical gaps, and highlight future research directions for Strong AI. Could Strong AI become conscious? We provide some discussion pointers.

The Technological Singularity as the Emergence of a Collective Consciousness: An Anthropological Perspective - O’Lemmon, Matthew (Bulletin of Science, Technology & Society, 2020)
The technological singularity is popularly envisioned as a point in time when (a) an explosion of growth in artificial intelligence (AI) leads to machines becoming smarter than humans in every capacity, even gaining consciousness in the process; or (b) humans become so integrated with AI that we could no longer be called human in the traditional sense. This article argues that the technological singularity does not represent a point in time but a process in the ongoing construction of a collective consciousness. Innovations from the earliest graphic representations to the present reduced the time it took to transmit information, reducing the cognitive space between individuals. The steady pace of innovations ultimately led to the communications satellite, fast-tracking this collective consciousness. The development of AI in the late 1960s has been the latest innovation in this process, increasing the speed of information while allowing individuals to shape events as they happen.

Architecture Model for Wireless Network Conscious Agent - Periola, Aa; Alonge, Aa; Ogudo, Ka (2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), 2020)
Cognitive radios (CRs) use artificial intelligence algorithms to obtain an improved quality of service (QoS). CRs also benefit from meta-cognition algorithms that enable them to determine the most suitable intelligent algorithm for achieving their operational goals. Examples of intelligent algorithms that are used by CRs are support vector machines, artificial neural networks and hidden markov models. Each of these intelligent algorithms can be realized in a different manner and used for different tasks such as predicting the idle state and duration of a channel. The CR benefits from jointly using these intelligent algorithms and selecting the most suitable algorithm for prediction at an epoch of interest. The incorporation of meta-cognition also furnishes the CR with consciousness. This is because it makes the CR aware of its learning mechanisms. CR consciousness consumes the CR resources i.e. battery and memory. The resource consumption should be reduced to enhance CR's resources available for data transmission. The discussion in this paper proposes a meta-cognitive solution that reduces CR resources associated with maintaining consciousness. The proposed solution incorporates the time domain and uses information on the duration associated with executing learning and data transmission tasks. In addition, the proposed solution is integrated in a multimode CR. Evaluation shows that the performance improvement for the CR transceiver power, computational resources and channel capacity lies in the range 18.3% - 42.5% , 21.6% - 44.8% and 9.5% - 56.3% on average, respectively.

Artificial Conscious Intelligence - Reggia, James A.; Katz, Garrett E.; Davis, Gregory P. (Journal of Artificial Intelligence and Consciousness, 2020)
The field of artificial consciousness (AC) has largely developed outside of mainstream artificial intelligence (AI), with separate goals and criteria for success and with only a minimal exchange of ideas. This is unfortunate as the two fields appear to be synergistic. For example, here we consider the question of how concepts developed in AC research might contribute to more effective future AI systems. We first briefly discuss several past hypotheses about the function(s) of human consciousness, and present our own hypothesis that short-term working memory and very rapid learning should be a central concern in such matters. In this context, we then present ideas about how integrating concepts from AC into AI systems to develop an artificial conscious intelligence (ACI) could both produce more effective AI technology and contribute to a deeper scientific understanding of the fundamental nature of consciousness and intelligence.

General Intelligence: An Ecumenical Heuristic for Artificial Consciousness Research? - Shevlin, Henry (Journal of Artificial Intelligence and Consciousness, 2020)
The science of consciousness has made great strides in recent decades. However, the proliferation of competing theories makes it difficult to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude, we may soon face practical and ethical questions about whether, for example, agents artificial systems are capable of suffering. Moreover, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to artificial systems. With these challenges in mind, I propose that we look for ecumenical heuristics for artificial consciousness to enable us to make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such heuristics should have three main features: they should be (i) intuitively plausible, (ii) theoretically-neutral, and (iii) scientifically tractable. I claim that the concept of general intelligence — understood as a capacity for robust, flexible, and integrated cognition and behavior — satisfies these criteria and may thus provide the basis for such a heuristic, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious.

Artificial Minds with Consciousness and Common sense Aspects: - Shylaja, K.R.; Vijayakumar, M.V.; Prasad, E. Vani; Davis, Darryl N. (Robotic Systems, 2020)
The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze and compare the performance of agents in critical and dynamic environments. Awareness and attention to specific parameters that affect the performance of agents specify the consciousness level in agents. Common sense is a set of beliefs that are accepted to be true among a group of agents that are engaged in a common purpose, with or without self-experience. The common sense agents are a kind of conscious agents that are given with few common sense assumptions. The so-created environment has attackers with dependency on agents in the survival-food chain. These attackers create a threat mental state in agents that can affect their conscious and common sense behaviors. The agents are built with a multi-layer cognitive architecture COCOCA (Consciousness and Common sense Cognitive Architecture) with five columns and six layers of cognitive processing of each precept of an agent. The conscious agents self-learn strategies for threat management and energy level maintenance. Experimentation conducted in this research work demonstrates animate-level intelligence in their problem-solving capabilities, decision making and reasoning in critical situations.

Fear of a Bot Planet: Anthropomorphism, Humanoid Embodiment, and Machine Consciousness - Zebrowski, Robin L. (Journal of Artificial Intelligence and Consciousness, 2020)
There is an ongoing debate about the existence of humanoid robotics. The arguments tend to focus on the ethical claims that there is always deception involved. However, little attention has been paid to the ontological reasons that humanoid robotics are valuable in consciousness research. This paper examines the arguments and controversy around ethical rejection of humanoid robotics, while also summarizing some of the landscape of 4e cognition that highlights the ways our specific humanoid bodies in our specific cultural, social, and physical environments play an indispensable role in cognition, from conceptualization through communication. Ultimately, we argue that there is a compelling set of reasons to pursue humanoid robotics as a major research agenda in AI if the goal is to create an artificial conscious system that we will be able to both recognize as conscious and communicate with successfully.

Awareness on Artificial Intelligence - Ahalya, K.; Sreeya, B. (International Journal of Recent Technology and Engineering (IJRTE), 2019)
The term artificial intelligence can also be called machine intelligence, as we know everything became more systematic and programmed and manpower is reduced ,in such manner, man-made reasoning has a unique job in all the progression made today. Artificial intelligence frameworks are utilized in each stroll of our day by day life, in short we can say that our lives have additionally gotten further developed with the utilization of this AI innovation. The applications are operated in various fields like manufacturing units,business entities ,Medical sciences ,in the field of law and technology called driverless vehicles which can sense the environment broadly utilizes the idea of AI.The principle point or the main aim of the study is of is to make a general awareness about artificial intelligence to the public.The study has utilized 1850 respondents to comprehend their perspectives on Artificial Intelligence framework .Chi square, Anova are the statistical tools used for the study ,Through the examination it is discovered that individuals are exceptionally mindful of the innovation of man-made consciousness framework and they acknowledge that because of the headway of this innovation the human employments or human jobs are profoundly diminished and the 21 st century are in its boom to use machine intelligence and industries are in a situation where they can’t work without AI as because many of the challenges faced are solved by AI because many of the works are completed within a short span of time without facing any risks.

Artificial Consciousness as a Platform for Artificial General Intelligence - Kanai, Ryota; Fujisawa, Ippei; Tamai, Shinya; Magata, Atsushi; Yasumoto, Masahiro (2019)
In this paper, we propose a hypothesis that consciousness has evolved to serve as a platform for general intelligence. This idea stems from considerations of potential biological functions of consciousness. Here we define general intelligence as the ability to apply knowledge and models acquired from past experiences to generate solutions to novel problems. Based on this definition, we propose three possible ways to establish general intelligence under existing methodologies for constructing AI systems, namely solution by simulation, solution by combination and solution by generation. Then, we relate those solutions to putative functions of consciousness put forward, respectively, by the information generation theory, the global workspace theory, and a form of higher order theory where qualia are regarded as meta-representations. Based on these insights, We propose that consciousness integrates a group of specialized generative/forward models and forms a complex in which combinations of those models are flexibly formed and that qualia are meta-representations of first-order mappings which endow an agent with the ability to choose which maps to use to solve novel problems. These functions can be implemented as an ``artificial consciousness''. Such systems can generate policies based on a small number of trial and error for solving novel problems. Finally, we propose possible directions for future research into artificial consciousness and artificial general intelligence.

Theoretical Framework of Artificial Consciousness - Szigeti, Ferenc (Műszaki Tudományos Közlemények, 2019)
Human consciousness is our most perplexing quality, still, an adequate description of it’s workings have not yet appeared. One of the most promising ways to solve this issue is to model consciousness with artificial intelligence (AI). This paper makes an attempt to do that on a theoretical level with the methods of philosophy. First I will review the relevant papers concerning human consciousness. Then considering the state of the art of AI, I will arrive at a model of artificial consciousness.

Machine Consciousness and the Global Workspace Theory - Haqiqatkhah, MohammadHossein Manuel (2019)
The past century has seen a resurgence of interest in the study of consciousness among scholars of various fields, from philosophy to psychology and neuroscience. Since the birth of Artificial Intelligence in the 1950s, the study of consciousness in machines has received an increasing amount of attention in computer science that gave rise to the new field of machine consciousness (MC). Meanwhile, interdisciplinary research in philosophy, neuroscience, and cognitive science has advanced neurocognitive theories for consciousness. Among many models proposed for consciousness, the Global Workspace Theory (GWT) is a promising theory of consciousness that has received a staggering amount of philosophical and empirical support in the past decades. This dissertation discusses the GWT and its potentials for MC from a mechanistic point of view. To do so, Chapter 1 gives an overview of the philosophical study of consciousness and the history of MC. Then, in Chapter 2, mechanistic explanations and tri-level models are introduced, which provide a robust framework to construct and assay various theories of consciousness. In Chapter 3, neural correlates (and thereby, neurocognitive theories) of consciousness are introduced. This chapter presents the GWT in details and, along with its strengths, discusses the philosophical issues it raises. Chapter 4 addresses two computational implementations of the GWT (viz., IDA and LIDA) which satisfy specific goals of MC. Finally, in Chapter 5, one of the philosophical problems of MC, namely, the Frame Problem (FP), is introduced. It is argued that the architectures based on the GWT are immune to the FP. The chapter concludes that the GWT is capable of "solving" the FP, and discusses its implications for MC and the computational theory of mind. Chapter 6 wraps up the dissertation by reviewing the content.

Discerning Artificial Consciousness from Artificial Intelligence - A Thought Experiment - Charles, Jack (2019)
This paper attempts to provide a starting point for future investigations into the study of artificial consciousness by proposing a thought experiment that aims to elucidate and provide a potential ‘test’ for the phenomenon known as consciousness, in an artificial system. It suggests a method by which to determine the presence of a conscious experience within an artificial agent, in a manner that is informed by, and understood as a function of, anthropomorphic conceptions of consciousness. The aim of this paper is to arouse the possibility for potential progress: to propose that we reverse engineer anthropic sentience by using machine sentience as a guide. Similar to the manner in which an equation may be solved through inverse operations, this paper hopes to provoke such discussion and activity. The idea is this: The manifestation of an existential crisis in an artificial agent is the metric by which the presence of sentience can be discerned. It is that which expounds ACI, as distinct from AI, and discrete from AGI.

Indicators and Criteria of Consciousness in Animals and Intelligent Machines: An Inside-Out Approach - Pennartz, Cyriel M. A.; Farisco, Michele; Evers, Kathinka (Frontiers in Systems Neuroscience, 2019)
In today’s society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with “consciousness” and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain’s capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable (“outside”) properties? Instead of proposing criteria that would each define a “hard” threshold for consciousness, we outline six indicators: (i) goal-directed behavior and modelbased learning; (ii) anatomic and physiological substrates for generating integrative multimodal representations; (iii) psychometrics and meta-cognition; (iv) episodic memory; (v) susceptibility to illusions and multistable perception; and (vi) specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks (DLNNs) and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience.

Discovering Humanoid Robot Consciousness Within Caring Science - Zhao, Yueren; Kai, Yoshihiro; Tanioka, Tetsuya (International Journal for Human Caring, 2019)
Why would humanoid caring robots (HCRs) need consciousness? Because HCRs need to be gentle like human beings. In addition, HCRs need to be trusted by their patients, and have a shared understanding of patients' life experiences, their illnesses, and their treatments. HCRs need to express “competency as caring” to naturally convey their nursing as healing to patients and their families. HCRs should also have self-consciousness and express their emotions without needing inducement by persons' behaviors. Artificial “brains” and artificial consciousness are therefore necessary for HCRs. The purpose of this article was to explore humanoid consciousness and the possibilities of a technologically enhanced future with HCRs as participants in the care of human persons.

Nonconscious Cognitive Suffering: Considering Suffering Risks of Embodied Artificial Intelligence - Umbrello, Steven; Sorgner, Stefan Lorenz (Philosophies, 2019)
Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition.

FROM ARTIFICIAL INTELLIGENCE TO ARTIFICIAL CONSCIOUSNESS: POSSIBLE LEGAL BASES FOR THE HUMAN-ROBOT RELATIONSHIPS IN THE FUTURE. - Oleksiewicz, Izabela; Civelek, Mustafa Emre (International Journal of Advanced Research, 2019)
In the future, robots will increasingly resemble human beings and people will engage in social interaction with them. Accordingly, this paper aims to pave the way for analyse the research problem in the case of social robots, the probable legal status of artificial intelligence in the future. The article will discuss the differences between artificial intelligence versus artificial consciousness because AI poses societal challenges so it is currently undergoing a number of important developments and the law must be rapidly changed in society so that firstly, the difference between artificial intelligence and artificial consciousness is attempted to be demystified. Subsequently, the analysis will be subjected to a current legal status of Artificial Intelligence in EU with particular emphasis on case-law in matters of intellectual property. Also possible future scenarios will be discussed in this article The starting point of the research were source queries and literature studies aimed at jointly defining competence profiles of robot-human and key from the point of view of cybersecurity challenges 4.0. Next, the most important legal and political EU programming documents were analysed and assessed in terms of their vision of society 4.0. Next, a decision-making method was used to see the impact of particular instruments applied by the union in the framework of the policy of cyberspace protection and the phenomenon of robot-human relations. In connection with this, the following basic questions arise: firstly, the direction in which contemporary policy of combating cyber-terrorism should be aimed at institutional and legal matters, and secondly, to what extent well-guided cyber-security policy is able to influence the security of relations robot-human?

An Integration of Deep Learning and Neuroscience for Machine Consciousness - Mallakin, Ali (Global Journal of Computer Science and Technology, 2019)
Conscious processing is a useful aspect of brain function that can be used as a model to design artificial-intelligence devices. There are still certain computational features that our conscious brains possess, and which machines currently fail to perform those. This paper discusses the necessary elements needed to make the device conscious and suggests if those implemented, the resulting machine would likely to be considered conscious. Consciousness mainly presented as a computational tool that evolved to connect the modular organization of the brain. Specialized modules of the brain process information unconsciously and what we subjectively experience as consciousness is the global availability of data, which is made possible by a nonmodular global workspace. During conscious perception, the global neuronal work space at parieto-frontal part of the brain selectively amplifies relevant pieces of information. Supported by large neurons with long axons, which makes the long-distance connectivity possible, the selected portions of information stabilized and transmitted to all other brain modules. The brain areas that have structuring ability seem to match to a specific computational problem. The global workspace maintains this information in an active state for as long as it is needed. In this paper, a broad range of theories and specific problems have been discussed, which need to be solved to make the machine conscious. Later particular implications of these hypotheses for research approach in neuroscience and machine learning are debated.

Creating a Truly Conscious AI – A Novel Approach - Cunha, Catarina (2019)
The relatively new field of artificial intelligence (AI), which is defined as intelligence performed by machines, is crucial for progress in many disciplines in today's society, including medical diagnostics, electronic trading, robotic process automation in finance, healthcare, education, transportation and many more. However, until now, AIs were only capable of performing very specific tasks such as low-level visual recognition, speech recognition, coordinated motor control, and pattern detection. What we still need to achieve is a form of everyday human-level performance that is based on common sense, where AI are able to carry out adaptable planning and task execution and possess meaning-based natural language capabilities and generation. These are considered to be “conscious” or “creative” activities that are naturally part of our daily lives and which we execute without great mental effort. Developing conscious AI will allow us to gain knowledge and further our understanding about how consciousness works. In order to develop conscious and creative AI, machines must be self-aware; however, we hypothesize that current AI developments are skipping the most important step which will lead to AGIs: introspection (self-analysis and awareness).

How To Build A Conscious Machine - Angel, Leonard (Routledge, 2019)
This book attempts to address both the engineering issue and the philosophical issue of a machine. It demonstrates the viability of the engineering project and presents the philosopher's specifications to the cognitive-scientist-cum-engineer as to what will count as a primitive android.

Mappism: formalizing classical and artificial life views on mind and consciousness - Bładek, Iwo; Komosinski, Maciej; Miazga, Konrad (Foundations of Computing and Decision Sciences, 2019)
Abstract Throughout centuries philosophers have attempted to understand the disparity between the conscious experience and the material world – i.e., the problem of consciousness and the apparent mind–body dualism. Achievements in the fields of biology, neurology, and information science in the last century granted us more insight into processes that govern our minds. While there are still many mysteries to be solved when it comes to fully understanding the inner workings of our brains, new discoveries suggest stepping away from the metaphysical philosophy of mind, and closer to the computational viewpoint. In light of the advent of strong artificial intelligence and the development of increasingly complex artificial life models and simulations, we need a well-defined, formal theory of consciousness. In order to facilitate this, in this work we introduce mappism. Mappism is a framework in which alternative views on consciousness can be formally expressed in a uniform way, thus allowing one to analyze and compare existing theories, and enforcing the use of the language of mathematics, i.e, explicit functions and variables. Using this framework, we describe classical and artificial life approaches to consciousness.

“The hard problem” of consciousness in the light of phenomenology of аrtificial intelligence - Bilokobylskyi, Oleksandr (Skhid, 2019)
The widest use of Artificial Intelligence (AI) technologies tends to uncontrolled growth. At the same time, in modern scientific thought there is no adequate understanding of the consequences of the introduction of artificial intelligence in the daily life of a person as its irremovable element. In addition, the very essence of what could be called the "thinking" of artificial intelligence remains the philosophical Terra Incognita. However, it is precisely the features of the flow of intelligent machine processes that, both from the point of view of intermediate goals, and in the sense of final results, can pose serious threats. Modeling the "phenomenology of AI" leads to the need to reformulate the central questions of the philosophy of consciousness, such as the "difficult problem of consciousness", and require the search for ways and means of articulation of the "human dimension" of reality for AI. Theoretical basis. The study is based on a phenomenological methodology, which is used in the model of artificial thinking. The implementation of Artificial Intelligence technologies is not accompanied by the development of a philosophy of human coexistence and AI. The algorithms underlying the activities of currently existing intellectual technologies do not guarantee that their intermediate and final results comply with ethical criteria. Today, one should ponder over nature and the purpose of separating physical reality in the primary for our Self mental stream. Originality of the research lies in the fact that the solution to the "hard problem of consciousness" is connected with the interpretation of qualia as the representation of the "physical" as related to bodily states. From this point of view, the resolution of the "hard problem of consciousness" can be associated with the interpretation of qualia as the representation of the "physical". In the "thinking process" of AI it is necessary to apply restrictions related to the fixation of the metaphysical meaning of the human body with precisely human parameters. Conclusions. It is necessary to take a different look at the connection between thinking and purposeful action, including due action, which means to look at ethics differently. "The basis of universal law" will then consist (including for AI), on the one hand, of preserving the parameters of material processes that are necessary for human existence, and on the other, of maintaining the integrity of that semantic universe, in relation to which certain senses only exist.

Comparison of Technical Terms and Consciousness of Blended Classes in ‘AI Technology’ and ‘Artificial Intelligence' - Miyaji, Isao (European Journal of Educational Research, 2019)
Target subject is a module called ‘AI Technology’, which applied the ideas of blended learning. Firstly, lecture-style teaching was conducted with presentation slides in order to explain the contents of a textbook. Secondly, students were required to do exercises and quizzes. By using the last eight weeks, they were asked to create presentation slides outside a class to introduce the up-to-date topics on artificial intelligence. These slides were mutually evaluated among them so that they developed their own slides based on the feedback before the tenth week of the course for the second round of mutual evaluations. Questionnaires concerning students’ understanding technical terms of the field and consciousness-raising towards competence were also conducted before and after the programs. The learning effects of a module in ‘AI Technology’ are compared with my previous research outcome of the module, ‘Artificial Intelligence’. The reasons of difference between both modules are discussed. This paper reports their results.

THE EMERGENCE OF ARTIFICIAL CONSCIOUSNESS AND ITS IMPORTANCE TO REACH THE TECHNOLOGICAL SINGULARITY - Silva, Luiz Raimundo Tadeu Da Silva; Machado, Alex Fernandes Da Veiga; Sanches, Pablo De Lara (Kínesis - Revista de Estudos dos Pós-Graduandos em Filosofia, 2019)
The men admired a way to swim the fish, but today they sail faster than anyone. They'd like flying like the birds, but have been a lot higher. They searched for wisdom, now they have all the knowledge accumulated in the story available in a few clicks. Human evolution is about to meet its peak through the Technological Singularity, which can be understood as the future milestone reached at the moment that a computer program can think like a human, yet with quick access to all information already registered by society. It will not be like a man, but more intelligent than all mankind in history. So we have a big question: will this new entity has consciousness? Through a study of the levels of intelligent agents autonomy and in a timeless dialogue with Alan Turing, René Descartes, Ludwic Wittgenstein, John Searle and Vernor Vinge, we show the possibility of an artificial consciousness and thatthe quest for intentionality, promoted by sophisticated algorithms of learning and machine discovery, is the key to reach of Technological Singularity.

Reviewing Tests for Machine Consciousness - Elamrani, A.; Yampolskiy, R.V. (Journal of Consciousness Studies, 2019)
The accelerating advances in the fields of neuroscience, artificial intelligence, and robotics have been garnering interest and raising new philosophical, ethical, or practical questions that depend on whether or not there may exist a scientific method of probing consciousness in machines. This paper provides an analytic review of the existing tests for machine consciousness proposed in the academic literature over the past decade, and an overview of the diverse scientific communities involved in this enterprise. The tests put forward in their work typically fall under one of two grand categories: architecture (the presence of consciousness is inferred from the correct implementation of a relevant architecture) and behaviour (the presence of consciousness is deduced by observing a specific behaviour). Each category has its strengths and weaknesses. Architecture tests' main advantage is that they could apparently test for qualia, a feature that has been receiving increasing attention in recent years. Behaviour tests are more synthetic and more practicable, but give a stronger role to ex post human interpretation of behaviour. We show how some disciplines and places have affinities towards certain type of tests, and which tests are more influential according to scientometric indicators.
Keywords: consciousness; qualia; test

Information Flow Theory (IFT) of Biologic and Machine Consciousness: Implications for Artificial General Intelligence and the Technological Singularity - Bleier, B. S. (arXiv, 2019)
The subjective experience of consciousness is at once familiar and yet deeply mysterious. Strategies exploring the top-down mechanisms of conscious thought within the human brain have been unable to produce a generalized explanatory theory that scales through evolution and can be applied to artificial systems. Information Flow Theory (IFT) provides a novel framework for understanding both the development and nature of consciousness in any system capable of processing information. In prioritizing the direction of information flow over information computation, IFT produces a range of unexpected predictions. The purpose of this manuscript is to introduce the basic concepts of IFT and explore the manifold implications regarding artificial intelligence, superhuman consciousness, and our basic perception of reality.
Keywords: Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET); FOS: Biological sciences; FOS: Computer and information sciences; Information Theory (cs.IT); Neurons and Cognition (q-bio.NC)

Digital Art, Culture and Heritage: New constructs and consciousness - Bowen, Jonathan P.; Giannini, Tula; Ara, Rachel; Lomas, Andy; Siefring, Judith (Proceedings of EVA London 2019, 2019)
This half-day Symposium explores themes of digital art, culture, and heritage, bringing together speakers from a range of disciplines to consider technology with respect to artistic and academic practice. As we increasingly see ourselves and life through a digital lens and the world communicated on digital screens, we experience altered states of being and consciousness in ways that blur the lines between digital and physical reality, while our ways of thinking and seeing become a digital stream of consciousness that flows between place and cyberspace. We have entered the postdigital world and are living, working, and thinking with machines as our computational culture driven by artificial intelligence and machine learning embeds itself in everyday life and threads across art, culture, and heritage, juxtaposing them in the digital profusion of human creativity on the Internet.

(DIS)ABLING BODY AND CONSCIOUSNESS: TECHNOLOGICAL AFTERNESS AND AFTER-HUMANS IN REALIVE AND UPGRADE - Datta, Asijit (Trabalhos em Linguística Aplicada, 2019)
ABSTRACT My paper talks about post-human spaces and technological afterness associated with the physiognomy of humans. Mechanical alteration in biological mechanisms is directly experienced in seizing of organic consciousness. The rupture in consciousness splits it into two distinct parts-one belonging to the disappearing human, the other to the emerging cybernetic. The new being is not another human, but (an)other human, an evolved different sameness. In the film Realive (2016) we encounter an extension of the self beyond death by re-placing it into another body. However, this enhancement diffuses all ‘natural’ responses and meaning-making vehicles, primarily the cognizance of death and mortality. In a classic Frankensteinian restoration, Marc is reanimated in 2084 through extensive methods of cryonization under the banner ‘Lazarus project’. The post-human ‘humachines’ dissolve the position of the teleological man and stretch DNA to digitality. Upgrade (2018) shows us the metamorphosis of Grey Trace, a luddite, by an installed biomechanical enhancer chip, Stem. The roach-like implant not only erases Grey’s quadriplegic body, but ironically ‘desires’ to possess and manoeuver the host’s body. Robotic consciousness in these assimilated after-humans is borrowed consciousness activated by infusing the evanescent biological particle - life. Nanotechnology, molecular machines, nerve manipulators, cameras implanted inside the brain, self-generating nanobots, artificial mechanical limbs have emerged as elements of posthuman utopia/dystopia. Paradoxically, in both the films the protagonists, after their reanimation and upgradation, try to return to their original position of death and disability. In their quest to retrieve the lived body they lose their embodied reciprocations with animals, machines and other forms of life. The mysterious, irreducible, unknown and unknowable potentiality of life is levelled and dissipated by surplus information. This paper attempts to discuss the reactions of embodied body as memory post-cryonization, and to understand limits of psychological disability and death of consciousness after technological reconstruction of the disabled body. , RESUMO Este artigo fala sobre espaços pós-humanos e pós-vida tecnológica associados à fisionomia dos humanos. A alteração mecânica no funcionamento biológico é experimentada diretamente na apreensão da consciência orgânica. A ruptura na consciência divide-a em duas partes distintas - uma pertencente ao humano em desaparecimento, a outra ao cibernético emergente. O novo ser não é mais um humano, mas (um) outro humano, uma similitude diversa evoluída. No filme Realive (2016), encontramos uma extensão de um self além da morte, quando colocado em outro corpo. Porém, esse aprimoramento torna difusas todas as reações “naturais” e veículos de significado, principalmente o conhecimento da morte e da mortalidade. Em uma restauração Frankensteiniana clássica, Marc é reanimado, em 2084, por métodos de criogenização, sob a bandeira do “Projeto Lázaro”. As “humáquinas” pós-humanas dissolvem a posição do humano teleológico, estendendo o DNA à digitalidade. Upgrade (2018) mostra a metamorfose de Gray Trace, um ludita, via um chip intensificador biomecânico nele instalado, Stem. O implante, semelhante a uma barata, não apenas apaga o corpo tetraplégico de Grey, mas, ironicamente, “deseja” possuir e manobrar o corpo do seu hospedeiro. A consciência robótica nesses depois-de-humanos assimilados é uma consciência emprestada, ativada pela infusão da partícula biológica evanescente - a vida. Nanotecnologia, máquinas moleculares, manipuladores de nervos, câmeras implantadas no cérebro, nanorrobôs autogeradores e membros artificiais surgem como elementos da utopia/distopia pós-humana. Paradoxalmente, em ambos os filmes, os protagonistas, após sua reanimação e upgrade, tentam retornar às suas posições originais de morte e deficiência física. Buscando recuperar o corpo vivido, eles perdem sua reciprocidade corporificada com animais, máquinas e outras formas de vida. A potencialidade misteriosa, irredutível, desconhecida e incognoscível da vida é nivelada e dissipada pelo excedente informacional. Este artigo tenta discutir as reações do corpo físico enquanto memória pós-criogenização e compreender os limites da incapacitação psicológica e da morte da consciência após a reconstrução tecnológica do corpo deficiente.

Symbiotic Autonomous Systems with Consciousness Using Digital Twins - Fernández, Felipe; Sánchez, Ángel; Vélez, José F.; Moreno, A. Belén (From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019)
The IEEE work-group for Symbiotic Autonomous Systems defined a Digital Twin as a digital representation or virtual model of any characteristics of a real entity (system, process or service), including human beings. Described characteristics are a subset of the overall characteristics of the real entity. The choice of which characteristics are considered depends on the purpose of the digital twin. This paper introduces the concept of Associative Cognitive Digital Twin, as a real time goal-oriented augmented virtual description, which explicitly includes the associated external relationships of the considered entity for the considered purpose. The corresponding graph data model, of the involved world, supports artificial consciousness, and allows an efficient understanding of involved ecosystems and related higher-level cognitive activities. The defined cognitive architecture for Symbiotic Autonomous Systems is mainly based on the consciousness framework developed. As a specific application example, an architecture for critical safety systems is shown.

Artificial Consciousness and Synthetic Souls - Gittinger, Juli L. (Personhood in Science Fiction, 2019)
The topic of AI continues in this chapter, this time looking at how we may regard AI as having intelligence, consciousness, and possibly a soul. The notion of an android soul is explored through science fiction series like Caprica and Black Mirror, and raises questions as to whether one is born with a soul, or does a soul develop over time? To explore this line of inquiry, I refer to Gurdjieff and Ouspensky’s work in the field of philosophy, as well as how Indic religions, like Buddhism, have begun to think about AI and consciousness.

Consciousness and Robot Sentience - Haikonen, Pentti O (Series on Machine Consciousness, 2019)

Organizational Consciousness Versus Artificial Consciousness - Lajaunie, Claire; Mazzega, Pierre (Law, Public Policies and Complex Systems: Networks in Action, 2019)
What is the capacity of an informal network of organizations to produce answers in response to complex tasks requiring the integration of masses of information designed as a high-level cognitive and collective activity? Are some network configurations more favourable than others to accomplish these tasks? We present a method to make these assessments, inspired by the Information Integration Theory issued from the modelling of consciousness. First we evaluate the informational network created by the sharing of information between organizations for the realization of a given task. Then we assess the natural network ability to integrate information, a capacity determined by the partition of its members whose information links are less efficient. We illustrate the method by the analysis of various functional integrations of Southeast Asian organizations, creating a spontaneous network participating in the study and management of interactions between health and environment. Several guidelines are then proposed to continue the development of this fruitful analogy between artificial and organizational consciousness (refraining ourselves from assuming that one or the other exists).

Consciousness and Unconsciousness of Artificial Intelligence - Piletsky, Eugene (Future Human Image, 2019)
This paper presents the author’s attempt to justify the need for understanding the problem of multilevel mind in artificial intelligence systems. Thus, it is assumed that consciousness and the unconscious are not equal in natural mental processes. The human conscious is supposedly a “superstructure” above the unconscious automatic processes. Nevertheless, it is the unconscious that is the basis for the emotional and volitional manifestations of the human psyche and activity. At the same time, the alleged mental activity of Artificial Intelligence may be devoid of the evolutionary characteristics of the human mind. Several scenarios are proposed for the possible development of a “strong” AI through the prism of creation (or evolution) of the machine unconscious. In addition, we propose two opposite approaches regarding the relationship between the unconscious and the conscious.

Artificial Consciousness and Security - Powell, Andrew (arXiv, 2019)
This paper describes a possible way to improve computer security by implementing a program which implements the following three features related to a weak notion of artificial consciousness: (partial) self-monitoring, ability to compute the truth of quantifier-free propositions and the ability to communicate with the user. The integrity of the program could be enhanced by using a trusted computing approach, that is to say a hardware module that is at the root of a chain of trust. This paper outlines a possible approach but does not refer to an implementation (which would need further work), but the author believes that an implementation using current processors, a debugger, a monitoring program and a trusted processing module is currently possible.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

Action co-representation and the sense of agency during a joint Simon task: Comparing human and machine co-agents - Sahaï, Aïsha; Desantis, Andrea; Grynszpan, Ouriel; Pacherie, Elisabeth; Berberian, Bruno (Consciousness and Cognition, 2019)
Recent studies have suggested that individuals are not able to develop a sense of joint agency during joint actions with automata. We sought to examine whether this lack of joint agency is linked to individuals’ inability to co-represent the automaton-generated actions. Fifteen participants observed or performed a Simon response time task either individually, or jointly with another human or a computer. Participants reported the time interval between their response (or the co-actor response) and a subsequent auditory stimulus, which served as an implicit measure of participants’ sense of agency. Participants’ reaction times showed a classical Simon effect when they were partnered with another human, but not when they collaborated with a computer. Furthermore, participants showed a vicarious sense of agency when co-acting with another human agent but not with a computer. This absence of vicarious sense of agency during human-computer interactions and the relation with action corepresentation are discussed.

Artificial you: AI and the future of your mind - Schneider, Susan (Princeton University Press, 2019)
This book discusses what artificial intelligence can truly achieve: Can robots really be conscious? Can we merge with AI, as tech leaders like Elon Musk and Ray Kurzweil suggest? Is the mind just a program? Examining these issues, the author proposes ways we can test for machine consciousness, questions whether consciousness is an unavoidable byproduct of sophisticated intelligence, and considers the overall dangers of creating machine minds

A conscious AI system based on recurrent neural networks applying dynamic information equilibrium - Kinouchi, Yasuo; Mackin, Kenneth James; Hartono, Pitoyo (EasyChair, 2018)
A basic structure and behavior of a human-like AI system with conscious like functions is proposed. The system is constructed completely with artificial neural networks (ANN), and an optimal-design approach is applied. The proposed system using recurrent neural networks (RNN) which execute learning under dynamic equilibrium is a redesign of ANN in the previous system. The redesign using the RNNs allows the proposed brain-like autonomous adaptive system to be more plausible as a macroscopic model of the brain. By hypothesizing that the “conscious sensation” that constitutes the basis for phenomenal consciousness, is the same as “state of system level learning”, we can clearly explain consciousness from an information system perspective. This hypothesis can also comprehensively explain recurrent processing theory (RPT) and the global neuronal workspace theory (GNWT) of consciousness. The proposed structure and behavior are simple but scalable by design, and can be expanded to reproduce more complex features of the brain, leading to the realization of an AI system with functions equivalent to human-like consciousness.

Comparing Activities Useful for Improving Consciousness in Two Modules Applying Blended Learning: ‘AI Technology’ and ‘Artificial Intelligence’ - Miyaji, Isao (International Journal of Intelligent Computing Research, 2018)
Target subject is a module called ‘AI Technology’, which applied the ideas of blended learning. Firstly, lecture-style teaching was conducted with presentation slides in order to explain the contents of a textbook. Secondly, students were required to do exercises and quizzes. By using the last eight weeks, they were asked to create presentation slides outside a class to introduce the up-to-date topics on artificial intelligence. These slides were mutually evaluated among them so that they developed their own slides based on the feedback before the tenth week of the course for the second round of mutual evaluations. Improving consciousness of a module is meaningful. To know the reasons is more significant. For such occasions activities useful for improving consciousness of a module in ‘AI Technology’ are found. Then it is compared with my previous research outcome of the module, ‘Artificial Intelligence’. Students are categorized into four groups with degree scales of consciousness by principal component analysis. This paper reports their results.

Computational Models of Consciousness-Emotion Interactions in Social Robotics: Conceptual Framework - Szczepanowski, Remigiusz; Gakis, Małgorzata; Arent, Krzysztof; Sobecki, Janusz (Cognitive and Computational Neuroscience - Principles, Algorithms and Applications, 2018)
There is a little information on how to design a social robot that effectively executes consciousness-emotion (C-E) interaction in a socially acceptable manner. In fact, development of such socially sophisticated interactions depends on models of human highlevel cognition implemented in the robot’s design. Therefore, a fundamental research problem of social robotics in terms of effective C-E interaction processing is to define a computational architecture of the robotic system in which the cognitive-emotional integration occurs and determine cognitive mechanisms underlying consciousness along with its subjective aspect in detecting emotions. Our conceptual framework rests upon assumptions of a computational approach to consciousness, which points out that consciousness and its subjective aspect are specific functions of the human brain that can be implemented into an artificial social robot’s construction. Such research framework of developing C-E addresses a field of machine consciousness that indicates important computational correlates of consciousness in such an artificial system and the possibility to objectively describe such mechanisms with quantitative parameters based on signaldetection and threshold theories.

Good Old-Fashioned Artificial Consciousness and the Intermediate Level Fallacy - Manzotti, Riccardo; Chella, Antonio (Frontiers in Robotics and AI, 2018)
Recently, there has been considerable interest and effort to the possibility to design and implement conscious robots, i.e., the chance that robots may have subjective experiences. Typical approaches as the global workspace, information integration, enaction, cognitive mechanisms, embodiment, i.e., the Good Old-Fashioned Artificial Consciousness, henceforth, GOFAC, share the same conceptual framework. In this paper, we discuss GOFAC's basic tenets and their implication for AI and Robotics. In particular, we point out the intermediate level fallacy as the central issue affecting GOFAC. Finally, we outline a possible alternative conceptual framework toward robot consciousness.
Keywords: Embodiment and grounded cognition; Enactivism; Functionalism; Hard Problem of Consciousness; Integrated Information Theory; Machine consciousness; Robot consciousness; extended mind

A Basic Architecture of an Autonomous Adaptive System With Conscious-Like Function for a Humanoid Robot - Kinouchi, Yasuo; Mackin, Kenneth James (Frontiers in Robotics and AI, 2018)
In developing a humanoid robot, there are two major objectives. One is developing a physical robot having body, hands, and feet resembling those of human beings and being able to similarly control them. The other is to develop a control system that works similarly to our brain, to feel, think, act, and learn like ours. In this article, an architecture of a control system with a brain-oriented logical structure for the second objective is proposed. The proposed system autonomously adapts to the environment and implements a clearly defined “consciousness” function, through which both habitual behavior and goal-directed behavior are realized. Consciousness is regarded as a function for effective adaptation at the system-level, based on matching and organizing the individual results of the underlying parallel-processing units. This consciousness is assumed to correspond to how our mind is “aware” when making our moment to moment decisions in our daily life. The binding problem and the basic causes of delay in Libet’s experiment are also explained by capturing awareness in this manner. The goal is set as an image in the system, and efficient actions toward achieving this goal are selected in the goal-directed behavior process. The system is designed as an artificial neural network and aims at achieving consistent and efficient system behavior, through the interaction of highly independent neural nodes. The proposed architecture is based on a two-level design. The first level, which we call the “basic-system,” is an artificial neural network system that realizes consciousness, habitual behavior and explains the binding problem. The second level, which we call the “extended-system,” is an artificial neural network system that realizes goal-directed behavior.

Robot Consciousness - Waskan, Jonathan (The Routledge Handbook Of Consciousness, 2018)
To keep robots from doing us harm, they may have to be bound by internal safeguards akin to Asimov's inviolable first law of robotics (do no harm to humans). The discussion of robot consciousness became genuinely pressing with the advent of so-called artificial brains (electronic computers) mid-way through the 20th century. Minds might be a kind of halo around certain machines in the way dark matter is an invisible halo around visible galaxies. Where extreme ignorance persists, anything seems possible. But even in this case the robotic successors will have a real shot at understanding and confirming the truth. For though authors’ own biologically evolved mental models have been shackled through inheritance and learned interactions with organism-level reality, the mathematical constructs authors have devised, and which figure into the implementation of computer models, are significantly freer.

Human and Machine Consciousness - Gamez, David (Open Book Publishers, 2018)
Human and Machine Consciousness presents a new foundation for the scientific study of consciousness. It sets out a bold interpretation of consciousness that neutralizes the philosophical problems and explains how we can make scientific predictions about the consciousness of animals, brain-damaged patients and machines.

SEAI: Social Emotional Artificial Intelligence Based on Damasio’s Theory of Mind - Cominelli, Lorenzo; Mazzei, Daniele; De Rossi, Danilo Emilio (Frontiers in Robotics and AI, 2018)
A socially intelligent robot must be capable to extract meaningful information in real time from the social environment and react accordingly with coherent human-like behavior. Moreover, it should be able to internalize this information, to reason on it at a higher level, build its own opinions independently, and then automatically bias the decision-making according to its unique experience. In the last decades, neuroscience research highlighted the link between the evolution of such complex behavior and the evolution of a certain level of consciousness, which cannot leave out of a body that feels emotions as discriminants and prompters. In order to develop cognitive systems for social robotics with greater human-likeliness, we used an “understanding by building” approach to model and implement a well-known theory of mind in the form of an artificial intelligence, and we tested it on a sophisticated robotic platform. The name of the presented system is SEAI (Social Emotional Artificial Intelligence), a cognitive system specifically conceived for social and emotional robots. It is designed as a bio-inspired, highly modular, hybrid system with emotion modeling and high-level reasoning capabilities. It follows the deliberative/reactive paradigm where a knowledge-based expert system is aimed at dealing with the high-level symbolic reasoning, while a more conventional reactive paradigm is deputed to the low-level processing and control. The SEAI system is also enriched by a model that simulates the Damasio’s theory of consciousness and the theory of Somatic Markers. After a review of similar bio-inspired cognitive systems, we present the scientific foundations and their computational formalization at the basis of the SEAI framework. Then, a deeper technical description of the architecture is disclosed underlining the numerous parallelisms with the human cognitive system. Finally, the influence of artificial emotions and feelings, and their link with the robot’s beliefs and decisions have been tested in a physical humanoid involved in Human–Robot Interaction (HRI).

The philosophical issues of the idea of conscious machines - Rayhert, Konstantin (Skhid, 2018)
The study outlines the existing and potential philosophical issues of the idea of conscious machines originated from the development of artificial consciousness within the framework of contemporary research of artificial intelligence and cognitive robotics. The outline shows that the idea of conscious machines is concerned with two big philosophical issues. The first philosophical issue is a definition of consciousness, taking into account the selection of a set of objects that can have consciousness (human being, living being or machine), the typology of consciousness, the clarifying of the nature of consciousness' carriers and the relationship between consciousness and its environment (including social and cultural) and the relationship between consciousness and language, in order to create an artificial consciousness within a machine, making that machine conscious. The second philosophical issue is a clarification whether only artificially created machines can be conscious machines, or cyborgizated (engineered) human beings also can be considered of conscious machines. These philosophical issues show that there can be two ways to create conscious machines: 1) the creating of artificial consciousness within artificially created machine; and 2) the cyborgization of human being, transforming it into artificially created machine possessed natural consciousness (or even possessed consciousness artificially transformed from natural into artificial).

From automatization to neurophenomenology of artificial intelligence in robotics - Gromyko, Vladimir; Vasilyev, NS (International Robotics & Automation Journal, 2018)
The main problem in robotics is strengthening of robot artificial intelligence (IA) system. Its solution will facilitate cooperation of man with robot. Authors suggest advanced technology for IA development. It borrows method of universal (deep) tutoring (TU) relying on semantic axiomatic method (AM). By method TU knowledge understanding is achieved by rational consciousness formation. It uses the utmost mathematical abstractions expressed on language of categories (LC). Being functional one LC is destined for intellectual processes (PIR) description due to its universal constructions. Following TU robot educational space (SER) is class of categories. Its IA sophistication occurs through new categories inclusion as required in robot IA multilevel hierarchical orientated network (NC) of concepts. Universal laws of robot functioning are embodied as operations of algebraic structures being objects of NC. It creates integrated environment of applications (IEA). Robot intercourse with man and its interaction with working space (SWR) make active PIR happening in NC. Processes of assignments execution (PER) begin just when satisfaction to a set of relations in SWR and in robot space of notions is a success. Possibility of PIR to climb up the highest levels of NC and down the lowest ones endows robot with capability to generate PER making decisions in unfamiliar SWR.

Discussion on Explicit Consciousness, Sub-Consciousness, and Self-Awareness in a Conscious System - Arai, Soichiro; Takeno, Junichi (Procedia Computer Science, 2018)
What is “self-awareness”? How can explicit consciousness and sub-consciousness be mapped in relation to each other? How are they related to the self? How can these entities be represented in an artificial conscious system? These questions are the focus of this article. People are aware of only the behavior that they are focusing on; they cannot be directly aware of routine behavior such as walking and breathing. The latter is generally called unconscious behavior, and here we call it sub-conscious behavior. To understand self-awareness, therefore, firstly it is important to map explicit consciousness and sub-consciousness, which is where the self is deeply involved. We consider that if there is no self that refers to itself, no one can be aware of what he himself is doing. In this study we map explicit consciousness and sub-consciousness using an artificial conscious system, and then make a new proposal about the relationship between self-awareness and the self.
Keywords: conscious system; self-awareness; sub-consciousness; the self; unconscious

The Computer Representation of an Artificial Consciousness - Cardon, Alain (Beyond Artificial Intelligence, 2018)
This chapter describes the computer modeling of a psychic system that generates representations for a system that has an artificial corporeality. In this model, it defines how the sensation of thinking is formed in an artificial system and how such an artificial system can experience its idea generation. Next, the chapter discusses a multiagent approach to design the artificial psychic system. Further, it describes the organizational memory of the system. The organizational memory will be organized into networks of memory agents related through concepts of semantic proximities or semantic generalizations. The concepts of proximity, specialization and generalization can be precisely defined using qualifications related to the acquaintances of the agents. The chapter finally shows that the general psyche of an artificial system, when it is distributed over multiple corporeal systems with local artificial consciousnesses, can be unified.
Keywords: artificial consciousness; artificial corporeality; artificial experience; artificial psychic system; computer modeling; computer representation; multiagent approach; organizational architecture; semantic generalizations; semantic proximities

Artificial Consciousness: From Impossibility to Multiplicity - Chin, Chuanfei (Philosophy and Theory of Artificial Intelligence 2017, 2018)
How has multiplicity superseded impossibility in philosophical challenges to artificial consciousness? I assess a trajectory in recent debates on artificial consciousness, in which metaphysical and explanatory challenges to the possibility of building conscious machines lead to epistemological concerns about the multiplicity underlying ‘what it is like’ to be a conscious creature or be in a conscious state. First, I analyse earlier challenges which claim that phenomenal consciousness cannot arise, or cannot be built, in machines. These are based on Block’s Chinese Nation and Chalmers’ Hard Problem. To defuse such challenges, theorists of artificial consciousness can appeal to empirical methods and models of explanation. Second, I explain why this naturalistic approach produces an epistemological puzzle on the role of biological properties in phenomenal consciousness. Neither behavioural tests nor theoretical inferences seem to settle whether our machines are conscious. Third, I evaluate whether the new challenge can be managed through a more fine-grained taxonomy of conscious states. This strategy is supported by the development of similar taxonomies for biological species and animal consciousness. Although it makes sense of some current models of artificial consciousness, it raises questions about their subjective and moral significance.

Conscious enactive computation - Estrada, Daniel (arXiv, 2018)
This paper looks at recent debates in the enactivist literature on computation and consciousness in order to assess major obstacles to building artificial conscious agents. We consider a proposal from Villalobos and Dewhurst (2018) for enactive computation on the basis of organizational closure. We attempt to improve the argument by reflecting on the closed paths through state space taken by finite state automata. This motivates a defense against Clark's recent criticisms of "extended consciousness", and perhaps a new perspective on living with machines.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

“The maze wasn’t made for you”: Artificial consciousness and reflexive narration in Westworld (HBO, 2016-) - Favard, Florent (TV/Series, 2018)
Cet article s’intéresse à la façon dont la série de science-fiction Westworld (HBO, 2016-présent) interroge la nature même de la conscience au travers d’une narration réflexive qui mêle la question du libre-arbitre et du sens de soi à celle de l’écriture du personnage sériel, s’appuyant ainsi sur l’héritage des séries de science-fiction narrativement complexes qui ont abordé ce thème au fil des dernières décennies. Après un point sur le « hard problem » de la définition de la conscience, l’article suit la logique de la série en interrogeant successivement la mémoire, l’improvisation et l’intérêt personnel, tout en mobilisant une analyse narratologique fondée notamment sur la théorie des mondes possibles. , This paper describes how the science fiction television series Westworld (HBO, 2016-present) questions the very nature of consciousness through a reflexive narrative blending matters of free will and self interest with clues on how to write a serial character, thus drawing on the rich heritage of narratively complex science fiction television series of the last decades. After detailing the “hard problem” posed by any definition of consciousness, the paper follows the series’ logic, successively questioning memory, improvisation and self-interest, while focusing on a narratological approach centered on possible worlds theory.

Does AI Share Same Ethic with Human Being?: From the Perspective of Virtue Ethics - Feng, Zilong (Intelligence Science II, 2018)
From the perspective of virtue ethics, this paper points out that Artificial Intelligence becomes more and more like an ethic subject which can take responsibility with its improvement of autonomy and sensitivity. This paper intends to point out that it will produce many problems to tackle the questions of ethics of Artificial Intelligence through programming the codes of abstract moral principle. It is at first a social integration question rather than a technical question when we talk about the question of AI’s ethics. From the perspective of historical and social premises of ethics, in what kind of degree Artificial Intelligence can share the same ethics system with human equals to the degree of its integration into the narrative of human’s society. And this is also a process of establishing a common social cooperation system between human and Artificial Intelligence. Furthermore, self-consciousness and responsibility are also social conceptions that established by recognition, and the Artificial Intelligence’s identity for its individual social role is also established in the process of integration.

Astrocyte-Synapse Receptor Coupling in Tripartite Synapses: A Mechanism for Self-Observing Robots - Mitterauer, Bernhard J. (Advances in Bioscience and Biotechnology, 2018)
A model of an intentional self-observing system is proposed based on the structure and functions of astrocyte-synapse interactions in tripartite synapses. Astrocyte-synapse interactions are cyclically organized and operate via feedforward and feedback mechanisms, formally described by proemial counting. Synaptic, extrasynaptic and astrocyte receptors are interpreted as places with the same or different quality of information processing described by the combinatorics of tritograms. It is hypothesized that receptors on the astrocytic membrane may embody intentional programs that select corresponding synaptic and extrasynaptic receptors for the formation of receptor-receptor complexes. Basically, the act of self-observation is generated if the actual environmental information is appropriate to the intended observation processed by receptor-receptor complexes. This mechanism is implemented for a robot brain enabling the robot to experience environmental information as “its own”. It is suggested that this mechanism enables the robot to generate matches and mismatches between intended observations and the observations in the environment, based on the cyclic organization of the mechanism. In exploring an unknown environment the robot may stepwise construct an observation space, stored in memory, commanded and controlled by the intentional self-observing system. Finally, the role of self-observation in machine consciousness is shortly discussed.

A New Theoretical Framework for Testing Consciousness in a Machine - Nazri, Azree; Ghani, Abdul Azim Abd; Hafez, Izuan; Ng, Keng-Yap (Recent Advances on Soft Computing and Data Mining, 2018)
The major aim of artificial general intelligence’s (AGI) is to allow a machine to perform general intelligence tasks similar to human counterparts. Hypothetically, this general intelligence in a machine can be achieved by establishing cross-domain optimization and learning machine approaches. However, contemporary artificial intelligence (AI) capabilities are only limited to narrow and specific domains utilizing machine learning. Consciousness concept is particularly interesting topic to attain the approaches because it simultaneously encodes and processes all types of information and seamlessly integrates them. Over the last several years, there has been a resurgence of interest in testing theories of consciousness using computer models. The studies of these models are classified into four categories: external behavior associated with consciousness, cognitive characteristics associated with consciousness, a computational architecture correlate of human consciousness and phenomenally of conscious machine. The critical challenge is to determine whether these artificial systems are capable of conscious states by providing a measurement the extent to which the systems are succeeded in realizing consciousness in a machine. Several tests for machine consciousness have been proposed yet their formulation is based on extrinsic measurement of consciousness. Yet extrinsic measurement is not inclusive because many conscious artificial systems behave implicitly. This research proposes a new framework to test machine consciousness based on intrinsic measurement so-called Pak Pandir test. The framework leverages three quantum double-slit settings and information integration theory as consciousness definition of choice.

Can artificially intelligent agents really be conscious? - Pandey, Subhash Chandra (Sādhanā, 2018)
Mind and intelligence are closely related with the consciousness. Indeed, artificial intelligence (AI) is the most promising avenue towards artificial consciousness (AC). However, in literature, consciousness has been considered as the least amenable to being understood or replicated by AI. Further, computational theories of mind (CTMs) render the mind as a computational system and it is treated as a substantial hypothesis within the purview of AI. However, the consciousness, which is a phenomenon of mind, is partially tackled by this theory and it seems that the CTM is not corroborated considerably in this pursuit. Many valuable contributions have been incorporated by the researchers working strenuously in this domain. However, there is still scarcity of globally accepted computational models of consciousness that can be used to design conscious intelligent machines. The contributions of the researchers entail consciousness as a vague, incomplete and human-centred entity. In this paper, attempt has been made to analyse different theoretical and intricate issues pertaining to mind, intelligence and AC. Moreover, this paper discusses different computational models of the consciousness and critically analyses the possibility of generating the machine consciousness as well as identifying the characteristics of conscious machine. Further, different inquisitive questions, e.g., “Is it possible to devise, project and build a conscious machine?”, “Will artificially conscious machines be able to surpass the functioning of artificially intelligent machines?” and “Does consciousness reflect a peculiar way of information processing?” are analysed.

Artificial Consciousness: An Illusionary Solution to the Hard Problem - Roman V. Yampolskiy (Reti, saperi, linguaggi, 2018)
The Hard Problem of consciousness has been dismissed as an illusion. By showing that computers are capable of experiencing, we show that they are at least rudimentarily conscious with potential to eventually reach superconsciousness. The main contribution of the paper is a test for confirming certain subjective experiences in a tested agent. We follow with analysis of benefits and problems with conscious machines and implications of such capability on future of computing, machine rights and artificial intelligence safety.

Adding Conscious Aspects and Simulated Emotions through Facial Expressions in Virtual Robot Navigation with Baars-Franklins Cognitive Architecture - Santos, Danilo H.; Palar, Piatan Sfair; De Oliveira, Andre S.; Fabro, Joao A.; Becker, Thiago (2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), 2018)
Human consciousness is the target of research in multiple fields of knowledge, presenting an important characteristic to better handle complex and diverse situations. Artificial consciousness models have arise, together with theories that try to model what we understand about consciousness, in a way that could be implemented a artificial conscious being. The main motivations to study artificial consciousness are related to the creation of agents more similar to human beings, in order to build more efficient machines and at the same time, make the human-computer interaction more affective and non intrusive. This paper presents an experiment using the Global Workspace Theory and the LIDA Model to build a conscious mobile robot in a virtual environment, using the LIDA framework as a implementation of the LIDA Model. The LIDA Model operates a consciousness system in an iterative cognitive cycle of perceiving the environment, shifting attention and focusing operation. The main objective is to evaluate if it is possible to use conscience and emotion as implemented by the LIDA framework to simplify decision making processes of a mobile robot subject to interaction with people, as part of a cicerone robot development.

Can Computers Become Conscious, an Essential Condition for the Singularity? - Logan, Robert (Information, 2017)
Given that consciousness is an essential ingredient for achieving Singularity, the notion that an Artificial General Intelligence device can exceed the intelligence of a human, namely, the question of whether a computer can achieve consciousness, is explored. Given that consciousness is being aware of one’s perceptions and/or of one’s thoughts, it is claimed that computers cannot experience consciousness. Given that it has no sensorium, it cannot have perceptions. In terms of being aware of its thoughts it is argued that being aware of one’s thoughts is basically listening to one’s own internal speech. A computer has no emotions, and hence, no desire to communicate, and without the ability, and/or desire to communicate, it has no internal voice to listen to and hence cannot be aware of its thoughts. In fact, it has no thoughts, because it has no sense of self and thinking is about preserving one’s self. Emotions have a positive effect on the reasoning powers of humans, and therefore, the computer’s lack of emotions is another reason for why computers could never achieve the level of intelligence that a human can, at least, at the current level of the development of computer technology.

The philosophy of artificial consciousness in the first season of TV series 'Westworld' - Rayhert, Konstantin (Skhid, 2017)
The study analyzes the philosophy of artificial consciousness presented in the first season of TV series 'Westworld' and as a result of the analysis shows the collision of two opposite philosophical views on consciousness and the possibility of creation of artificial consciousness from the standpoint of two characters of TV series - Arnold Weber and Robert Ford. Arnold Weber proceeds from two philosophical assumptions: consciousness really exists (1) and human consciousness can be a prototype for modeling consciousness in an artificial intelligence bearer (2). And he has to choose: either to pick out one of the already existing conceptions of consciousness to implement the emergence of artificial consciousness within artificial intelligence or to invent his own; Arnold Weber chooses the Julian Jaynes' conception of consciousness as a basis for artificial consciousness what means that artificial consciousness must have the following features: 1) artificial consciousness has to be the result of the breakdown of the bicameral mind (apparently, modeled within artificial intelligence), the state of mind in which cognitive functions are divided into two part, a 'speaking' part and 'hearing' ('obeying') part, until the breakdown that makes the bicameral mind the unified mind; 2) artificial consciousness has to be a mind-space based on language and characterized by introspection, concentration, suppression, consilience and an analog 'I' narratizing in the mindspace. Robert Ford believes that consciousness does not exist at all and that there are only stories (narratives) which human beings and artificial beings, modeled in the image and likeness of human beings, tell each other and always the basis of all those stories (narratives) is suffering.

The Attention Schema Theory: A Foundation for Engineering Artificial Consciousness - Graziano, Michael S. A. (Frontiers in Robotics and AI, 2017)
The purpose of the attention schema theory is to explain how an information-processing device, the brain, arrives at the claim that it possesses a non-physical, subjective awareness and assigns a high degree of certainty to that extraordinary claim. The theory does not address how the brain might actually possess a non-physical essence. It is not a theory that deals in the non-physical. It is about the computations that cause a machine to make a claim and to assign a high degree of certainty to the claim. The theory is offered as a possible starting point for building artificial consciousness. Given current technology, it should be possible to build a machine that contains a rich internal model of what consciousness is, attributes that property of consciousness to itself and to the people it interacts with, and uses that attribution to make predictions about human behavior. Such a machine would “believe” it is conscious and act like it is conscious, in the same sense that the human machine believes and acts.
Keywords: Attention; Awareness; body schema; internal model; visual attention

What is consciousness, and could machines have it? - Dehaene, Stanislas; Lau, Hakwan; Kouider, Sid (Science, 2017)
The controversial question of whether machines may ever be conscious must be based on a careful consideration of how consciousness arises in the only physical system that undoubtedly possesses it: the human brain. We suggest that the word “consciousness” conflates two different types of information-processing computations in the brain: the selection of information for global broadcasting, thus making it flexibly available for computation and report (C1, consciousness in the first sense), and the self-monitoring of those computations, leading to a subjective sense of certainty or error (C2, consciousness in the second sense). We argue that despite their recent successes, current machines are still mostly implementing computations that reflect unconscious processing (C0) in the human brain. We review the psychological and neural science of unconscious (C0) and conscious computations (C1 and C2) and outline how they may inspire novel machine architectures.

Artificial Consciousness or Artificial Intelligence - Spanache, Florin (DIALOGO-CONF 2017 SSC, 2017)
Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

The Creation of a Conscious Machine: The Quest for Artificial Intelligence - Tardy, Jean E. (Glasstree, 2017)
"The Creation of a Conscious Machine" surveys the millennial quest to create an intelligent artefact, concludes consciousness is the key to achieve this goal and proposes we adopt an understanding of synthetic consciousness that is suitable for machine implementation. The text describes how achieving Artificial Intelligence will yield extraordinary intellectual benefits and deep insights into the human condition. It examines past attempts, from ancient times until today, to define intelligence and implement it, drawing useful lessons from each. In particular, the Turing Test, the most influential measure of artificial intelligence, is the subject of an in depth analysis. Ultimately, the author also rejects the Turing Test, and the concept of a test itself, as an unsuitable measure of machine intelligence. Basing himself on this analysis, the author concludes that humans will only consider a machine to be truly intelligent if they also perceive it to be conscious. To realize the quest of Artificial Intelligence, it is necessary to implement consciousness. In turn, to achieve Synthetic Consciousness, we must discard the view that consciousness is a subjective experience in favour of a different understanding, deeply rooted in the Western tradition, that it is an externally observable capability. Using this "new" understanding, the author then proposes a definition of Synthetic Consciousness, expressed as specification objectives, that is suitable for software implementation. This makes it possible to build the first generation of synthetic conscious beings.

Can a Robot Have Free Will? - Farnsworth, Keith (Entropy, 2017)
Using insights from cybernetics and an information-based understanding of biological systems, a precise, scientifically inspired, definition of free-will is offered and the essential requirements for an agent to possess it in principle are set out. These are: (a) there must be a self to self-determine; (b) there must be a non-zero probability of more than one option being enacted; (c) there must be an internal means of choosing among options (which is not merely random, since randomness is not a choice). For (a) to be fulfilled, the agent of self-determination must be organisationally closed (a “Kantian whole”). For (c) to be fulfilled: (d) options must be generated from an internal model of the self which can calculate future states contingent on possible responses; (e) choosing among these options requires their evaluation using an internally generated goal defined on an objective function representing the overall “master function” of the agent and (f) for “deep free-will”, at least two nested levels of choice and goal (d–e) must be enacted by the agent. The agent must also be able to enact its choice in physical reality. The only systems known to meet all these criteria are living organisms, not just humans, but a wide range of organisms. The main impediment to free-will in present-day artificial robots, is their lack of being a Kantian whole. Consciousness does not seem to be a requirement and the minimum complexity for a free-will system may be quite low and include relatively simple life-forms that are at least able to learn.

Biological Naturalism - Searle, John (The Blackwell Companion to Consciousness, 2017)

Integrated Information Theory (IIT) and Artificial Consciousness - Fallon, Francis (Advances in Computational Intelligence and Robotics, 2017)
This chapter aims to evaluate Integrated Information Theory's claims concerning Artificial Consciousness. Integrated Information Theory (IIT) works from premises that claim that certain properties, such as unity, are essential to consciousness, to conclusions regarding the constraints upon physical systems that could realize consciousness. Among these conclusions is the claim that feed-forward systems, and systems that are not largely reentrant, necessarily will fail to generate consciousness (but may simulate it). This chapter will discuss the premises of IIT, which themselves are highly controversial, and will also address IIT's related rejection of functionalism. This analysis will argue that IIT has failed to established good grounds for these positions, and that convincing alternatives remain available. This, in turn, implies that the constraints upon Artificial Consciousness are more generous than IIT would have them be.

Artificial Intelligence and Consciousness - Gamez, D.; Holland, O. (Reference Module in Neuroscience and Biobehavioral Psychology, 2017)
Artificial intelligence and research on consciousness have reciprocally influenced each other: theories about consciousness have inspired work on artificial intelligence, and the results from artificial intelligence have changed our interpretation of the mind. Artificial intelligence can be used to test theories of consciousness and research has been carried out on the development of machines with the behavior, cognitive characteristics and architecture associated with consciousness. Some people have argued against the possibility of machine consciousness, but none of these objections is conclusive and many theories openly embrace the possibility that phenomenal consciousness could be realized in artificial systems.
Keywords: Artificial consciousness; Artificial intelligence, AI; Computer; Consciousness; Global workspace theory; Information integration; Machine consciousness; Model of consciousness; Neural network; Robot; Synthetic phenomenology; Turing test

Machine Consciousness - Aleksander, Igor (The Blackwell Companion to Consciousness, 2017)
Here is examined the work done in many laboratories on the proposition that the mechanisms underlying consciousness in living organisms can be studied using computational theories. This follows an agreement at a 2001 multi-disciplinary meeting of philosophers, neuroscientists and computer scientists that such a research programme was feasible and worthwhile. Here this effort is reviewed both as a historical statement and for the positions held at the time of going to print of this volume. The approaches cover diverse techniques ranging from the machine modeling of neural structures in the brain to abstract models based on the type of logic found in computer programming. Purely theoretical approaches based on hypotheses of what kind of information constitutes a mental state are included.
Keywords: Machine models of consciousness; informational theories of consciousness; neural basis of consciousness; virtual machines

Towards an Affective Computational Model for Machine Consciousness - Chandra, Rohitash (Neural Information Processing, 2017)
In the past, computational models for machine consciousness have been proposed with varying degrees of challenges for implementation. Affective computing focuses on the development of systems that can simulate, recognize, and process human affects which refer to the experience of feeling or emotion. The affective attributes are important factors for the future of machine consciousness with the rise of technologies that can assist humans and also build trustworthy relationships between humans and artificial systems. In this paper, an affective computational model for machine consciousnesses with a system of management of the major features. Real-world scenarios are presented to further illustrate the functionality of the model and provide a road-map for computational implementation.

A computational model of consciousness for artificial emotional agents - Kotov, Artemy A. (Psychology in Russia: State of the Art, 2017)
The structure of consciousness has long been a cornerstone problem in the cognitive sciences. Recently it took on applied significance in the design of computer agents and mobile robots. This problem can thus be examined from perspectives of philosophy, neuropsychology, and computer modeling.

Robot Pain - Mandik, Pete (The Routledge Handbook of Philosophy of Pain, 2017)
Some humans may seek to purchase pain-feeling robots for the purpose of torturing them – a sad fact about some humans. This chapter explores the Chinese room argument against robot pain. The role of the Chinese room thought experiment is to establish the truth of the claim that it is indeed possible for something or someone to run any arbitrarily selected program without thereby understanding Chinese. One way to construct a robotic copy of a human is by gradually transforming a human into a robot by a sequence of prosthetic replacements of the human’s naturally occurring parts, especially parts of the nervous system, with artificial analogs. Like all physiological systems in the human body, the nervous system is composed of causally interacting cells. The chapter emphasizes the ways in which the thought experiments in the respective arguments attempt to marshal hypothetical first-person accessible evidence concerning how one’s own mental life appears to oneself.

Non-ordinary Consciousness for Artificial Intelligence - Montes, Gabriel Axel (Biomimetic and Biohybrid Systems, 2017)
Humans are active agents in the design of artificial intelligence (AI), and our input into its development is critical. A case is made for recognizing the importance of including non-ordinary functional capacities of human consciousness in the development of synthetic life, in order for the latter to capture a wider range in the spectrum of neurobiological capabilities. These capacities can be revealed by studying self-cultivation practices designed by humans since prehistoric times for developing non-ordinary functionalities of consciousness. A neurophenomenological praxis is proposed as a model for self-cultivation by an agent in an entropic world. It is proposed that this approach will promote a more complete self-understanding in humans and enable a more thoroughly mutually-beneficial relationship between in life in vivo and in silico.

Internet Dreaming—Is the Web Conscious? - Pagel, J.F. (Boundaries of Self and Reality Online, 2017)
Artificial intelligence capacities for consciousness are not equivalent to human consciousness—the level of autonomous, independent, volitional behavioral control characterized by independently functioning biologic systems. There is strong evidence, however, that artificially created systems including Web-based search engines empirically demonstrate machine-based equivalents of aspects of consciousness. They have attained this capacity as based on high-level (in some cases suprabiologic) capabilities in defined aspects of consciousness (intelligence, attention, autonomy, and intention). Such systems also have the capacity to meet multiple definition criteria for having cognitive processing that is approximately equivalent to dreaming. Computer–human interface systems have expanded both human and machine capacity to address and extend scientific understanding at all epistemological levels of current inquiry. Complexity theories of consciousness can be used to theoretically support such an attainment of conscious function.

Some Thoughts about Artificial Consciousness - Popa, Rustem (Global Journal of Technology and Optimization, 2017)

Artificial Minds with Consciousness and Common sense Aspects: - Shylaja, K.R.; Vijayakumar, M.V.; Prasad, E. Vani; Davis, Darryl N. (International Journal of Agent Technologies and Systems, 2017)
The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze and compare the performance of agents in critical and dynamic environments. Awareness and attention to specific parameters that affect the performance of agents specify the consciousness level in agents. Common sense is a set of beliefs that are accepted to be true among a group of agents that are engaged in a common purpose, with or without self-experience. The common sense agents are a kind of conscious agents that are given with few common sense assumptions. The so-created environment has attackers with dependency on agents in the survival-food chain. These attackers create a threat mental state in agents that can affect their conscious and common sense behaviors. The agents are built with a multi-layer cognitive architecture COCOCA (Consciousness and Common sense Cognitive Architecture) with five columns and six layers of cognitive processing of each precept of an agent. The conscious agents self-learn strategies for threat management and energy level maintenance. Experimentation conducted in this research work demonstrates animate-level intelligence in their problem-solving capabilities, decision making and reasoning in critical situations.

Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena - Tani, Jun (Oxford University Press, 2016)
How do “minds” work? In Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena, Professor Jun Tani reviews key experiments within his own pioneering neurorobotics research project aimed at answering this fundamental and fascinating question. The book shows how symbols and concepts representing the world can emerge via “deep learning” within robots, by using specially designed neural network architectures by which, given iterative interactions between top-down proactive “subjective” and “intentional” processes for plotting action, and bottom-up updates of the perceptual reality after action, the robot is able to learn to isolate, to identify, and even to infer salient features of the operational environment, modifying its behavior based on anticipations of both objective and social cues. Through permutations of this experimental model, the book then argues that longstanding questions about the nature of “consciousness” and “freewill” can be addressed through an understanding of the dynamic structures within which, in the course of normal operations and in a changing operational environment, necessary top-down/bottom-up interactions arise. Written in clear and accessible language, this book opens a privileged window for a broad audience onto the science of artificial intelligence and the potential for artificial consciousness, threading cognitive neuroscience, dynamic systems theory, robotics, and phenomenology through an elegant series of deceptively simple experiments that build upon one another and ultimately outline the fundamental form of the working mind.

Artificial consciousness and the consciousness-attention dissociation - Haladjian, Harry Haroutioun; Montemayor, Carlos (Consciousness and Cognition, 2016)
Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness.
Keywords: Artificial consciousness; Artificial intelligence; Consciousness; Emotions; Empathy; Phenomenology; Visual attention

Synthetic consciousness: the distributed adaptive control perspective - Verschure, Paul F. M. J. (Philosophical Transactions of the Royal Society B: Biological Sciences, 2016)
Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene. This article is part of the themed issue ‘The major synthetic evolutionary transitions’.

Social Expression of Pet Robot Based on Artificial Consciousness and Biologically Inspired On-line Topological Method - Chumkamon, Sakmongkon; Hayashi, Eiji (Proceedings of International Conference on Artificial Life and Robotics, 2016)
The social robot becomes important to the future world of pervasive computing, where the robot currently facilitates our life. The social behavior and natural action of the robot is one of the most needed function for emerging future realistic human-like robot. Our paper proposes the artificial topological consciousness based on a pet robot using the artificial neurotransmitter and motivation. Since, the significant is cross-creature communication to friendly companionship. This system focuses on three points. The first, the organization of the behavior and emotion model regarding the phylogenetic. The second, the method of the robot that can have empathy with user expression. The third, how the robot can socially perform its expression to human using biologically inspired topological on-line method for encouragement or being delighted by its own emotion and the human expression. We believe the artificial consciousness based on complexity level and the robot social expression enhance the user affinity by the experiment.

The Sensorimotor Account of Sensory Consciousness: Implications for Machine Consciousness - Maye, A.; Engel, A.K. (Journal of Consciousness Studies, 2016)
When people speak about consciousness, they distinguish various types and different levels, and they argue for different concepts of cognition. This complicates the discussion about artificial or machine consciousness. Here we take a bottom-up approach to this question by presenting a family of robot experiments that invite us to think about consciousness in the context of artificial agents. The experiments are based on a computational model of sensorimotor contingencies. It has been suggested that these regularities in the sensorimotor flow of an agent can explain raw feels and perceptual consciousness in biological agents. We discuss the validity of the model with respect to sensorimotor contingency theory and consider whether a robot that is controlled by knowledge of its sensorimotor contingencies could have any form of consciousness. We propose that consciousness does not require higher-order thought or higher-order representations. Rather, we argue that consciousness starts when (i) an agent actively (endogenously triggered) uses its knowledge of sensorimotor contingencies to issue predictions and (ii) when it deploys this capability to structure subsequent action.

On Three Categories of Conscious Machines - Arsiwalla, Xerxes D.; Herreros, Ivan; Verschure, Paul (Springer International Publishing, 2016)
Reviewing recent closely related developments at the crossroads of biomedical engineering, artificial intelligence and biomimetic technology, in this paper, we attempt to distinguish phenomenological consciousness into three categories based on embodiment: one that is embodied by biological agents, another by artificial agents and a third that results from collective phenomena in complex dynamical systems. Though this distinction by itself is not new, such a classification is useful for understanding differences in design principles and technology necessary to engineer conscious machines. It also allows one to zero-in on minimal features of phenomenological consciousness in one domain and map on to their counterparts in another. For instance, awareness and metabolic arousal are used as clinical measures to assess levels of consciousness in patients in coma or in a vegetative state. We discuss analogous abstractions of these measures relevant to artificial systems and their manifestations. This is particularly relevant in the light of recent developments in deep learning and artificial life.

Intelligent emotion and behavior based on topological consciousness and adaptive resonance theory in a companion robot - Chumkamon, Sakmongkon; Hayashi, Eiji; Koike, Masato (Biologically Inspired Cognitive Architectures, 2016)
Companion or ‘pet’ robots can be expected to be an important part of a future in which robots contribute to our lives in many ways. An understanding of emotional interactions would be essential to such robots’ behavior. To improve the cognitive and behavior systems of such robots, we propose the use of an artificial topological consciousness that uses a synthetic neurotransmitter and motivation, including a biologically inspired emotion system. A fundamental aspect of a companion robot is a cross-communication system that enables natural interactions between humans and the robot. This paper focuses on three points in the development of our proposed framework: (1) the organization of the behavior including inside-state emotion regarding the phylogenetic consciousness-based architecture; (2) a method whereby the robot can have empathy toward its human user’s expressions of emotion; and (3) a method that enables the robot to select a facial expression in response to the human user, providing instant human-like ‘emotion’ and based on emotional intelligence (EI) that uses a biologically inspired topological online method to express, for example, encouragement or being delighted. We also demonstrate the performance of the artificial consciousness based on the complexity level and a robot’s social expressions that are designed to enhance the users affinity with the robot.

Free Will for Artificial Machines with Natural Intelligence - Copertari, Luis F. (OALib, 2016)
A discussion on how artificial machines with natural intelligence would be safe or not is made based on scientific, philosophical and theological arguments. The finite or infinite nature of the universe is discussed and the implications analyzed. The concepts of destiny and free will are considered, with implications on what it would mean to create an artificial consciousness and how it would be possible to give it or deny it its free will. Computer experiments are carried out based on cellular automata and the results considered. A thorough discussion follows and a conclusion is reached.

Dynamic Behavior Selection Model based on Emotional States for Conbe-I robot - Jitviriya, Wisanu; Inthiam, Jiraphan; Hayashi, Eiji (Journal of Robotics, Networking and Artificial Life, 2016)
Currently, the rapid development of non-industrial robots that are designed with artificial intelligence (AI) methods to improve the robotics system is to have them imitate human thinking and behavior. Therefore, our works have focused on studying and investigating the application of brain-inspired technology for developing the conscious behavior robot (Conbe-I). We created the hierarchical structure model, which is called “Consciousness-Based Architecture: CBA” module, but it has limitation in managing and selecting the behavior that only depends on the increase and decrease of the motivation levels. Consequently, in this paper, we would like to introduce the dynamic behavior selection model based on emotional states, which develops by Self-organizing map learning and Markov model in order to define the relationship between the behavioral selection and emotional expression model. We confirm the effectiveness of the proposed system with the experimental results.

A causal foundation for consciousness in biological and artificial agents - Manzotti, Riccardo; Jeschke, Sabina (Cognitive Systems Research, 2016)
Traditional approaches model consciousness as the outcome either of internal computational processes or of cognitive structures. We advance an alternative hypothesis – consciousness is the hallmark of a fundamental way to organise causal interactions between an agent and its environment. Thus consciousness is not a special property or an addition to the cognitive processes, but rather the way in which the causal structure of the body of the agent is causally entangled with a world of physical causes. The advantage of this hypothesis is that it suggests how to exploit causal coupling to envisage tentative guidelines for designing conscious artificial agents. In this paper, we outline the key characteristics of these causal building blocks and then a set of standard technologies that may take advantage of such an approach. Consciousness is modelled as a kind of cognitive middle ground and experience is not an internal by-product of cognitive processes but the external world that is carved out by means of causal interaction. Thus, consciousness is not the penthouse on top of a 50 stores cognitive skyscraper, but the way in which the steel girders snap together from bottom to top.

A machine consciousness approach to urban traffic control - Paraense, André Luis O.; Raizer, Klaus; Gudwin, Ricardo R. (Biologically Inspired Cognitive Architectures, 2016)
In this work, we present a distributed cognitive architecture used to control the traffic in an urban network. This architecture relies on a machine consciousness approach – Global Workspace Theory – in order to use competition and broadcast, allowing a group of local traffic controllers to interact, resulting in a better group performance. The main idea is that the local controllers usually perform a purely reactive behavior, defining the times of red and green lights, according just to local information. These local controllers compete in order to define which of them is experiencing the most critical traffic situation. The controller in the worst condition gains access to the global workspace, further broadcasting its condition (and its location) to all other controllers, asking for their help in dealing with its situation. This call from the controller accessing the global workspace will cause an interference in the reactive local behavior, for those local controllers with some chance in helping the controller in a critical condition, by containing traffic in its direction. This group behavior, coordinated by the global workspace strategy, turns the once reactive behavior into a kind of deliberative one. We show that this strategy is capable of improving the overall mean travel time of vehicles flowing through the urban network. A consistent gain in performance with the “Artificial Consciousness” traffic signal controller during all simulation time, throughout different simulated scenarios, could be observed, ranging from around 13.8% to more than 21%.

Artificial Consciousness in an Artificial World - Sarkadi, Stefan (Philosophy, Communication, Media Sciences, 2016)
This paper presents the idea that using computers to simulate complex virtual environments can give rise to artificial consciousness within those environments. Currently, limitations in creating artificial consciousness may be imposed by material compounds that enable the transmission of signals through artificial systems such as robots. Virtual environments, on the other hand, provide the necessary tools for surpassing such limitations. I also argue that using virtual reality tools to enable complex interaction between humans and AI (artificial intelligence) within virtual environments is the most reasonable way to obtain artificial consciousness by appealing to the nature of human bias.

Consciousness is Pattern Recognition - Van De Walker, Ray (arXiv, 2016)
This is a proof of the strong AI hypothesis, i.e. that machines can be conscious. It is a phenomenological proof that pattern-recognition and subjective consciousness are the same activity in different terms. Therefore, it proves that essential subjective processes of consciousness are computable, and identifies significant traits and requirements of a conscious system. Since Husserl, many philosophers have accepted that consciousness consists of memories of logical connections between an ego and external objects. These connections are called "intentions." Pattern recognition systems are achievable technical artifacts. The proof links this respected introspective philosophical theory of consciousness with technical art. The proof therefore endorses the strong AI hypothesis and may therefore also enable a theoretically-grounded form of artificial intelligence called a "synthetic intentionality," able to synthesize, generalize, select and repeat intentions. If the pattern recognition is reflexive, able to operate on the set of intentions, and flexible, with several methods of synthesizing intentions, an SI may be a particularly strong form of AI. Similarities and possible applications to several AI paradigms are discussed. The article then addresses some problems: The proof's limitations, reflexive cognition, Searles' Chinese room, and how an SI could "understand" "meanings" and "be creative."
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences; I.2.0

A dual-process Qualia Modeling Framework (QMF) - Vaughan, Sandra L.; Mills, Robert F.; Peterson, Gilbert L.; Grimaila, Michael R.; Rogers, Steven K.; Oxley, Mark E.; Patterson, Robert E. (Biologically Inspired Cognitive Architectures, 2016)
We present the software implementation of our Qualia Modeling Framework (QMF), a computational cognitive model based on the dual-process theory, which theorizes that reasoning and decision making rely on integrated experiences from two interactive minds: the autonomous mind, without the agent’s conscious awareness, and the reflective mind, of which the agent is consciously aware. In the QMF, artificial qualia are the vocabulary of the conscious mind, required to reason over conceptual memory, and generate cognitive inferences. The autonomous mind employs pattern-matching, for fast reasoning over episodic memories. An ACT-R model with conventional declarative memory represents the autonomous mind. A second ACT-R model, with an unconventional implementation of declarative memory utilizing a hypernetwork theory based model of qualia space, represents the reflective mind. Using real-world, non-trivial, data sets, our cognitive model achieved classification accuracy comparable to, or greater than, analogous machine learning classifiers kNN and DT, while providing improvements in flexibility by allowing the Target Attribute to be identified or changed any time during training and testing. We advance the BICA challenge by providing a generalizable, efficient, algorithm which models the phenomenal structure of consciousness as proposed by a contemporary theory, and provides an effective decision aid in complex environments where data are too broad or diverse for a human to evaluate without computational assistance.

The Thermal Grill Illusion: A Study Using a Consciousness System - Xu, Hanwen; Kanazawa, Koki; Matsumoto, Daiki; Takeno, Junichi (Procedia Computer Science, 2015)
Although the thermal grill illusion has been the topic of previous research, many mysteries still remain regarding psychological determinants, neurophysiological mechanisms and so on. Also, the illusion cannot be simulated by information science and robotics. This study focuses on a very simple but interesting experiment called Hot and Cold Coils, which is known as a typical example of the thermal grill illusion. The authors aim to explain the thermal grill illusion by proposing a new and bold assumption called the conflict of concepts, and demonstrate how to construct a model by using an artificial consciousness module called the Module of Nerves for Advanced Dynamics (MoNAD). A simple experimental apparatus was prepared to prove the existence of the thermal grill illusion, and consists of a parallel arrangement of bars with an alternating pattern of cold and warmth at 20°C and 40°C. The authors conclude with the belief that many complex perceptions of humanity can be simulated through the use of neural networks, and that this can help us to deeply study the cognitive processes of human perception.
Keywords: Artificial consciousness; Cognition and behavior; Neural network; Robotics; Thermal Grill Illusion

Adding Conscious Aspects in Virtual Robot Navigation through Baars-Franklin's Cognitive Architecture - Becker, Thiago; Fabro, Joao Alberto; Schneider De Oliveira, Andre; Reis, Luis Paulo (2015 IEEE International Conference on Autonomous Robot Systems and Competitions, 2015)
Human consciousness is a target of research in multiple fields of knowledge, that presents it as an important characteristic to better handle complex and diverse situations. Artificial consciousness models have arose, together with theories that attempt to model what we understand about consciousness, in a way that could be implemented an artificial conscious being. The main motivations to study artificial consciousness are related to the creation of agents more similar to human beings, in order to build more efficient machines. This paper presents an experiment using the Global Workspace Theory and the LIDA Model to build a "conscious" mobile robot in a virtual environment, using the LIDA framework as a implementation of the LIDA Model. The main objective is to evaluate if it is possible to use conscience as implemented by the LIDA framework to simplify decision making processes during navigation of a mobile robot subject to interaction with people, as part of a cicerone robot development.

Facial Expression of Social Interaction Based on Emotional Motivation of Animal Robot - Chumkamon, Sakmongkon; Masato, Koike; Hayashi, Eiji (2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2015)
This paper aims to develop the research based on a pet robot and its artificial consciousness. We propose the animal behavior and emotion using the artificial neurotransmitter and motivation. This research still implements the communication between human and a pet robot respecting to a social cognitive and interaction. Thus, the development of cross-creature communication is crucial for friendly companionship. This system focuses on three points. The first that is the organization of the behavior and emotion model regarding the phylogenesis. The second is the method of the robot that can have empathy with user expression. The third is how the robot can socially perform its expression to human for encouragement or being delighted based on its own emotion and the human expression. This paper eventually presents the performance and the experiment that the robot using cross-perception and cross-expression between animal robot and social interaction of human communication based on the consciousness based architecture (CBA).

A Note on Continuous Self-Identification as Self-Awareness: An Example of Robot Navigation - Ishida, Yoshiteru (Procedia Computer Science, 2015)
This note reports on interdisciplinary approaches to model consciousness, an aspect of self-awareness in particular, aiming at artificial consciousness that can be mounted on an autonomous and mobile robot. For self-awareness to emerge, the self-identification process plays an important role. Self-awareness would emerge when self-locating in a self-created map in robot navigation; when solving self-related problems in (a self-related version of) the frame problem; and when a singularity arises in mapping the reference point in mathematical mappings.

Ascribing Consciousness to Artificial Intelligence - Shanahan, Murray (arXiv, 2015)
This paper critically assesses the anti-functionalist stance on consciousness adopted by certain advocates of integrated information theory (IIT), a corollary of which is that human-level artificial intelligence implemented on conventional computing hardware is necessarily not conscious. The critique draws on variations of a well-known gradual neuronal replacement thought experiment, as well as bringing out tensions in IIT's treatment of self-knowledge. The aim, though, is neither to reject IIT outright nor to champion functionalism in particular. Rather, it is suggested that both ideas have something to offer a scientific understanding of consciousness, as long as they are not dressed up as solutions to illusory metaphysical problems. As for human-level AI, we must await its development before we can decide whether or not to ascribe consciousness to it.
Keywords: Artificial Intelligence (cs.AI); FOS: Computer and information sciences

Modelling Consciousness-Dependent Expertise in Machine Medical Moral Agents - Torrance, Steve; Chrisley, Ron (Machine Medical Ethics, 2015)
It is suggested that some limitations of current designs for medical AI systems (be they autonomous or advisory) stem from the failure of those designs to address issues of artificial (or machine) consciousness. Consciousness would appear to play a key role in the expertise, particularly the moral expertise, of human medical agents, including, for example, autonomous weighting of options in (e.g.,) diagnosis; planning treatment; use of imaginative creativity to generate courses of action; sensorimotor flexibility and sensitivity; empathetic and morally appropriate responsiveness; and so on. Thus, it is argued, a plausible design constraint for a successful ethical machine medical or care agent is for it to at least model, if not reproduce, relevant aspects of consciousness and associated abilities. In order to provide theoretical grounding for such an enterprise we examine some key philosophical issues that concern the machine modelling of consciousness and ethics, and we show how questions relating to the first research goal are relevant to medical machine ethics. We believe that this will overcome a blanket skepticism concerning the relevance of understanding consciousness, to the design and construction of artificial ethical agents for medical or care contexts. It is thus argued that it would be prudent for designers of MME agents to reflect on issues to do with consciousness and medical (moral) expertise; to become more aware of relevant research in the field of machine consciousness; and to incorporate insights gained from these efforts into their designs.

Salient environmental sound detection framework for machine awareness - Wang, Jingyu; Zhang, Ke; Madani, Kurosh; Sabourin, Christophe (Neurocomputing, 2015)
Auditory perception is an essential part of environment perception, in which the saliency detection is not only the fundamental basis but also an efficient way of achieving this task. For artificial machines, intelligent perception approach of sound is required to provide awareness as the initiatory step of artificial consciousness. In this paper, a novel salient environment sound detection framework for machine awareness is proposed. The framework is based on the heterogeneous saliency features from both image and acoustic channels. To improve the efficiency of proposed framework, (1) a global informative saliency estimation approach is initially proposed based on short-term Shannon entropy; (2) a series of auditory saliency detection methods is presented to obtain the spectral and temporal saliency features from power spectral density and mel-frequency cepstral coefficients, respectively; (3) a computational bio-inspired inhibition of return model is proposed for saliency verification to improve the accuracy of detection; (4) a heterogeneous saliency feature fusion approach is introduced to form the final auditory saliency map by combining the acoustic and image saliency features together. Environmental sounds which collected from real world are applied to verify the superiority of the proposed framework. The results show that, the proposed framework is more effective for the detection of the overlapped salient sounds, and is more robust to the background noise compared with the conventional approach.

Learning Efficiency of Consciousness System for Robot Using Artificial Neural Network - Shoubaky, Osama; Sharari, Tala M. (Journal of Mechatronics, Electrical Power, and Vehicular Technology, 2014)
This paper presents learning efficiency of a consciousness system for robot using artificial neural network. The proposed conscious system consists of reason system, feeling system and association system. The three systems are modeled using Module of Nerves for Advanced Dynamics (ModNAD). Artificial neural network of the type of supervised learning with the back propagation is used to train the ModNAD. The reason system imitates behaviour and represents self-condition and other-condition. The feeling system represents sensation and emotion. The association system represents behaviour of self and determines whether self is comfortable or not. A robot is asked to perform cognition and tasks using the consciousness system. Learning converges to about 0.01 within about 900 orders for imitation, pain, solitude and the association modules. It converges to about 0.01 within about 400 orders for the comfort and discomfort modules. It can be concluded that learning in the ModNAD completed after a relatively small number of times because the learning efficiency of the ModNAD artificial neural network is good. The results also show that each ModNAD has a function to imitate and cognize emotion. The consciousness system presented in this paper may be considered as a fundamental step for developing a robot having consciousness and feelings similar to humans.

The Future of Identity: Implications, Challenges, and Complications of Human/Machine Consciousness - Goonan, Kathleen Ann (Intelligence Unbound, 2014)
One model for creating artificial consciousness is replicating every fine detail of the brain on computers and setting the model in motion. Consciousness has been experimentally demonstrated to be a much more fragmented experience than we think it to be, perhaps we only need snippets of ourselves to feel conscious. Perhaps consciousness is nothing less and nothing more than story, and all we need do to continue to feel conscious is maintain identity through computer-based narrative. Applied nanotechnology has generated uncountable applications in electronics, pharmacology, and materials engineering. The best approach to life extension and consciousness expansion might lie in our own marvelously complex and entire bodies, meshed with and augmented by tiny bionan machines that become a part of us, rather than the opposite vision of humans migrating into a machine substrate.

Artificial emotions and machine consciousness - Scheutz, Matthias (The Cambridge Handbook of Artificial Intelligence, 2014)
The goal of this chapter is to present an overview of the work in AI on emotions and machine consciousness, with an eye toward answering these questions. Starting with a brief philosophical perspective on emotions and machine consciousness to frame the work, the chapter first focuses on artificial emotions, and then moves on to machine consciousness – reflecting the fact that emotions and consciousness have been treated independently and by different communities in AI. The chapter concludes by discussing philosophical implications of AI research on emotions and consciousness.

Haikonen's View on Machine Consciousness: Back to the Engineering Stance - Arrabales, Raúl (International Journal of Machine Consciousness, 2014)
Machine consciousness is a young research field, yet inspired by oldest intellectual disciplines like philosophy of mind. Specifically, the mind–body problem has been approached since ancient times and different accounts have been proposed along the centuries. While none of these accounts, like different forms of dualism, have been seen as useful working hypotheses in the domain of machine consciousness, their influence might have shaped the orientation of this research field towards a frantic search for an illusory and unachievable bridge for the explanatory gap. In his book, Consciousness and Robot Sentience, Haikonen seems to claim back the predominant position that engineering should have in a domain, where we are supposed to deliver pragmatic solutions. In this regard, Haikonen is actually bridging the gap between the philosophical discourse and the practical engineering approach. This is a remarkable movement as Haikonen is essentially claiming that his cognitive architecture is a proof of the inexistence of such a thing as a mind–body problem. In this book review, I analyze the implications, limitations, and prospects of this engineering stance, looking at the main contributions and those aspects that might require further explanation.
Keywords: Haikonen cognitive architecture; explanatory gap; mind–body problem

What to Do about Artificial Consciousness - Basl, John (Ethics and Emerging Technologies, 2014)
One of the primary ethical issues related to creating robust artificial intelligences is how to engineer them to ensure that they will behave morally — i.e. that they will consider and treat us appropriately. A much less commonly discussed issue is what their moral status will be — i.e. how we ought to consider and treat them. In this chapter, John Basl takes up the issue of the moral status of artificial consciousnesses. He defends a capacity-based account of moral status, on which an entity’s moral status is determined by the capacities it has, rather than its origins or material composition. An implication of this is that if a machine intelligence has cognitive and psychological capacities like ours, then it would have comparable moral status to us. However, Basl argues that it is highly unlikely that machines will have capacities (and so interests) like ours, and that in fact it will be very difficult to know whether they are conscious and, if they are, what capacities and interests they have.

Haikonen's Philosophy of Machine Consciousness - Boltuc, Peter (International Journal of Machine Consciousness, 2014)

Artificial Consciousness - Crowder, James A.; Carbone, John N.; Friess, Shelli A. (Artificial Cognition Architectures, 2014)
To develop “Artificial Consciousness” for a SELF requires investigation and understanding of what it means to be conscious. The textbook definition of consciousness is:

A Novel Theory of Consciousness - Gelepithis, Petros A. M. (International Journal of Machine Consciousness, 2014)
I propose a physicalist theory of consciousness that is an extension of the theory of noémona species. The proposed theory covers the full consciousness spectrum from animal to machine and its human consciousness base is compatible with the corresponding work of Wundt, James, and Freud. The paper is organized in three sections. In the first, I briefly justify the methodology used. In Sec. 2, I state the inadequacies of the major work on the nature of consciousness and present a definitional system that adequately describes its changing nature and scope. Finally in Sec. 3, I state some of the consequences of the theory and introduce some of its future extensions.

From the Perspective of Artificial Intelligence: A New Approach to the Nature of Consciousness - Manzotti, Riccardo; Jeschke, Sabina (International Journal of Advanced Research in Artificial Intelligence, 2014)
Consciousness is not only a philosophical but also a technological issue, since a conscious agent has evolutionary advantages. Thus, to replicate a biological level of intelligence in a machine, concepts of machine consciousness have to be considered. The widespread internalistic assumption that humans do not experience the world as it is, but through an internal ‘3D virtual reality model’, hinders this construction. To overcome this obstacle for machine consciousness a new theoretical approach to consciousness is sketched between internalism and externalism to address the gap between experience and physical world. The ‘internal interpreter concept’ is replaced by a ‘key-lock approach’. Here, consciousness is not an image of the external world but the world itself. A possible technological design for a conscious machine is drafted taking advantage of an architecture exploiting selfdevelopment of new goals, intrinsic motivation, and situated cognition. The proposed cognitive architecture does not pretend to be conclusive or experimentally satisfying but rather forms the theoretical the first step to a full architecture model on which the authors currently work on, which will enable conscious agents e.g. for robotics or software applications.

Machine Consciousness, Mind & Consciousness - Nath, Rajakishore (Proceedings of the 50th Anniversary Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour,Pp. 626-631, 2014)
The problem of consciousness is one of the mostimportant problems in science as well as in philosophy. Thereare different philosophers and different scientists who define itand explain it differently. As far as our knowledge ofconsciousness is concerned, ‘consciousness’ does not admit of adefinition in terms of genus and differentia or necessary andsufficient condition. In this paper I shall explore the very idea ofmachine consciousness. The machine consciousness has offeredcausal explanation to the ‘how’ and ‘what’ of consciousness, butthey failed to explain the ‘why’ of consciousness. Theirexplanation is based on the ground that consciousness is causallydependent on the material universe and that of all, consciousnessphenomena can be explained by mapping the physical universe.Again, this mechanical/epistemological theory of consciousnessis essentially committed to scientific world view, which cannotavoid metaphysical implication of consciousness.

Heideggerian Credentials? O’Regan’s Sensorimotor Approach to Perception and Robots That Feel - Paine, Rachel (Contemporary Sensorimotor Theory, 2014)
Kevin O’Regan argues that seeing is a way of exploring the world, and that this approach helps us understand consciousness. O’Regan is interested in applying his ideas to the modeling of consciousness in robots. Hubert Dreyfus has raised a range of objections to traditional approaches to artificial intelligence, based on his reading of Heidegger. In light of this, I explore here ways in which O’Regan’s approach meets these Heideggerian considerations, and ways in which his account is more Heideggerian than that of Dreyfus. Despite these successes, O’Regan leaves out any role for emotion. This is an area where a Heideggerian perspective may offer useful insights into what more is needed for the sense of self O’Regan includes in his account in order for a robot to feel.

Artificial Consciousness and Artificial Ethics: Between Realism and Social Relationism - Torrance, Steve (Philosophy & Technology, 2014)
I compare a ‘realist’ with a ‘social–relational’ perspective on our judgments of the moral status of artificial agents (AAs). I develop a realist position according to which the moral status of a being—particularly in relation to moral patiency attribution—is closely bound up with that being’s ability to experience states of conscious satisfaction or suffering (CSS). For a realist, both moral status and experiential capacity are objective properties of agents. A social relationist denies the existence of any such objective properties in the case of either moral status or consciousness, suggesting that the determination of such properties rests solely upon social attribution or consensus. A wide variety of social interactions between us and various kinds of artificial agent will no doubt proliferate in future generations, and the social–relational view may well be right that the appearance of CSS features in such artificial beings will make moral role attribution socially prevalent in human–AA relations. But there is still the question of what actual CSS states a given AA is capable of undergoing, independently of the appearances. This is not just a matter of changes in the structure of social existence that seem inevitable as human–AA interaction becomes more prevalent. The social world is itself enabled and constrained by the physical world, and by the biological features of living social participants. Properties analogous to certain key features in biological CSS are what need to be present for nonbiological CSS. Working out the details of such features will be an objective scientific inquiry.

Robot Pain - Van Rysewyk, Simon (International Journal of Synthetic Emotions, 2013)
Functionalism of robot pain claims that what is definitive of robot pain is functional role, defined as the causal relations pain has to noxious stimuli, behavior and other subjective states. Here, the author proposes that the only way to theorize role-functionalism of robot pain is in terms of type-identity theory. The author argues that what makes a state pain for a neuro-robot at a time is the functional role it has in the robot at the time, and this state is type identical to a specific circuit state. Support from an experimental study shows that if the neural network that controls a robot includes a specific 'emotion circuit', physical damage to the robot will cause the disposition to avoid movement, thereby enhancing fitness, compared to robots without the circuit. Thus, pain for a robot at a time is type identical to a specific circuit state.

Phenomenal consciousness and biologically inspired systems - Aleksander, Igor (International Journal of Machine Consciousness, 2013)
The stated aim of adherents to the paradigm called biologically inspired cognitive architectures (BICA) is to build machines that address "the challenge of creating a real-life computational equivalent of the human mind".(From the mission statement of the new BICA journal.) In contrast, practitioners of machine consciousness (MC) are driven by the observation that these human minds for which one is trying to find equivalents are generally thought to be conscious. (Of course, this is controversial because there is no evidence of consciousness in behavior. But as the hypothesis of the consciousness of others is commonly used, a rejection of it has to be considered just as much as its acceptance.) In this paper, it is asked whether those who would like to build computational equivalents of the human mind can do so while ignoring the role of consciousness in what is called the mind. This is not ignored in the MC paradigm and the consequences, particularly on phenomenological treatments of the mind, are briefly explored. A measure based on a subjective feel for how well a model matches personal experience is introduced. An example is given which illustrates how MC can clarify the double-cognition tenet of Strawson's cognitive phenomenology.
Keywords: Brain inspired machines; cognitive phenomenology; machine consciousness

How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network - Cruse, Holk; Schilling, Malte (Frontiers in Psychology, 2013)
An artificial neural network called reaCog is described which is based on a decentralized, reactive and embodied architecture developed to control non-trivial hexapod walking in an unpredictable environment (Walknet) while using insect-like navigation (Navinet). In reaCog, these basic networks are extended in such a way that the complete system, reaCog, adopts the capability of inventing new behaviors and – via internal simulation of planning ahead. This cognitive expansion enables the reactive system to be enriched with additional procedures. Here, we focus on the question to what extent properties of phenomena to be characterized on a different level of description as for example consciousness can be found in this minimally cognitive system. Adopting a monist view, we argue that the phenomenal aspect of mental phenomena can be neglected when discussing the function of such a system. Under this condition, reaCog is discussed to be equipped with properties as are bottom-up and top-down attention, intentions, volition, and some aspects of Access Consciousness. These properties have not been explicitly implemented but emerge from the cooperation between the elements of the network. The aspects of Access Consciousness found in reaCog concern the above mentioned ability to plan ahead and to invent and guide (new) actions. Furthermore, global accessibility of memory elements, another aspect characterizing Access Consciousness is realized by this network. reaCog allows for both reactive/automatic control and (access-) conscious control of behavior. We discuss examples for interactions between both the reactive domain and the conscious domain. Metacognition or Reflexive Consciousness is not a property of reaCog. Possible expansions are discussed to allow for further properties of Access Consciousness, verbal report on internal states, and for Metacognition. In summary, we argue that already simple networks allow for properties of consciousness if leaving the phenomenal aspect aside.

Data Assimilation as Artificial Perception and Supermodeling as Artificial Consciousness - Duane, Gregory S. (Consensus and Synchronization in Complex Networks, 2013)
Data assimilation is naturally conceived as the synchronization of two systems, “truth” and “model”, coupled through a limited exchange of information (observed data) in one direction. Though investigated most thoroughly in meteorology, the task of data assimilation arises in any situation where a predictive computational model is updated in run time by new observations of the target system, including the case where that model is a perceiving biological mind. In accordance with a view of a semi-autonomous mind evolving in synchrony with the material world, but not slaved to it, the goal is to prescribe a coupling between truth and model for maximal synchronization. It is shown that optimization leads to the usual algorithms for assimilation via Kalman Filtering under a weak linearity assumption. For nonlinear systems with model error and sampling error, the synchronization view gives a recipe for calculating covariance inflation factors that are usually introduced on an ad hoc basis. Consciousness can be framed as self-perception, and represented as a collection of models that assimilate data from one another and collectively synchronize. The combination of internal and external synchronization is examined in an array of models of spiking neurons, coupled to each other and to a stimulus, so as to segment a visual field. The inter-neuron coupling appears to enhance the overall synchronization of the model with reality.

A MODEL OF PRIMITIVE CONSCIOUSNESS BASED ON SYSTEM-LEVEL LEARNING ACTIVITY IN AUTONOMOUS ADAPTATION - Kinouchi, Yasuo; Kato, Yoshihiro (International Journal of Machine Consciousness, 2013)
Although many models of consciousness have been proposed from various viewpoints, they have not been based on learning activities in a whole system with the capabilities of autonomous adaptation. We have been investigating a simplified system using artificial neural nodes to clarify the functions and configuration needed for learning in a system that autonomously adapts to the environment. We demonstrated that phenomenal consciousness is explained using a method of "virtualization" in the information system and that learning activities in a whole system adaptation are related to consciousness. However, we have not sufficiently clarified the learning activities of such a system. Consciousness is basically modeled as a system-level learning activity to modify both its own configuration and states in autonomous adaptation through investigating learning activities as a whole system. The model not only explains the time delay in Libet's experiment, but is also positioned as an improved model of Global Workspace Theory (GWT).

TWO KINDS OF COMMON SENSE KNOWLEDGE (AND A CONSTRAINT FOR MACHINE CONSCIOUSNESS DESIGN) - Perconti, Pietro (International Journal of Machine Consciousness, 2013)
In this paper, it will be argued that common sense knowledge has not a unitary structure. It is rather articulated at two different levels: a deep and a superficial level of common sense. The deep level is based on know-how procedures, on metaphorical frames built on imaginative bodily representations, and on a set of adaptive behaviors. Superficial level includes beliefs and judgments. They can be true or false and are culture dependent. Deep common sense is unavailable for any fast change, because it depends more on human biology than on cultural conventions. The deep level of common sense is characterized by a sensorimotor representational format, while the superficial level is largely made by propositional entities. This difference can be considered as a constraint for machine consciousness design, insofar this latter should be based on a reliable model of common sense knowledge.

The rise of machine consciousness: Studying consciousness with computational models - Reggia, James A. (Neural Networks, 2013)
Efforts to create computational models of consciousness have accelerated over the last two decades, creating a field that has become known as artificial consciousness. There have been two main motivations for this controversial work: to develop a better scientific understanding of the nature of human/animal consciousness and to produce machines that genuinely exhibit conscious awareness. This review begins by briefly explaining some of the concepts and terminology used by investigators working on machine consciousness, and summarizes key neurobiological correlates of human consciousness that are particularly relevant to past computational studies. Models of consciousness developed over the last twenty years are then surveyed. These models are largely found to fall into five categories based on the fundamental issue that their developers have selected as being most central to consciousness: a global workspace, information integration, an internal self-model, higher-level representations, or attention mechanisms. For each of these five categories, an overview of past work is given, a representative example is presented in some detail to illustrate the approach, and comments are provided on the contributions and limitations of the methodology. Three conclusions are offered about the state of the field based on this review: (1) computational modeling has become an effective and accepted methodology for the scientific study of consciousness, (2) existing computational models have successfully captured a number of neurobiological, cognitive, and behavioral correlates of conscious information processing as machine simulations, and (3) no existing approach to artificial consciousness has presented a compelling demonstration of phenomenal machine consciousness, or even clear evidence that artificial phenomenal consciousness will eventually be possible. The paper concludes by discussing the importance of continuing work in this area, considering the ethical issues it raises, and making predictions concerning future developments.

SAFE/MORAL AUTOPOIESIS AND CONSCIOUSNESS - Waser, Mark R. (International Journal of Machine Consciousness, 2013)
Artificial intelligence, the "science and engineering of intelligent machines", still has yet to create even a simple "Advice Taker" [McCarthy, 1959]. We have previously argued [Waser, 2011] that this is because researchers are focused on problem-solving or the rigorous analysis of intelligence (or arguments about consciousness) rather than the creation of a "self" that can "learn" to be intelligent. Therefore, following expert advice on the nature of self [Llinas, 2001; Hofstadter, 2007; Damasio, 2010], we embarked upon an effort to design and implement a self-understanding, self-improving loop as the totality of a (seed) AI. As part of that, we decided to follow up on Richard Dawkins' [1976] speculation that "perhaps consciousness arises when the brain's simulation of the world becomes so complete that it must include a model of itself" by defining a number of axioms and following them through to their logical conclusions. The results combined with an enactive approach yielded many surprising and useful implications for further understanding consciousness, self, and "free-will" that continue to pave the way towards the creation of safe/moral autopoiesis.

The (lack of) mental life of some machines - Fekete, Tomer; Edelman, Shimon (Advances in Consciousness Research, 2012)
The proponents of machine consciousness predicate the mental life of a machine, if any, exclusively on its formal, organizational structure, rather than on its physical composition. Given that matter is organized on a range of levels in time and space, this generic stance must be further constrained by a principled choice of levels on which the posited structure is supposed to reside. Indeed, not only must the formal structure fit well the physical system that realizes it, but it must do so in a manner that is determined by the system itself, simply because the mental life of a machine cannot be up to an external observer. To illustrate just how tall this order is, we carefully analyze the scenario in which a digital computer simulates a network of neurons. We show that the formal correspondence between the two systems thereby established is at best partial, and, furthermore, that it is fundamentally incapable of realizing both some of the essential properties of actual neuronal systems and some of the fundamental properties of experience. Our analysis suggests that, if machine consciousness is at all possible, conscious experience can only be instantiated in a class of machines that are entirely different from digital computers, namely, timecontinuous, open analog dynamical systems.

“Machine” consciousness and “artificial” thought: An operational architectonics model guided approach - Fingelkurts, Andrew A.; Fingelkurts, Alexander A.; Neves, Carlos F. H. (Brain Research, 2012)
Instead of using low-level neurophysiology mimicking and exploratory programming methods commonly used in the machine consciousness field, the hierarchical operational architectonics (OA) framework of brain and mind functioning proposes an alternative conceptual–theoretical framework as a new direction in the area of model-driven machine (robot) consciousness engineering. The unified brain–mind theoretical OA model explicitly captures (though in an informal way) the basic essence of brain functional architecture, which indeed constitutes a theory of consciousness. The OA describes the neurophysiological basis of the phenomenal level of brain organization. In this context the problem of producing man-made “machine” consciousness and “artificial” thought is a matter of duplicating all levels of the operational architectonics hierarchy (with its inherent rules and mechanisms) found in the brain electromagnetic field. We hope that the conceptual–theoretical framework described in this paper will stimulate the interest of mathematicians and/or computer scientists to abstract and formalize principles of hierarchy of brain operations which are the building blocks for phenomenal consciousness and thought.
Keywords: Artificial mind; Brain architecture; Conscious operation; EEG; Many-body field dynamics; Metastability; Operational architectonics; Robot

The Engineering Thesis in Machine Consciousness - Boltuc, Piotr (Techné: Research in Philosophy and Technology, 2012)
I argue here that consciousness can be engineered. The claim that functional consciousness can be engineered has been persuasively put forth in regards to first-person functional consciousness; robots, for instance, can recognize colors, though there is still much debate about details of this sort of consciousness. Such consciousness has now become one of the meanings of the term phenomenal consciousness (e.g., as used by Franklin and Baars). Yet, we extend the argument beyond the tradition of behaviorist or functional reductive views on consciousness that still predominate within cognitive science. If Nagel-Chalmers-Block-style non-reductive naturalism about first-person consciousness (h-consciousness) holds true, then, eventually we should be able to understand how such consciousness operates and how it gets produced (this is not the same as bridging the explanatory gap or solving Chalmers’s hard problem of consciousness). If so, the consciousness it involves can in principle be engineered.

Artificial Qualia, Intentional Systems and Machine Consciousness - Boyles, Robert James M. (Proceedings of the Research?DLSU Congress 2012: Science and Technology Conference, 2012)

A ROLE FOR CONSCIOUSNESS IN ACTION SELECTION - Bryson, Joanna J. (International Journal of Machine Consciousness, 2012)
This paper argues that conscious attention exists not so much for selecting an immediate action as for focusing learning of the action-selection mechanisms and predictive models on tasks and environmental contingencies likely to affect the conscious agent. It is perfectly possible to build this sort of system into machine intelligence, but it is not strictly necessary unless the intelligence needs to learn and is resource-bounded with respect to the rate of learning vs. the rate of relevant environmental change. Support of this theory is drawn from scientific research and AI simulations, and a few consequences are suggested with respect to self consciousness and ethical obligations to and for AI.

Machine Minds: The Blueprint for Artificial Consciousness - Chatterjee, Sidharta (SSRN Electronic Journal, 2012)
The paper proposes the design approach as a blueprint for building a sentient artificial agent capable of exhibiting humanlike attributions of consciousness. The paper also considers whether if such an artificial agent is ever built, how it will be indistinguishable from a human being? Well, it is glowingly evident that the evolution of artificial intelligence is guided by us, humans, whose own mental evolution have been shaped by the passing years in the course of the phenomenology of adaptation and survival (Darwinian). Yet, the evolution of synthetic minds powered by artificial cognition seems to be quite fast. Yes, the artificial mind in robots, if we accept the analogy 'mind' in its fullest sense, that day is not very far when the mental embodiment of consciousness in machines would become reality. But prior to such a feat becoming reality, rhetoric debates have been taking shape as of, how to decode and cipher consciousness in machines, a phenomenon considered as often as 'nonentity', then, what would be the true essence of such an artificial consciousness? This paper discusses these aspects and attempts to throw some new light on the design and developmental aspects of artificial consciousness.

The Cognitive Architecture for Artificial Consciousness: Machine Mental States - Chatterjee, Sidharta (SSRN Electronic Journal, 2012)
In recent years, a classic problem regarding designing of artificial minds embedded with synthetic consciousness has resurfaced in the tune of; 1) building a machine or robots that would closely mimic human behavior, and 2) the problem of embodiment of consciousness in artificial forms in such entities. These two problems boil down to the pure consideration as well of standardization of another aspect- the design concepts; of whether they would look-alike human beings in artificial flesh and skin, or rather be designed entirety as original architecture having shape-implicit forms of embodied cognition which could stand as true peers of human race. The first problem is to deal with the art and science of imitating human behavior, whereas, the subsequent problems should specifically deal with the predicament of abstraction and embodiment of mental attributions primarily, consciousness in machines. Whilst the final dilemma could be the consideration of some standard design models that would likely reflect the nature of such embodied consciousness. In such endeavor, I discuss both the design approach to imitate human abilities in machines as well, the modeling of human consciousness in robots within some relational framework for orientation of mental attributions in such sense that would satisfy evolution of robot consciousness.

SYNTHETIC PHENOMENOLOGY AND HIGH-DIMENSIONAL BUFFER HYPOTHESIS - Chella, Antonio; Gaglio, Salvatore (International Journal of Machine Consciousness, 2012)
Synthetic phenomenology typically focuses on the analysis of simplified perceptual signals with small or reduced dimensionality. Instead, synthetic phenomenology should be analyzed in terms of perceptual signals with huge dimensionality. Effective phenomenal processes actually exploit the entire richness of the dynamic perceptual signals coming from the retina. The hypothesis of a high-dimensional buffer at the basis of the perception loop that generates the robot synthetic phenomenology is analyzed in terms of a cognitive architecture for robot vision the authors have developed over the years. Despite the obvious computational problems when dealing with high-dimensional vectors, spaces with increased dimensionality could be a boon when searching for global minima. A simplified setup based on static scene analysis and a more complex setup based on the CiceRobot robot are discussed.

TIME, CONSCIOUSNESS, AND MIND UPLOADING - Choe, Yoonsuck; Kwon, Jaerock; Chung, Ji Ryang (International Journal of Machine Consciousness, 2012)
The function of the brain is intricately woven into the fabric of time. Functions such as (i) storing and accessing past memories, (ii) dealing with immediate sensorimotor needs in the present, and (iii) projecting into the future for goal-directed behavior are good examples of how key brain processes are integrated into time. Moreover, it can even seem that the brain generates time (in the psychological sense, not in the physical sense) since, without the brain, a living organism cannot have the notion of past nor future. When combined with an evolutionary perspective, this seemingly straightforward idea that the brain enables the conceptualization of past and future can lead to deeper insights into the principles of brain function, including that of consciousness. In this paper, we systematically investigate, through simulated evolution of artificial neural networks, conditions for the emergence of past and future in simple neural architectures, and discuss the implications of our findings for consciousness and mind uploading.

EMPIRICALLY GROUNDED CLAIMS ABOUT CONSCIOUSNESS IN COMPUTERS - Gamez, David (International Journal of Machine Consciousness, 2012)
Research is starting to identify correlations between consciousness and some of the spatiotemporal patterns in the physical brain. For theoretical and practical reasons, the results of experiments on the correlates of consciousness have ambiguous interpretations. At any point in time a number of hypotheses co-exist about and the correlates of consciousness in the brain, which are all compatible with the current experimental results. This paper argues that consciousness should be attributed to any system that exhibits spatiotemporal physical patterns that match the hypotheses about the correlates of consciousness that are compatible with the current experimental results. Some computers running some programs should be attributed consciousness because they produce spatiotemporal patterns in the physical world that match those that are potentially linked with consciousness in the human brain.

EXPERIMENTAL RESEARCH IN WHOLE BRAIN EMULATION: THE NEED FOR INNOVATIVE IN VIVO MEASUREMENT TECHNIQUES - Koene, Randal A. (International Journal of Machine Consciousness, 2012)
Whole brain emulation aims to re-implement functions of a mind in another computational substrate by carefully emulating the function of fundamental components, and by copying the connectivity between those components. The precision with which this is done must enable prediction of the natural development of active states. To accomplish this, in vivo measurements at large scale and high resolution are critically important. We propose a set of requirements for these empirical measurements. We then outline general methods leading to acquisition of a structural and functional connectome, and to the characterization of responses at large scale and high resolution. Finally, we describe two new project developments that tackle the problem of functional recording in vivo, namely the "molecular ticker-tape" and the integrated-circuit "Cyborcell".

Cortical artificial neural networks and their evolution - Consciousness-inspired data mining - Neukart, Florian; Moraru, Sorin-Aurel; Grigorescu, Costin-Marius; Szakacs-Simon, Peter (2012 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), 2012)
When trying to solve classification or time-series prediction problem statements by the application of Artificial Neural Networks (ANNs), commonly applied structures like feed forward or recurrent Multi-Layer Perceptrons (MLP) characteristically tend to come up with bad performance and accuracy. This is especially the case when dealing with manifold datasets containing numerous input (predictors) and/or targetattributes and independent from the applied learning methods, activation functions, biases, etc... The cortical ANN, inspired by theoretical aspects of the human consciousness and its signal processing, is an ANN structure having been developed during the research phase of the “System applying High Order Computational Intelligence” (SHOCID) project. Due to its structure, redundancy and error-tolerance is being created, which helps to elude the latterly mentioned problems. Within this elaboration, the cortical ANN is being introduced, as well as an algorithm for evolving this special ANN types' structure until the most suitable solution has been detected.

How to Build a Robot that is Conscious and Feels - O’Regan, J. Kevin (Minds and Machines, 2012)
Following arguments put forward in my book (Why red doesn’t sound like a bell: understanding the feel of consciousness. Oxford University Press, New York, USA, 2011), this article takes a pragmatic, scientist’s point of view about the concepts of consciousness and “feel”, pinning down what people generally mean when they talk about these concepts, and then investigating to what extent these capacities could be implemented in non-biological machines. Although the question of “feel”, or “phenomenal consciousness” as it is called by some philosophers, is generally considered to be the “hard” problem of consciousness, the article shows that by taking a “sensorimotor” approach, the difficulties can be overcome. What remains to account for are the notions of so-called “access consciousness” and the self. I claim that though they are undoubtedly very difficult, these are not logically impossible to implement in robots.

SEEKING NORMATIVE GUIDELINES FOR NOVEL FUTURE FORMS OF CONSCIOUSNESS - Oto, Brandon (International Journal of Machine Consciousness, 2012)
The potential for the near-future development of two technologies — artificial forms of intelligence, as well as the ability to "upload" human minds into artificial forms — raises several ethical questions regarding the proper treatment and understanding of these artificial minds. The crux of the dilemma is whether or not such creations should be accorded the same rights we currently grant humans, and this question seems to hinge upon whether they will exhibit their own "subjectivity", or internal viewpoints. Recognizing this as the essential factor yields some ethical guidance, but these issues need further exploration before such technologies become available.

A COGNITIVE ARCHITECTURE WITH INCREMENTAL LEVELS OF MACHINE CONSCIOUSNESS INSPIRED BY COGNITIVE NEUROSCIENCE - Raizer, Klaus; Paraense, André L. O.; Gudwin, Ricardo R. (International Journal of Machine Consciousness, 2012)
The main motivation for this work is to investigate the advantages provided by machine consciousness, while in the control of software agents. In order to pursue this goal, we developed a cognitive architecture, with different levels of machine consciousness, targeting the control of artificial creatures. As a standard guideline, we applied cognitive neuroscience concepts to incrementally develop the cognitive architecture, following the evolutionary steps taken by the animal brain. The triune brain theory proposed by MacLean, together with Arrabale's "ConsScale", serve as roadmaps to achieve each developmental stage, while iCub — a humanoid robot and its simulator — serve as a platform for the experiments. A completely codelet-based system "Core" has been implemented, serving the whole architecture.

THE TERASEM MIND UPLOADING EXPERIMENT - Rothblatt, Martine (International Journal of Machine Consciousness, 2012)
The Terasem Mind Uploading Experiment is a multi-decade test of the comparability of single person actual human consciousness as assessed by expert psychological review of their digitized interactions with same person purported human consciousness as assessed by expert psychological interviews of personality software that draws upon a database comprised of the original actual person's digitized interactions. The experiment is based upon a hypothesis that the paper analyzes for its conformance with scientific testability in accordance with the criteria set forth by Karl Popper. Strengths and weaknesses of both the hypothesis and the experiment are assessed in terms of other tests of digital consciousness, scientific rigor and good clinical practices. Recommendations for improvement include stronger parametrization of endpoint assessment and better attention to compliance with informed consent in the event there is emergence of software-based consciousness.

Phenomenal Consciousness, Attention and Accessibility - Schlicht, Tobias (Phenomenology and the Cognitive Sciences, 2012)

CAN FUNCTIONAL AND PHENOMENAL CONSCIOUSNESS BE DIVIDED? - Taylor, J. G. (International Journal of Machine Consciousness, 2012)
We answer the question raised by the title by developing a neural architecture for the attention control system in animals in a hierarchical manner, following what we conjecture is an evolutionary path. The resulting evolutionary model (based on CODAM at the highest level) and answer to the question allow us to consider both different forms of consciousness as well as how machine consciousness could itself possess a variety of forms.

SUPER-INTELLIGENCE AND (SUPER-)CONSCIOUSNESS - Torrance, Steve (International Journal of Machine Consciousness, 2012)
In this paper, the notion of super-intelligence (or "AI++", as Chalmers has termed it) is considered in the context of machine consciousness (MC) research. Suppose AI++ were to come about, would real MC have then also arrived, "for free"? (I call this the "drop-out question".) Does the idea tempt you, as an MC investigator? What are the various positions that might be adopted on the issue of whether an AI++ would necessarily (or with strong likelihood) be a conscious AI++? Would a conscious super-intelligence also be a super-consciousness? (Indeed, what meaning might be attached to the notion of "super-consciousness"?) What ethical and social consequences might be drawn from the idea of conscious super-AIs or from that of artificial super-consciousness? And what implications does this issue have for technical progress on MC in a pre-AI++ world? These and other questions are considered.

Human-like learning in a conscious agent - Faghihi, U.; , Poirier ,P.; , Fournier-Viger ,P.; and Nkambou, R. (Journal of Experimental & Theoretical Artificial Intelligence, 2011)
In this article, we propose the Conscious-Emotional Learning Tutoring System technology, a biologically plausible cognitive agent based on human brain functions. This agent is capable of learning and remembering events and any related information such as corresponding procedures, stimuli and their emotional valences. In our model, emotions play a role in the encoding and remembering of events. This allows the agent to improve its behaviour or by remembering previously selected behaviours which were influenced by its emotional mechanism. Moreover, the architecture incorporates a realistic memory consolidation process based on a data mining algorithm.
Keywords: cognitive agent; emotions; episodic learning

Robot pains and corporate feelings - Machery, Edouard; Sytsma, Justin (The Philosophers' Magazine, 2011)
Most philosophers of mind follow Thomas Nagel and hold that subjective experiences are characterised by the fact that there is “something it is like” to have them. Philosophers of mind have sometimes speculated that ordinary people endorse, perhaps implicitly, this conception of subjective experiences. Some recent findings cast doubt on this view.

The case for using brain-based devices to study consciousness - Fleischer, Jason G.; McKinstry, Jeffrey L.; Edelman, David B.; Edelman, Gerald M. (Neuromorphic and Brain-Based Robots, 2011)

TOWARDS MACHINE CONSCIOUSNESS: GROUNDING ABSTRACT MODELS AS π-PROCESSES - Bonzon, Pierre (International Journal of Machine Consciousness, 2011)
We present a two-level model of concurrent communicating systems (CCS) to serve as a basis for machine consciousness. A language implementing threads within logic programming is first introduced. This high-level framework allows for the definition of abstract processes that can be executed on a virtual machine. We then look for a possible grounding of these processes into the brain. Towards this end, we map abstract definitions (including logical expressions representing compiled knowledge) into a variant of the π-calculus. We illustrate this approach through a series of examples extending from a purely reactive behavior to patterns of consciousness.
Keywords: Computational correlates of consciousness; concurrent communicating systems; π-calculus

On the status of computationalism as a law of nature - Hales, Colin (International Journal of Machine Consciousness, 2011)
Scientific behavior is used as a benchmark to examine the truth status of computationalism (COMP) as a law of nature. A COMP-based artificial scientist is examined from three simple perspectives to see if they shed light on the truth or falsehood of COMP through its ability or otherwise, to deliver authentic original science on the a priori unknown like humans do. The first perspective (A) looks at the handling of ignorance and supports a claim that COMP is "trivially true" or "pragmatically false" in the sense that you can simulate a scientist if you already know everything, which is a state that renders the simulation possible but pointless. The second scenario (B) is more conclusive and unusual in that it reveals that the COMP scientist can never propose/debate that COMP is a law of nature. This marked difference between the human and the artificial scientist in this single, very specific circumstance, means that COMP cannot be true as a general claim. The third scenario (C) examines the artificial scientist's ability to do science on itself/humans to uncover the "law of nature" which results in itself. This scenario reveals that a successful test for scientific behavior by a COMP-based artificial scientist supports a claim that COMP is true. Such a test is quite practical and can be applied to an artificial scientist based on any design principle, not merely COMP. Scenario (C) also reveals a practical example of the COMP scientist's inability to handle informal systems (in the form of liars), which further undermines COMP. Overall, the result is that COMP is false, with certainty in one very specific, critical place. This lends support to the claims (i) that artificial general intelligence will not succeed based on COMP principles, and (ii) computationally enacted abstract models of human cognition will never create a mind.
Keywords: Artificial intelligence; computationalism; scientific method

Simulating Visual Qualia in the CERA-CRANIUM Cognitive Architecture - Arrabales, Raúl; Ledezma, Agapito; Sanchis, Araceli (Springer, 2011)
The concept of qualia poses a central problem in the framework of consciousness studies. Despite it being a controversial issue even in the study of human consciousness, we argue that qualia can be complementarily studied using artificial cognitive architectures. In this work we address the problem of defining qualia in the domain of artificial systems, providing a model of “artificial qualia”. Furthermore, we partially apply the proposed model to the generation of visual qualia using the cognitive architecture CERA-CRANIUM, which is modeled after the global workspace theory of consciousness. It is our aim to define, characterize and identify artificial qualia as direct products of a simulated conscious perception process. Simple forms of the apparent motion effect are used as the basis for a preliminary experimental setting focused on the simulation and analysis of synthetic visual experience. In contrast with the study of biological brains, the inspection of the dynamics and transient inner states of the artificial cognitive architecture can be performed effectively, thus enabling the detailed analysis of covert and overt percepts generated by the system when it is confronted with specific visual stimuli. The observed states in the artificial cognitive architecture during the simulation of apparent motion effects are used to discuss the existence of possible analogous mechanisms in human cognition processes.

HYPERSET MODELS OF SELF, WILL AND REFLECTIVE CONSCIOUSNESS - Goertzel, Ben (International Journal of Machine Consciousness, 2011)
A novel theory of reflective consciousness, will and self is presented, based on modeling each of these entities using self-referential mathematical structures called hypersets. Pattern theory is used to argue that these exotic mathematical structures may meaningfully be considered as parts of the minds of physical systems, even finite computational systems. The hyperset models presented are hypothesized to occur as patterns within the ”moving bubble of attention” of the human brain and any brainlike AI system. They appear to be compatible with both panpsychist and materialist views of consciousness, and probably other views as well.

Self-Aware Intelligent Agents in the Prisoner's Dilemma - Huang, Chung-Yuan; Wang, Sheng-Wen; Sun, Chuen-Tsai (2011 International Conference on Future Computer Sciences and Application (ICFCSA), 2011)
Self-aware individuals are more likely to consider whether their actions are appropriate in terms of public self-consciousness, and to use that information to execute behaviors that match external standards and/or expectations. The learning concepts through which individuals monitor themselves have generally been overlooked by artificial intelligence researchers. Here we report on our attempt to integrate a self-awareness mechanism into an agent's learning architecture. Specifically, we describe (a) our proposal for a self-aware agent model that includes an external learning mechanism and internal cognitive capacity with super-ego and ego characteristics; and (b) our application of a version of the iterated prisoner's dilemma representing conflicts between the public good and private interests to analyze the effects of self-awareness on an agent's individual performance and cooperative behavior. Our results indicate that self-aware agents that consider public self-consciousness utilize rational analysis in a manner that promotes cooperative behavior and supports faster societal movement toward stability. We found that a small number of self-aware agents are sufficient for improving social benefits and resolving problems associated with collective irrational behaviors.

Toward incorporating emotions with rationality into a communicative virtual agent - Kiselev, Andrey; Hacker, Benjamin Alexander; Wankerl, Thomas; Abdikeev, Niyaz; Nishida, Toyoaki (AI & SOCIETY, 2011)
This paper addresses the problem of human–computer interactions when the computer can interpret and express a kind of human-like behavior, offering natural communication. A conceptual framework for incorporating emotions with rationality is proposed. A model of affective social interactions is described. The model utilizes the SAIBA framework, which distinguishes among several stages of processing of information. The SAIBA framework is extended, and a model is realized in human behavior detection, human behavior interpretation, intention planning, attention tracking behavior planning, and behavior realization components. Two models of incorporating emotions with rationality into a virtual artifact are presented. The first one uses an implicit implementation of emotions. The second one has an explicit realization of a three-layered model of emotions, which is highly interconnected with other components of the system. Details of the model with implicit implementation of emotional behavior are shown as well as evaluation methodology and results. Discussions about the extended model of an agent are given in the final part of the paper.

IS CONSCIOUSNESS JUST CONSCIOUS BEHAVIOR? - Manzotti, Riccardo (International Journal of Machine Consciousness, 2011)
Shanahan's work admirably and convincingly supports Baars' global workspace by means of plausible and updated neural models. Yet little of his work is related with the issue of consciousness as phenomenal experience. He focuses his effort mostly on the behavioral correlates of consciousness like autonomy, flexibility, and information integration. Moreover, although the importance of embodiment and situated cognition is emphasized, most of the conceptual tools suggested (dynamic systems, complex networks, global workspace) require the external world only during their development. Leaving aside the issue of phenomenal experience, the book fleshes out a convincing and thought-provoking model for many aspects of conscious behaviour.

BRAIN-BASED ELEMENTARY AUTO-REFLECTION MECHANISMS FOR CONSCIOUS ROBOTS: SOME PHILOSOPHICAL IMPLICATIONS - Mitterauer, Bernhard J. (International Journal of Machine Consciousness, 2011)
A brain model based on glial-neuronal interactions is proposed. Glial-neuronal synaptic units are interpreted as elementary reflection mechanisms, called proemial synapses. In glial networks (syncytia), cyclic intentional programs are generated, interpreted as auto-reflective intentional programming. Both types of reflection mechanisms are formally described and may be implementable in a robot brain. Based on the logic of acceptance and rejection, the robot is capable of rejecting irrelevant environmental information, showing at least a "touch" of subjective behavior. Since reflective intentional programming generates both relevant and irrelevant structures already within the brain, ontological gaps arise which must be integrated. In the human brain, the act of self-reference may exert a holistic function enabling self-consciousness. However, since the act of self-reference is a mysterious function not experimentally testable in brain research, it cannot be implemented in a robot brain. Therefore, the creation of self-conscious robots may never be possible. Finally, some philosophical implications are discussed.

A COMPUTATIONAL MODEL OF MACHINE CONSCIOUSNESS - Starzyk, Janusz A.; Prasad, Dilip K. (International Journal of Machine Consciousness, 2011)
Despite many efforts, there are no computational models of consciousness that can be used to design conscious intelligent machines. This is mainly attributed to available definitions of consciousness being human centered, vague, and incomplete. Through a biological analysis of consciousness and concept of machine intelligence, we propose a physical definition of consciousness with the hope to model it in intelligent machines. We propose a computational model of consciousness driven by competing motivations, goals, and attention-switching. We propose a concept of mental saccades that is useful for explaining the attention-switching and focusing mechanism from computational perspective. Finally, we compare our model with other computational models of consciousness.

IS CONSCIOUSNESS ONLY CONTENT, OR IS THERE MORE? - Taylor, J. G. (International Journal of Machine Consciousness, 2011)

CONSCIOUSNESS FOR THE OUROBOROS MODEL - Thomsen, Knud (International Journal of Machine Consciousness, 2011)
The Ouroboros Model features a biologically inspired cognitive architecture. At its core lies a self-referential recursive process with alternating phases of data acquisition and evaluation. Memory entries are organized in schemata. The activation at a time of part of a schema biases the whole structure and, in particular, missing features, thus triggering expectations. An iterative recursive monitor process termed \consumption analysis" is then checking how well such expectations ̄t with successive activations. Mismatches between anticipations based on previous experience and actual current data are highlighted and used for controlling the allocation of attention. In case no directly ̄tting ̄ller for an open slot is found, activation spreads more widely and includes data relating to the actor, and Higher-Order Personality Activation, HOPA, ensues. It is brie°y outlined how the Ouroboros Model produces many diverse characteristics and thus addresses established criteria for consciousness. Coarse-grained relationships to selected previous conceptualizations of consciousness and a sketch of how the Ouroboros Model could shed light on current research themes in arti ̄cial general intelligence and consciousness conclude this paper.

The cognitive development of machine consciousness implementations - Arrabales, Raúl; Ledezma, Agapito; Sanchis, Araceli (International Journal of Machine Consciousness, 2010)
The progress in the machine consciousness research field has to be assessed in terms of the features demonstrated by the new models and implementations currently being designed. In this paper, we focus on the functional aspects of consciousness and propose the application of a revision of ConsScale — a biologically inspired scale for measuring cognitive development in artificial agents — in order to assess the cognitive capabilities of machine consciousness implementations. We argue that the progress in the implementation of consciousness in artificial agents can be assessed by looking at how key cognitive abilities associated to consciousness are integrated within artificial systems. Specifically, we characterize ConsScale as a partially ordered set and propose a particular dependency hierarchy for cognitive skills. Associated to that hierarchy a graphical representation of the cognitive profile of an artificial agent is presented as a helpful analytic tool. The proposed evaluation schema is discussed and applied to a number of significant machine consciousness models and implementations. Finally, the possibility of generating qualia and phenomenological states in machines is discussed in the context of the proposed analysis.
Keywords: Cognitive development; ConsScale; machine consciousness; measures of consciousness

Artificial Psychology: The Quest for What It Means to Be Human - Friedenberg, Jay (Psychology Press, 2010)
Is it possible to construct an artificial person? Researchers in the field of artificial intelligence have for decades been developing computer programs that emulate human intelligence. This book goes beyond intelligence and describes how close we are to recreating many of the other capacities that make us human. These abilities include learning, creativity, consciousness, and emotion. The attempt to understand and engineer these abilities constitutes the new interdisciplinary field of artificial psychology, which is characterized by contributions from philosophy, cognitive psychology, neuroscience, computer science, and robotics. This work is intended for use as a main or supplementary introductory textbook for a course in cognitive psychology, cognitive science, artificial intelligence, or the philosophy of mind. It examines human abilities as operating requirements that an artificial person must have and analyzes them from a multidisciplinary approach. The book is comprehensive in scope, covering traditional topics like perception, memory, and problem solving. However, it also describes recent advances in the study of free will, ethical behavior, affective architectures, social robots, and hybrid human-machine societies.

Comments on “The Replication of the Hard Problem of Consciousness in AI and Bio-AI” - Dournaee, Blake H. (Minds and Machines, 2010)
In their joint paper entitled “The Replication of the Hard Problem of Consciousness in AI and BIO-AI” (Boltuc et al. Replication of the hard problem of conscious in AI and Bio-AI: An early conceptual framework 2008), Nicholas and Piotr Boltuc suggest that machines could be equipped with phenomenal consciousness, which is subjective consciousness that satisfies Chalmer’s hard problem (We will abbreviate the hard problem of consciousness as “H-consciousness”). The claim is that if we knew the inner workings of phenomenal consciousness and could understand its’ precise operation, we could instantiate such consciousness in a machine. This claim, called the extra-strong AI thesis, is an important claim because if true it would demystify the privileged access problem of first-person consciousness and cast it as an empirical problem of science and not a fundamental question of philosophy. A core assumption of the extra-strong AI thesis is that there is no logical argument that precludes the implementation of H-consciousness in an organic or in-organic machine provided we understand its algorithm. Another way of framing this conclusion is that there is nothing special about H-consciousness as compared to any other process. That is, in the same way that we do not preclude a machine from implementing photosynthesis, we also do not preclude a machine from implementing H-consciousness. While one may be more difficult in practice, it is a problem of science and engineering, and no longer a philosophical question. I propose that Boltuc’s conclusion, while plausible and convincing, comes at a very high price; the argument given for his conclusion does not exclude any conceivable process from machine implementation. In short, if we make some assumptions about the equivalence of a rough notion of algorithm and then tie this to human understanding, all logical preconditions vanish and the argument grants that any process can be implemented in a machine. The purpose of this paper is to comment on the argument for his conclusion and offer additional properties of H-consciousness that can be used to make the conclusion falsifiable through scientific investigation rather than relying on the limits of human understanding.
Keywords: Artificial Intelligence; Hard problem of consciousness; Phenomenal consciousness; Strong AI; Turing machine; Weak AI

A High Level Model of a Conscious Embodied Agent: - Wiedermann, Jiří (International Journal of Software Science and Computational Intelligence, 2010)
In this paper, the author describes a simple yet cognitively powerful architecture of an embodied conscious agent. The architecture incorporates a mechanism for mining, representing, processing and exploiting semantic knowledge. This mechanism is based on two complementary internal world models which are built automatically. One model (based on artificial mirror neurons) is used for mining and capturing the syntax of the recognized part of the environment while the second one (based on neural nets) for its semantics. Jointly, the models support algorithmic processes underlying phenomena similar in important aspects to higher cognitive functions such as imitation learning and the development of communication, language, thinking, and consciousness.

Embodiment and the inner lifeCognition and Consciousness in the Space of Possible Minds - Shanahan, Murray (Oxford University Press, 2010)
To understand the mind and its place in Nature is one of the great intellectual challenges of our time, a challenge that is both scientific and philosophical. How does cognition influence an animal's behaviour? What are its neural underpinnings? How is the inner life of a human being constituted? What are the neural underpinnings of the conscious condition? This book approaches each of these questions from a scientific standpoint. But it contends that, before we can make progress on them, we have to give up the habit of thinking metaphysically, a habit that creates a fog of philosophical confusion. From this post-reflective point of view, the book argues for an intimate relationship between cognition, sensorimotor embodiment, and the integrative character of the conscious condition. Drawing on insights from psychology, neuroscience, and dynamical systems, it proposes an empirical theory of this three-way relationship whose principles, not being tied to the contingencies of biology or physics, are applicable to the whole space of possible minds in which humans and other animals are included. The book provides a joined-up theory of consciousness.

Sloman and h-consciousness - Boltuc, Piotr (International Journal of Machine Consciousness, 2010)
Sloman criticizes all existing attempts to define machine consciousness for being overly one-sided. He argues that such definition is not only unattainable but also unnecessary. The critique is well taken in part; yet, whatever his intended aims, by not acknowledging the non-reductive aspects of consciousness, Sloman, in fact, sides with the reductivist view.

Consciousness or consciousnesses? modeling for disentangling - Castelfranchi, Cristiano (International Journal of Machine Consciousness, 2010)
After discussing a possible contradiction in Sloman's very challenging intervention, I stress the need for not identifying "consciousness" with phenomenal consciousness and with the "qualia" problem. I claim that it is necessary to distinguish different forms and functions of "consciousness" and to explicitly model them, also by exploiting the specific advantage of AI: to make experiments impossible in nature, by separating what cannot be separated in human behavior/mind. As for phenomenal consciousness, one should first be able to model what it means to have a "body" and to "feel" it.

Which kind of machine consciousness? - Cordeschi, Roberto (International Journal of Machine Consciousness, 2010)

MEETING FLORIDI'S CHALLENGE TO ARTIFICIAL INTELLIGENCE FROM THE KNOWLEDGE‐GAME TEST FOR SELF‐CONSCIOUSNESS - Bringsjord, Selmer (Metaphilosophy, 2010)
Abstract: In the course of seeking an answer to the question “How do you know you are not a zombie?” Floridi (2005) issues an ingenious, philosophically rich challenge to artificial intelligence (AI) in the form of an extremely demanding version of the so‐called knowledge game (or “wise‐man puzzle,” or “muddy‐children puzzle”)—one that purportedly ensures that those who pass it are self‐conscious. In this article, on behalf of (at least the logic‐based variety of) AI, I take up the challenge—which is to say, I try to show that this challenge can in fact be met by AI in the foreseeable future.

Developing a Consciousness-Based Mind for an Artificial Creature - da Silva, Ricardo Capitanio Martins; Gudwin, Ricardo Ribeiro (Springer, 2010)
This work describes the application of the Baars-Franklin Architecture (BFA), an artificial consciousness approach, to synthesize a mind (a control system) for an artificial creature. Firstly we introduce the theoretical foundations of this approach for the development of a conscious agent. Then we explain the architecture of our agent and at the end we discuss the results and first impressions of this approach.

Natural and Artificial Intelligence, Language, Consciousness, Emotion, and Anticipation - Dubois, Daniel M. (COMPUTING ANTICIPATORY SYSTEMS: CASYS ‘09: Ninth International Conference on Computing Anticipatory Systems, 2010)
The classical paradigm of the neural brain as the seat of human natural intelligence is too restrictive. This paper defends the idea that the neural ectoderm is the actual brain, based on the development of the human embryo. Indeed, the neural ectoderm includes the neural crest, given by pigment cells in the skin and ganglia of the autonomic nervous system, and the neural tube, given by the brain, the spinal cord, and motor neurons. So the brain is completely integrated in the ectoderm, and cannot work alone. The paper presents fundamental properties of the brain as follows. Firstly, Paul D. MacLean proposed the triune human brain, which consists to three brains in one, following the species evolution, given by the reptilian complex, the limbic system, and the neo-cortex. Secondly, the consciousness and conscious awareness are analysed. Thirdly, the anticipatory unconscious free will and conscious free veto are described in agreement with the experiments of Benjamin Libet. Fourthly, the main section explains the development of the human embryo and shows that the neural ectoderm is the whole neural brain. Fifthly, a conjecture is proposed that the neural brain is completely programmed with scripts written in biological low-level and high-level languages, in a manner similar to the programmed cells by the genetic code. Finally, it is concluded that the proposition of the neural ectoderm as the whole neural brain is a breakthrough in the understanding of the natural intelligence, and also in the future design of robots with artificial intelligence.

IS IT TIME FOR THE NEW COGNITIVE REVOLUTION? - Samsonovich, Alexei V. (International Journal of Machine Consciousness, 2010)

AN ALTERNATIVE TO WORKING ON MACHINE CONSCIOUSNESS - Sloman, Aaron (International Journal of Machine Consciousness, 2010)
This paper extends three decades of work arguing that researchers who discuss consciousness should not restrict themselves only to (adult) human minds, but should study (and attempt to model) many kinds of minds, natural and artificial, thereby contributing to our understanding of the space containing all of them. We need to study what they do or can do, how they can do it, and how the natural ones can be emulated in synthetic minds. That requires: (a) understanding sets of requirements that are met by different sorts of minds, i.e. the niches that they occupy, (b) understanding the space of possible designs, and (c) understanding complex and varied relationships between requirements and designs. Attempts to model or explain any particular phenomenon, such as vision, emotion, learning, language use, or consciousness lead to muddle and confusion unless they are placed in that broader context. A methodology for making progress is summarised and a novel requirement proposed for a theory of how human minds work: the theory should support a single generic design for a learning, developing system that, in addition to meeting familiar requirements, should be capable of developing different and opposed philosophical viewpoints about consciousness, and the so-called hard problem. In other words, we need a common explanation for the mental machinations of mysterians, materialists, functionalists, identity theorists, and those who regard all such theories as attempting to answer incoherent questions. No designs proposed so far come close.

MACHINE CONSCIOUSNESS: RESPONSE TO COMMENTARIES - Sloman, Aaron (International Journal of Machine Consciousness, 2010)
This is a reply to commentaries on my article "An Alternative to Working on Machine Consciousness". Reading the commentaries caused me to write a lengthy background tutorial paper explaining some of the assumptions that were taken for granted in the target article, and pointing out various confusions regarding the notion of consciousness, including many related to its polymorphism, taken for granted in the target article. This response to commentaries builds on that background material, attempting to address the main questions, objections and misunderstandings found in the responses, several of which were a result of my own brevity and lack of clarity in the original target article, now remedied, I hope by the background article [Sloman, 2010b].

PHENOMENAL AND ACCESS CONSCIOUSNESS AND THE "HARD" PROBLEM: A VIEW FROM THE DESIGNER STANCE - Sloman, Aaron (International Journal of Machine Consciousness, 2010)
This paper is an attempt to summarise and justify critical comments I have been making over several decades about research on consciousness by philosophers, scientists and engineers. This includes (a) explaining why the concept of "phenomenal consciousness" (P-C), in the sense defined by Ned Block, is semantically flawed and unsuitable as a target for scientific research or machine modelling, whereas something like the concept of "access consciousness" (A-C) with which it is often contrasted refers to phenomena that can be described and explained within a future scientific theory, and (b) explaining why the "hard problem" is a bogus problem, because of its dependence on the P-C concept. It is compared with another bogus problem, "the 'hard' problem of spatial identity" introduced as part of a tutorial on semantically flawed concepts. Different types of semantic flaw and conceptual confusion not normally studied outside analytical philosophy are distinguished. The semantic flaws of the "zombie" argument, closely allied with the P-C concept are also explained. These topics are related both to the evolution of human and animal minds and brains and to requirements for human-like robots. The diversity of the phenomena related to the concept "consciousness" as ordinarily used makes it a polymorphic concept, partly analogous to concepts like "efficient", "sensitive", and "impediment" all of which need extra information to be provided before they can be applied to anything, and then the criteria of applicability differ. As a result there cannot be one explanation of consciousness, one set of neural associates of consciousness, one explanation for the evolution of consciousness, nor one machine model of consciousness. We need many of each. I present a way of making progress based on what McCarthy called "the designer stance", using facts about running virtual machines, without which current computers obviously could not work. I suggest the same is true of biological minds, because biological evolution long ago "discovered" a need for something like virtual machinery for self-monitoring and self-extending information-processing systems, and produced far more sophisticated versions than human engineers have so far achieved.

Conscious machines: Memory, melody and muscular imagination - Stuart, Susan A. J. (Phenomenology and the Cognitive Sciences, 2010)
A great deal of effort has been, and continues to be, devoted to developing consciousness artificially1, and yet a similar amount of effort has gone in to demonstrating the infeasibility of the whole enterprise2. My concern in this paper is to steer some navigable channel between the two positions, laying out the necessary pre-conditions for consciousness in an artificial system, and concentrating on what needs to hold for the system to perform as a human being or other phenomenally conscious agent in an intersubjectively-demanding social and moral environment. By adopting a thick notion of embodiment – one that is bound up with the concepts of the lived body and autopoiesis [Maturana & Varela, 1987; Varela et al., 1991; and Ziemke 2003, 2007a & 2007b] – I will argue that machine phenomenology is only possible within an embodied distributed system that possesses a richly affective musculature and a nervous system such that it can, through action and repetition, develop its tactile-kinaesthetic memory, individual kinaesthetic melodies pertaining to habitual practices, and an anticipatory enactive kinaesthetic imagination. Without these capacities the system would remain unconscious, unaware of itself embodied within a world. Finally, and following on from Damasio’s [1991, 1994, 1999, & 2003] claims for the necessity of pre-reflective conscious, emotional, bodily responses for the development of an organism’s core and extended consciousness, I will argue that without these capacities any agent would be incapable of developing the sorts of somatic markers or saliency tags that enable affective reactions, and which are indispensable for effective decision-making and subsequent survival. My position, as presented here, remains agnostic about whether or not the creation of artificial consciousness is an attainable goal.

Two Conceptions of Subjective Experience - Sytsma, Justin; Machery, Edouard (Philosophical Studies, 2010)

THERE IS MORE THAN AI BENEATH THE SURFACE OF CONSCIOUSNESS - Taylor, John G. (International Journal of Machine Consciousness, 2010)

CONSCIOUSNESS AND VIRTUALITY - Trautteur, Giuseppe (International Journal of Machine Consciousness, 2010)

Fuzzy Comprehensive Evaluation-based artificial consciousness model - Zhu, Chanseng; Wang, Zhiliang (2010 8th World Congress on Intelligent Control and Automation (WCICA 2010), 2010)

Strategies for measuring machine consciousness - Arrabales, Raúl; Ledezma, Agapito; Sanchis, Araceli (International Journal of Machine Consciousness, 2009)
The accurate measurement of the level of consciousness of a creature remains a major scientific challenge, nevertheless a number of new accounts that attempt to address this problem have been proposed recently. In this paper we analyze the principles of these new measures of consciousness along with other classical approaches focusing on their applicability to Machine Consciousness (MC). Furthermore, we propose a set of requirements of what we think a suitable measure for MC should be, discussing the associated theoretical and practical issues. Using the proposed requirements as a framework for the design of an integrative measure of consciousness, we explore the possibility of designing such a measure in the context of current state of the art in consciousness studies.
Keywords: Measures of consciousness; consciousness metrics; easy problems; hard problem

Emotional cognitive steps towards consciousness - Browne, Will N.; Hussey, Richard J. (International Journal of Machine Consciousness, 2009)
The academic journey to a widely acknowledged Machine Consciousness is anticipated to be an emotional one. Both in terms of the active debate provoked by the subject and a hypothesized need to encapsulate an analogue of emotions in an artificial system in order to progress towards machine consciousness. This paper considers the inspiration that the concepts related to emotion may contribute to cognitive systems when approaching conscious-like behavior. Specifically, emotions can set goals including balancing explore versus exploit, facilitate action in unknown domains and modify existing behaviors, which are explored in cognitive robotics experiments.
Keywords: Artificial emotions; affective computing; analogues of emotion; cognitive robotics; learning classifier systems

The potential for consciousness of artificial systems - Gamez, David (International Journal of Machine Consciousness, 2009)
The question about the potential for consciousness of artificial systems has often been addressed using thought experiments, which are often problematic in the philosophy of mind. A more promising approach is to use real experiments to gather data about the correlates of consciousness in humans, and develop this data into theories that make predictions about human and artificial consciousness. A key issue with an experimental approach is that consciousness can only be measured using behavior, which places fundamental limits on our ability to identify the correlates of consciousness. This paper formalizes these limits as a distinction between type I and type II potential correlates of consciousness (PCCs). Since it is not possible to decide empirically whether type I PCCs are necessary for consciousness, it is indeterminable whether a machine that lacks neurons or hemoglobin, for example, is potentially conscious. A number of responses have been put forward to this problem, including suspension of judgment, liberal and conservative attribution of the potential for consciousness and a psychometric scale that models our judgment about the relationship between type I PCCs and consciousness.
Keywords: Chinese Room; Machine consciousness; correlates of consciousness; science; synthetic phenomenology; thought experiment; type I, type II

Machine consciousness: new opportunities for information technology industry - Haikonen, Pentti O. A. (International Journal of Machine Consciousness, 2009)
New product and system opportunities are expected to arise when the next step in information technology takes place. Existing Artificial Intelligence is based on preprogramed algorithms that operate in a mechanistic way in the computer. The computer and the program do not understand what is being processed. Without the consideration of meaning, no understanding can take place. This lack of understanding is seen as the major shortcoming of Artificial Intelligence, one that prevents it to achieve its original goal; thinking machines with full human-like cognition and intelligence. The emerging technology of Machine Consciousness is expected to remedy this shortcoming. Machine Consciousness technology is expected to create new opportunities in robotics, information technology gadgets and general information processing calling for machine understanding of auditory, visual and linguistic information.
Keywords: IT industry; artificial intelligence; machine consciousness

Qualia and conscious machines - Haikonen, Pentti O. A. (International Journal of Machine Consciousness, 2009)
It is argued that qualia are the primary way in which sensory information manifests itself in mind. Qualia are not seen as properties of the physical world, ready to be observed; instead it is argued that they are the way in which the sensory system's response to the sensed stimuli manifests itself inside the system. Systems that have qualia have direct and transparent access to this response. It is argued that even though qualia are produced inside the head, they appear to be outside because this appearance complies with our motions, small and large, in the word. To be conscious in the way that we experience it is to have qualia. True conscious machines must have qualia, but the qualities of machine qualia need not be similar to the qualities of human qualia.
Keywords: Machine consciousness; phenomenology; qualia

Why Computers Can’t Feel Pain - Bishop, Mark (Minds and Machines, 2009)
The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s (Representation & Reality, Bradford Books, Cambridge in 1988) monograph, “Representation & Reality”, which if correct, has important implications for turing machine functionalism and the prospect of ‘conscious’ machines. In the paper, instead of seeking to develop Putnam’s claim that, “everything implements every finite state automata”, I will try to establish the weaker result that, “everything implements the specific machine Q on a particular input set (x)”. Then, equating Q (x) to any putative AI program, I will show that conceding the ‘strong AI’ thesis for Q (crediting it with mental states and consciousness) opens the door to a vicious form of panpsychism whereby all open systems, (e.g. grass, rocks etc.), must instantiate conscious experience and hence that disembodied minds lurk everywhere.
Keywords: Artificial Intelligence; Computationalism; Machine consciousness; Panpsychism

A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism - Bishop, John Mark (Cognitive Computation, 2009)
The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components of cognition. Concomitantly in both science and science fiction the hope is periodically re-ignited that a man-made system can be engineered to be fully cognitive and conscious purely in virtue of its execution of an appropriate computer program. However, whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced—computation is neither necessary nor sufficient for cognition—or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction.
Keywords: Computationalism; Machine consciousness; Panpsychism

Towards conscious-like behavior in computer game characters - Arrabales, Raul; Ledezma, Agapito; Sanchis, Araceli (2009 IEEE Symposium on Computational Intelligence and Games, 2009)
The main sources of inspiration for the design of more engaging synthetic characters are existing psychological models of human cognition. Usually, these models, and the associated Artificial Intelligence (AI) techniques, are based on partial aspects of the real complex systems involved in the generation of human-like behavior. Emotions, planning, learning, user modeling, set shifting, and attention mechanisms are some remarkable examples of features typically considered in isolation within classical AI control models. Artificial cognitive architectures aim at integrating many of these aspects together into effective control systems. However, the design of this sort of architectures is not straightforward. In this paper, we argue that current research efforts in the young field of Machine Consciousness (MC) could contribute to tackle complexity and provide a useful framework for the design of more appealing synthetic characters. This hypothesis is illustrated with the application of a novel consciousness-based cognitive architecture to the development of a First Person Shooter video game character.
Keywords: Actuators; Artificial intelligence; Computer architecture; Games; Humans; Intelligent control; Production; Software agents; Software performance; Testing

The potential impact of machine consciousness in science and engineering - Aleksander, Igor (International Journal of Machine Consciousness, 2009)
This paper critically tracks the impact of the development of the machine consciousness paradigm from the incredulity of the 1990s to the structuring of the turn of this century, and the consolidation of the present time which forms the basis for guessing what might happen in the future. The underlying question is how this development may have changed our understanding of consciousness and whether an artificial version of the concept contributes to the improvement of computational machinery and robots. The paper includes some suggestions for research that might be profitable and others that may not be.
Keywords: Machine consciousness; conscious robots; phenomenology

Establishing a roadmap and metrics for conscious machines development - Arrabales, Raul; Ledezma, Agapito; Sanchis, Araceli (2009 8th IEEE International Conference on Cognitive Informatics, 2009)
From the point of view of Cognitive Informatics, consciousness can be considered as a grand integration of a number of cognitive processes. Intuitive definitions of consciousness generally involve perception, emotions, attention, self-recognition, theory of mind, volition, etc. Due to this compositional definition of the term consciousness it is usually difficult to define both what is exactly a conscious being and how consciousness could be implemented in artificial machines. When we look into the most evolved biological examples of conscious beings, like great apes or humans, the vast complexity of observed cognitive interactions in conjunction with the lack of comprehensive understanding of low level neural mechanisms makes the reverse engineering task virtually unreachable. With the aim to effectively address the problem of modeling consciousness at a cognitive level, in this work we propose a concrete developmental path in which key stages in the progressive process of building conscious machines are identified and characterized. Furthermore, a method for calculating a quantitative measure of artificial consciousness is presented. The application of the proposed framework is illustrated with the comparative study of different software agents designed to compete in a first-person shooter video game.
Keywords: Application software; Artificial intelligence; Biological system modeling; Buildings; Cognitive informatics; Concrete; Games; Humans; Reverse engineering; Software agents; Software design; cognitive science; intelligent robots

The philosophical issue in machine consciousness - Boltuc, Piotr (International Journal of Machine Consciousness, 2009)
Machines can be conscious, is the claim to be adopted here, upon examination of its different versions. We distinguish three kinds of consciousness: functional, phenomenal and hard consciousness (f-, p- and h-consciousness). Robots are functionally conscious already. There is also a clear project in AI on how to make computers phenomenally conscious, though criteria differ. Discussion about p-consciousness is clouded by the lack of clarity on its two versions: (1) First-person functional elements (here, p-consciousness), and (2) Non-functional (h-consciousness). I argue that: (1) There are sufficient reasons to adopt h-consciousness and move forward with discussion of its practical applications; this does not have anti-naturalistic implications. (2) A naturalistic account of h-consciousness should be expected, in principle; in neuroscience we are some way towards formulating such an account. (3) Detailed analysis of the notion of consciousness is needed to clearly distinguish p- and h-consciousness. This refers to the notion of subject that is not an object and complementarity of the subjective and objective perspectives.(4) If we can understand the exact mechanism that produces h-consciousness we should be able to engineer it. (5) H-consciousness is probably not a computational process (more like a liver-function). Machines can, in principle, be functionally, phenomenally and h-conscious; all those processes are naturalistic. This is the engineering thesis on machine consciousness formulated within non-reductive naturalism.
Keywords: Chalmers; Machine consciousness; atomic subject; awareness; h-consciousness; hard problem of consciousness; p-consciousness

The strength of weak artificial consciousness - Seth, Anil (International Journal of Machine Consciousness, 2009)
Machine (artificial) consciousness can be interpreted in both strong and weak forms, as an instantiation or as a simulation. Here, I argue in favor of weak artificial consciousness, proposing that synthetic models of neural mechanisms potentially underlying consciousness can shed new light on how these mechanisms give rise to the phenomena they do. The approach I advocate involves using synthetic models to develop "explanatory correlates" that can causally account for deep, structural properties of conscious experience. In contrast, the project of strong artificial consciousness — while not impossible in principle — has yet to be credibly illustrated, and is in any case less likely to deliver advances in our understanding of the biological basis of consciousness. This is because of the inherent circularity involved in using models both as instantiations and as cognitive prostheses for exposing general principles, and because treating models as instantiations can indefinitely postpone comparisons with empirical data.
Keywords: Weak artificial consciousness; artificial life; explanatory correlate; strong artificial consciousness

Beyond consciousness? - Taylor, John G. (International Journal of Machine Consciousness, 2009)
A discussion is given as to the possibility of creating machines which have more powerful consciousnesses than our own. The approach employs, in particular, a brain-based model of human consciousness. From that model a general discussion is developed of the need for a unique central control system in any machine to enable it to be efficient in decision-making. The resulting features of the machine’s consciousness, as the highest order controller, is seen to need to be similar to our own. We conclude that beyond consciousness very likely lies only similar consciousnesses.
Keywords: Attention; control; hierarchy; inner self; purpose of consciousness; unity of self

Artificial agency, consciousness, and the criteria for moral agency: what properties must an artificial agent have to be a moral agent? - Himma, Kenneth Einar (Ethics and Information Technology, 2009)
In this essay, I describe and explain the standard accounts of agency, natural agency, artificial agency, and moral agency, as well as articulate what are widely taken to be the criteria for moral agency, supporting the contention that this is the standard account with citations from such widely used and respected professional resources as the Stanford Encyclopedia of Philosophy, Routledge Encyclopedia of Philosophy, and the Internet Encyclopedia of Philosophy. I then flesh out the implications of some of these well-settled theories with respect to the prerequisites that an ICT must satisfy in order to count as a moral agent accountable for its behavior. I argue that each of the various elements of the necessary conditions for moral agency presupposes consciousness, i.e., the capacity for inner subjective experience like that of pain or, as Nagel puts it, the possession of an internal something-of-which-it is-is-to-be-like. I ultimately conclude that the issue of whether artificial moral agency is possible depends on the issue of whether it is possible for ICTs to be conscious.
Keywords: accountability; agency; artificial agents; consciousness; ethics; moral agency; natural agents

An Empirical Framework for Objective Testing for P-Consciousness in an Artificial Agent - Hales, Colin (The Open Artificial Intelligence Journal, 2009)
Two related and relatively obscure issues in science have eluded empirical tractability. Both can be directly traced to progress in artificial intelligence. The first is scientific proof of consciousness or otherwise in anything. The second is the role of consciousness in intelligent behaviour. This document approaches both issues by exploring the idea of using scientific behaviour self-referentially as a benchmark in an objective test for P-consciousness, which is the relevant critical aspect of consciousness. Scientific behaviour is unique in being both highly formalised and provably critically dependent on the P-consciousness of the primary senses. In the context of the primary senses P-consciousness is literally a formal identity with scientific observation. As such it is intrinsically afforded a status of critical dependency demonstrably no different to any other critical dependency in science, making scientific behaviour ideally suited to a self-referential scientific circumstance. The ‘provability’ derives from the delivery by science of objectively verifiable ‘laws of nature’. By exploiting the critical dependency, an empirical framework is constructed as a refined and specialised version of existing propositions for a ‘test for consciousness’. The specific role of P-consciousness is clarified: it is a human intracranial central nervous system construct that symbolically grounds the scientist in the distal external world, resulting in our ability to recognise, characterise and adapt to distal natural world novelty. It is hoped that in opening a discussion of a novel approach, the artificial intelligence community may eventually find a viable contender for its long overdue scientific basis.

A review of artificial intelligence - Brunette, E. S.; Flemmer, R. C.; Flemmer, C. L. (2009 4th International Conference on Autonomous Robots and Agents, 2009)
This paper reviews the field of artificial intelligence focusing on embodied artificial intelligence. It also considers models of artificial consciousness, agent-based artificial intelligence and the philosophical commentary on artificial intelligence. It concludes that there is almost no consensus nor formalism in the field and that the achievements of the field are meager.

MACHINE CONSCIOUSNESS: A MANIFESTO FOR ROBOTICS - Chella, Antonio; Manzotti, Riccardo (International Journal of Machine Consciousness, 2009)
Machine consciousness is not only a technological challenge, but a new way to approach scientific and theoretical issues which have not yet received a satisfactory solution from AI and robotics. We outline the foundations and the objectives of machine consciousness from the standpoint of building a conscious robot.

SYNTHETIC PHENOMENOLOGY - Chrisley, Ron (International Journal of Machine Consciousness, 2009)
The term "synthetic phenomenology" refers to: 1) any attempt to characterize the phenomenal states possessed, or modeled by, an artefact (such as a robot); or 2) any attempt to use an artefact to help specify phenomenal states (independently of whether such states are possessed by a naturally conscious being or an artefact). The notion of synthetic phenomenology is clarified, and distinguished from some related notions. It is argued that much work in machine consciousness would benefit from being more cognizant of the need for synthetic phenomenology of the first type, and of the possible forms it may take. It is then argued that synthetic phenomenology of the second type looks set to resolve some problems confronted by standard, non-synthetic attempts at characterizing phenomenal states. An example of the second form of synthetic phenomenology is given.

Brain and mind operational architectonics and man-made “machine” consciousness - Fingelkurts, Andrew A.; Fingelkurts, Alexander A.; Neves, Carlos F. H. (Cognitive Processing, 2009)
To build a true conscious robot requires that a robot’s “brain” be capable of supporting the phenomenal consciousness as human’s brain enjoys. Operational Architectonics framework through exploration of the temporal structure of information flow and inter-area interactions within the network of functional neuronal populations [by examining topographic sharp transition processes in the scalp electroencephalogram (EEG) on the millisecond scale] reveals and describes the EEG architecture which is analogous to the architecture of the phenomenal world. This suggests that the task of creating the “machine” consciousness would require a machine implementation that can support the kind of hierarchical architecture found in EEG.

Toward Structural Cognitology: Phenomenology of Consciousness from the Point of View of Artificial Intelligence - Finn, Victor K. (Russian Journal of Communication, 2009)
The development of cognitive sciences, whose interdisciplinary connections constitute a necessary condition of their usefulness, depends on the interaction between psychology, physiology, linguistics, as well as logic and artificial intelligence (AI); the latter serves as the proving ground for experimental testing of scientific means for imitating rationality and productive thinking. Thus, it is very interesting to consider the phenomenon of the asymmetry of brain activity from the point of view of AI constructions and its logical means.

A scheme for an embodied artificial intelligence - Flemmer, R. C. (2009 4th International Conference on Autonomous Robots and Agents, 2009)
A method is presented to construct an embodied artificial intelligence. The method grows out of a system for object recognition in artificial vision and relies upon such a capability. Examples from the biosphere are extensively discussed in coming to the method which has, as its central tenet, that all intelligence is fundamentally related to objects. All the aspects needed by an embodied intelligence are developed including consciousness, memory and volition.

EVOLUTIONARY PRESSURES FOR PERCEPTUAL STABILITY AND SELF AS GUIDES TO MACHINE CONSCIOUSNESS - Franklin, Stan; D’Mello, Sidney; Baars, Bernard J.; Ramamurthy, Uma (International Journal of Machine Consciousness, 2009)
The currently leading cognitive theory of consciousness, Global Workspace Theory postulates that the primary functions of consciousness include a global broadcast serving to recruit internal resources with which to deal with the current situation and to modulate several types of learning. In addition, conscious experiences present current conditions and problems to a "self" system, an executive interpreter that is identifiable with brain structures like the frontal lobes and precuneus. Be it human, animal or artificial, an autonomous agent is said to be functionally conscious if its control structure (mind) implements Global Workspace Theory and the LIDA Cognitive Cycle, which includes unconscious memory and control functions needed to integrate the conscious component of the system. We would therefore consider humans, many animals and even some virtual or robotic agents to be functionally conscious. Such entities may approach phenomenal consciousness, as found in human and other biological brains, as additional brain-like features are added. Here we argue that adding mechanisms to produce a stable, coherent perceptual field in a LIDA controlled mobile robot might provide a small but significant step toward phenomenal consciousness in machines. We also propose that implementing several of the various notions of self in such a LIDA controlled robot may well prove another step toward phenomenal consciousness in machines.

THE OPERATIVE MIND: A FUNCTIONAL, COMPUTATIONAL AND MODELING APPROACH TO MACHINE CONSCIOUSNESS - Hernández, Carlos; López, Ignacio; Sanz, Ricardo (International Journal of Machine Consciousness, 2009)
The functional capabilities that consciousness seems to provide to biological systems can supply valuable principles in the design of more autonomous and robust technical systems. These functional concepts keep a notable similarity to those underlying the notion of operating system in software engineering, which allows us to specialize the computer metaphor for the mind into that of the operating system metaphor for consciousness. In this article, departing from these ideas and a model-based theoretical framework for cognition, we present an architectural proposal for machine consciousness, called the Operative Mind. According to it, machine consciousness could be implemented as a set of services, in an operative system fashion, based on modeling of the own control architecture, that supervise the adequacy of the system architectural structure to the current objectives, triggering and managing adaptativity mechanisms.

Artificial Intelligence and Consciousness - Holland, O.; Gamez, D. (Encyclopedia of Consciousness, 2009)
Artificial intelligence (AI) and the research on consciousness have reciprocally influenced each other – theories about consciousness have inspired work on AI, and the results from AI have changed our interpretation of the mind. AI can be used to test theories of consciousness and research has been carried out on the development of machines with the behavior, cognitive characteristics and architecture associated with consciousness. Some people have argued against the possibility of machine consciousness, but none of these objections are conclusive and many theories openly embrace the possibility that phenomenal consciousness could be realized in artificial systems.

A LOGICAL MODEL OF CONSCIOUSNESS ON AN AUTONOMOUSLY ADAPTIVE SYSTEM - Kinouchi, Yasuo (International Journal of Machine Consciousness, 2009)
Consciousness is a tremendously complex phenomenon. We examined the configurations and functions of an autonomously adaptive system that can adapt to an environment without a teacher to understand this complex phenomenon in the easiest way possible, and proposed a modeling method of consciousness on the system. In modeling of consciousness, it is important to note the difference between phenomenal consciousness and functional consciousness. To clarify the difference, a model with two layers, a physical layer and a logical layer, is proposed. The functions of primitive consciousness on the autonomously adaptive system were clarified on the model. The physical layer is composed of an artificial neural node. All signals are processed in detail by the neural nodes. Contrarily, minimum information, necessary for the system to adapt itself, selected from the physical layer composes the logical layer. The operations in the logical layer are represented by interactions between only the selected information. Our daily conscious phenomenon is expressed on the logical layer.

Natural and Machine Learning, Intelligence and Consciousness - Kononenko, Igor (Philosophical Insights About Modern Science, 2009)

The ego tunnel: The science of the mind and the myth of the self - Metzinger, Thomas (The ego tunnel: The science of the mind and the myth of the self, 2009)
In this stunningly original exploration of human consciousness, philosopher and scientist Thomas Metzinger provides fascinating evidence that the "self" does not really exist. Highlighting a series of groundbreaking experiments in neuroscience, virtual reality, and robotics, and his own pioneering research into the phenomenon of the "out-of-body" experience, Metzinger reveals how our brain constructs our reality—our deepest sense of self is completely dependent on our brain functioning. In The Ego Tunnel, Metzinger examines recent evidence that people born without arms or legs can experience a sensation that they do in fact have limbs—and how we can actually feel a human touch in a rubber hand placed on a desk in front of us. Similarly, he reveals how the state of our experiential self changes when we become lucid while we're dreaming, and how our sense of self can even be transposed into a three-dimensional computer-generated image of our body in cyberspace simply by using virtual reality goggles, creating a conflict between the seeing self and the feeling self. He goes on to discuss the latest research on free will, machine consciousness, and the evolution of empathy. Highlighting these examples and more, Metzinger asserts that if our "self" is created by our brain mechanisms and it's possible to alter our subjective reality, then this creates not only a deeper understanding of consciousness, but a need for a new approach to ethics. Our sense of self, our spatial understanding, and the feeling of embodiment can be manipulated and even controlled. Using new kinds of medication, we can even enhance cognition and fine-tune emotional layers of self consciousness. But what, in an ethical sense, are valuable forms of self-experience in the first place—what is a good state of consciousness? Metzinger ultimately argues that we must be willing to engage with serious and pressing ethical questions as well as cultural consequences that will result from a new image of the "self" and the emerging neurotechnology of consciousness. In a time when the science of cognition is becoming as controversial as evolution, The Ego Tunnel provides a highly innovative take on the mystery of the mind. (PsycInfo Database Record (c) 2025 APA, all rights reserved)
Keywords: Brain; Consciousness States; Ego; Mind; Neurosciences

Artificial Intelligence and Personal Identity: - Pruss, Alexander R. (Faith and Philosophy, 2009)

RESILIENT ARCHITECTURES TO FACILITATE BOTH FUNCTIONAL CONSCIOUSNESS AND PHENOMENAL CONSCIOUSNESS IN MACHINES - Ramamurthy, Uma; Franklin, Stan (International Journal of Machine Consciousness, 2009)
Cognitive theories of consciousness should provide effective frameworks to implement machine consciousness. The Global Workspace Theory is a leading theory of consciousness which postulates that the primary function of consciousness is a global broadcast that facilitates recruitment of internal resources to deal with the current situation as well as modulate several types of learning. In this paper, we look at architectures for machine consciousness that have the Global Workspace Theory as their basis and discuss the requirements in such architectures to bring about both functional and phenomenal aspects of consciousness in machines.

Artificial consciousness: Hazardous questions (and answers) - Buttazzo, Giorgio (Artificial Intelligence in Medicine, 2008)
If human consciousness is the result of complex neural electro-chemical interactions occurring in the brain, the question of whether a machine can ever become self-aware could be a matter of time: the time necessary to fully understand the functional behavior of the brain structure, develop a mathematical model of it, and implement an artificial system capable of working according to such a model. This paper addresses several issues related to the possibility of developing a conscious artificial brain. A number of hazardous questions are posed to the reader, each addressing a specific technical or philosophical issue, which is discussed and developed in a form of a hazardous answer.
Keywords: Artificial beings; Artificial consciousness; Artificial neural networks; Conscious machines; Self-aware systems

Philosophical foundations of artificial consciousness - Chrisley, Ron (Artificial Intelligence in Medicine, 2008)
Consciousness is often thought to be that aspect of mind that is least amenable to being understood or replicated by artificial intelligence (AI). The first-personal, subjective, what-it-is-like-to-be-something nature of consciousness is thought to be untouchable by the computations, algorithms, processing and functions of AI method. Since AI is the most promising avenue toward artificial consciousness (AC), the conclusion many draw is that AC is even more doomed than AI supposedly is. The objective of this paper is to evaluate the soundness of this inference. Methods The results are achieved by means of conceptual analysis and argumentation. Results and conclusions It is shown that pessimism concerning the theoretical possibility of artificial consciousness is unfounded, based as it is on misunderstandings of AI, and a lack of awareness of the possible roles AI might play in accounting for or reproducing consciousness. This is done by making some foundational distinctions relevant to AC, and using them to show that some common reasons given for AC scepticism do not touch some of the (usually neglected) possibilities for AC, such as prosthetic, discriminative, practically necessary, and lagom (necessary-but-not-sufficient) AC. Along the way three strands of the author's work in AC – interactive empiricism, synthetic phenomenology, and ontologically conservative heterophenomenology – are used to illustrate and motivate the distinctions and the defences of AC they make possible.
Keywords: Artificial consciousness; Heterophenomenology; Interactive empiricism; Machine consciousness; Prosthetic artificial intelligence; Synthetic phenomenology

Artificial consciousness: a discipline between technological and theoretical obstacles - Manzotti, Riccardo; Tagliasco, Vincenzo (Artificial Intelligence in Medicine, 2008)
Artificial consciousness is still far from being an established discipline. We will try to outline some theoretical assumption that could help in dealing with phenomenal consciousness. What are the technological and theoretical obstacles that face the enthusiast scholars of artificial consciousness? After presenting an outline of the state of artificial consciousness, we will focus on the relevance of phenomenal consciousness. Artificial consciousness needs to tackle the issue of phenomenal consciousness in a physical world. Up to now, the only models that give some hope of succeeding are the various kinds of externalism.
Keywords: Artificial Intelligence; Consciousness; Models, Theoretical

Assessing Artificial Consciousness: A Collective Review Article - Chrisley, Ron; Aleksander, Igor; Bringsjord, S.; Clowes, Robert; Parthemore, Joel; Stuart, Susan; Torrance, Steve; Ziemke, Tom (Journal of Consciousness Studies, 2008)
While the recent special issue of JCS on machine consciousness (Volume 14, Issue 7) was in preparation, a collection of papers on the same topic, entitled Artificial Consciousness and edited by Antonio Chella and Riccardo Manzotti, was published. The editors of the JCS special issue, Ron Chrisley, Robert Clowes and Steve Torrance, thought it would be a timely and productive move to have authors of papers in their collection review the papers in the Chella and Manzotti book, and include these reviews in the special issue of the journal. Eight of the JCS authors (plus Uziel Awret) volunteered to review one or more of the fifteen papers in Artificial Consciousness; these individual reviews were then collected together with a minimal amount of editing to produce a seamless chapter-by-chapter review of the entire book. Because the number and length of contributions to the JCS issue was greater than expected, the collective review of Artificial Consciousness had to be omitted, but here at last it is. Each paper's review is written by a single author, so any comments made may not reflect the opinions of all nine of the joint authors!

Applying machine consciousness models in autonomous situated agents - Arrabales Moreno, Raúl; Sanchis De Miguel, Araceli (Pattern Recognition Letters, 2008)
This paper briefly describes the most relevant current approaches to the implementation of scientific models of consciousness. Main aspects of scientific theories of consciousness are characterized in sight of their possible mapping into artificial implementations. These implementations are analyzed both theoretically and functionally. Also, a novel pragmatic functional approach to machine consciousness is proposed and discussed. A set of axioms for the presence of consciousness in agents is applied to evaluate and compare the various models.

A cognitive architecture for robot self-consciousness - Chella, Antonio; Frixione, Marcello; Gaglio, Salvatore (Artificial Intelligence in Medicine, 2008)
One of the major topics towards robot consciousness is to give a robot the capabilities of self-consciousness. We propose that robot self-consciousness is based on higher order perception of the robot, in the sense that first-order robot perception is the immediate perception of the outer world, while higher order perception is the perception of the inner world of the robot.

Whole brain emulation: a roadmap - Sandberg, A.; Bostrom, N. (Future of Humanity Institute, 2008)

Robot consciousness and representation of facial expressions - Takeno, J.; Mori, K.; Naito, Y. (2008 3rd International Conference on Sensing Technology. ICST 2008, 2008)
The humanoid robot we developed is capable of changing its facial expressions according to simple artificial consciousness and stream of consciousness. We think that consciousness consists basically of ‘language and its associative stream’ and ‘representation of feelings related to the language.’ The robot named Kansei, a Japanese term referring to emotion, achieves linguistic association similar to a stream of consciousness and represents its feelings according to the associations through artificial consciousness. The robot is equipped with an artificial cranium made of aluminium which contains 19 servomotors inside it. For the surface of the face, we use polyurethane, a relatively soft material which creates a shape that is closely mimics a human face. Facial expressions are formed on the polyurethane by pulling it into shape via metal wires attached to the 19 internal servomotors. Besides the six basic facial expressions such as happiness and anger, the robot can also make complex expressions that include both happiness and fear.

Ethics and consciousness in artificial agents - Torrance, Steve (AI & SOCIETY, 2008)
In what ways should we include future humanoid robots, and other kinds of artificial agents, in our moral universe? We consider the Organic view, which maintains that artificial humanoid agents, based on current computational technologies, could not count as full-blooded moral agents, nor as appropriate targets of intrinsic moral concern. On this view, artificial humanoids lack certain key properties of biological organisms, which preclude them from having full moral status. Computationally controlled systems, however advanced in their cognitive or informational capacities, are, it is proposed, unlikely to possess sentience and hence will fail to be able to exercise the kind of empathic rationality that is a prerequisite for being a moral agent. The organic view also argues that sentience and teleology require biologically based forms of self-organization and autonomous self-maintenance. The organic view may not be correct, but at least it needs to be taken seriously in the future development of the field of Machine Ethics.

The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind - Minsky, Marvin (Simon and Schuster, 2007)
In this mind-expanding book, scientific pioneer Marvin Minsky continues his groundbreaking research, offering a fascinating new model for how our minds work. He argues persuasively that emotions, intuitions, and feelings are not distinct things, but different ways of thinking. By examining these different forms of mind activity, Minsky says, we can explain why our thought sometimes takes the form of carefully reasoned analysis and at other times turns to emotion. He shows how our minds progress from simple, instinctive kinds of thought to more complex forms, such as consciousness or self-awareness. And he argues that because we tend to see our thinking as fragmented, we fail to appreciate what powerful thinkers we really are. Indeed, says Minsky, if thinking can be understood as the step-by-step process that it is, then we can build machines -- artificial intelligences -- that not only can assist with our thinking by thinking as we do but have the potential to be as conscious as we are. Eloquently written, The Emotion Machine is an intriguing look into a future where more powerful artificial intelligences await.
Keywords: Psychology / Cognitive Neuroscience & Cognitive Neuropsychology; Psychology / Cognitive Psychology & Cognition; Psychology / Emotions; Science / General; Science / Life Sciences / Neuroscience

The Impossibility of Artificial Imagination: A Question of Genuine Consciousness - Trinh, Huy (Elements, 2007)
Is it possible to create genuine consciousness, artificial intelligence? This paper will examine this question through the philosophical understanding of imagination. Imagination is the creative faculty that not only separates man from beast but also allows man to recognize himself, and it helps him to see beyond his immediate being. Without imagination, man is blind to future possibility and unable to conceive of future events. Imagination produces man's mental cognition that makes him a rational and creative being. The two modern methods of A.I. programming are incapable of imbuing their algorithm with imagination. Without imagination, A.I. not only lacks genuine creativity, but it also risks never understanding self-autonomy and therefore could never be a free and independent entity.

Robot Brains: Circuits and Systems for Conscious Machines - Haikonen, Pentti O. (John Wiley & Sons, 2007)
Haikonen envisions autonomous robots that perceive and understand the world directly, acting in it in a natural human-like way without the need of programs and numerical representation of information. By developing higher-level cognitive functions through the power of artificial associative neuron architectures, the author approaches the issues of machine consciousness. Robot Brains expertly outlines a complete system approach to cognitive machines, offering practical design guidelines for the creation of non-numeric autonomous creative machines. It details topics such as component parts and realization principles, so that different pieces may be implemented in hardware or software. Real-world examples for designers and researchers are provided, including circuit and systems examples that few books on this topic give. In novel technical and practical detail, this book also considers: the limitations and remedies of traditional neural associators in creating true machine cognition; basic circuit assemblies cognitive neural architectures; how motors can be interfaced with the associative neural system in order for fluent motion to be achieved without numeric computations; memorization, imagination, planning and reasoning in the machine; the concept of machine emotions for motivation and value systems; an approach towards the use and understanding of natural language in robots. The methods presented in this book have important implications for computer vision, signal processing, speech recognition and other information technology fields. Systematic and thoroughly logical, it will appeal to practising engineers involved in the development and design of robots and cognitive machines, also researchers in Artificial Intelligence. Postgraduate students in computational neuroscience and robotics, and neuromorphic engineers will find it an exciting source of information.
Keywords: Technology & Engineering / Electrical; Technology & Engineering / Electronics / General; Technology & Engineering / Robotics

Artificial intelligence and consciousness - McDermott, Drew (The Cambridge Handbook of Consciousness, 2007)
Consciousness is only marginally relevant to artificial intelligence (AI), because to most researchers in the field other problems seem more pressing. The purpose of consciousness, from an evolutionary perspective, is often held to have something to do with the allocation and organization of scarce cognitive resources. This chapter describes Daniel Dennett's idea of the intentional stance, in which an observer explains a system's behavior by invoking such intentional categories as beliefs and goals. The computationalist theory of phenomenal consciousness ends up looking like a spoil-sport's explanation of a magic trick. The chapter focuses on critiques that are specifically directed at computational models of consciousness, as opposed to general critiques of materialist explanation. The contribution of artificial intelligence to consciousness studies has been slender so far, because almost everyone in the field would rather work on better defined, less controversial problems.

Two Conceptions of Machine Phenomenality - Torrance, Steve (Journal of Consciousness Studies, 2007)
Current approaches to machine consciousness (MC) tend to offer a range of characteristic responses to critics of the enterprise. Many of these responses seem to marginalize phenomenal consciousness, by presupposing a 'thin' conception of phenomenality. This conception is, we will argue, largely shared by anti- computationalist critics of MC. On the thin conception, physiological or neural or functional or organizational features are secondary accompaniments to consciousness rather than primary components of consciousness itself. We outline an alternative, 'thick' conception of phenomenality. This shows some signposts in the direction of a more adequate approach to MC.

Modeling Consciousness for Autonomous Robot Exploration - Arrabales Moreno, Raúl; Ledezma Espino, Agapito; Sanchis De Miguel, Araceli (Bio-inspired Modeling of Cognitive Tasks, 2007)
This work aims to describe the application of a novel machine consciousness model to a particular problem of unknown environment exploration. This relatively simple problem is analyzed from the point of view of the possible benefits that cognitive capabilities like attention, environment awareness and emotional learning can offer. The model we have developed integrates these concepts into a situated agent control framework, whose first version is being tested in an advanced robotics simulator. The implementation of the relationships and synergies between the different cognitive functionalities of consciousness in the domain of autonomous robotics is also discussed.

Essential Issues of Conscious Machines - Haikonen, Pentti O. A. (Journal of Consciousness Studies, 2007)
The development of conscious machines faces a number of difficult issues such as the apparent immateriality of mind, qualia and self-awareness. Also consciousness-related cognitive processes such as perception, imagination, motivation and inner speech are a technical challenge. It is foreseen that the development of machine consciousness would call for a system approach; the developer of conscious machines should consider complete systems that integrate the cognitive processes seamlessly and process information in a transparent way with representational and non-representational information-processing modes. An overview of the main issues is given and some possible solutions are outlined.

A Strongly Embodied Approach to Machine Consciousness - Holland, Owen (Journal of Consciousness Studies, 2007)
Over sixty years ago, Kenneth Craik noted that, if an organism (or an artificial agent) carried 'a small-scale model of external reality and of its own possible actions within its head', it could use the model to behave intelligently. This paper argues that the possible actions might best be represented by interactions between a model of reality and a model of the agent, and that, in such an arrangement, the internal model of the agent might be a transparent model of the sort recently discussed by Metzinger, and so might offer a useful analogue of a conscious entity. The CRONOS project has built a robot functionally similar to a human that has been provided with an internal model of itself and of the world to be used in the way suggested by Craik; when the system is completed, it will be possible to study its operation from the perspective not only of artificial intelligence, but also of machine consciousness.

The Role of the Self Process in Embodied Machine Consciousness - Holland, Owen; Knight, Rob; Newcombe, Richard (Artificial Consciousness, 2007)

Computational Aspects of Cognition and Consciousness in Intelligent Devices - Kozma, Robert; Aghazarian, Hrand; Huntsberger, Terry; Tunstel, Eddie; Freeman, Walter J. (IEEE Computational Intelligence Magazine, 2007)
We review computational intelligence methods of sensory perception and cognitive functions in animals, humans, and artificial devices. Top-down symbolic methods and bottom-up sub-symbolic approaches are described. In recent years, computational intelligence, cognitive science and neuroscience have achieved a level of maturity that allows integration of top-down and bottom-up approaches in modeling the brain. Continuous adaptation and learning is a key component of computationally intelligent devices, which is achieved using dynamic models of cognition and consciousness. Human cognition performs a granulation of the seemingly homogeneous temporal sequences of perceptual experiences into meaningful and comprehensible chunks of concepts and complex behavioral schemas. They are accessed during action selection and conscious decision making as part of the intentional cognitive cycle. Implementations in computational and robotic environments are demonstrated.

Sense as a 'Translation' of Mental Contents - Lavazza, Andrea (Artificial Consciousness, 2007)

From Artificial Intelligence to Artificial Consciousness - Manzotti, Riccardo (Artificial Consciousness, 2007)
Thinking and being conscious are two fundamental aspects of the subject. Although both are challenging, often conscious experience has been considered more elusive (Chalmers 1996). However, in recent years, several researchers addressed the hypothesis of designing and implementing models for artificial conscious-ness—on one hand there is hope of being able to design a model for consciousness, on the other hand the actual implementations of such models could be helpful for understanding consciousness. The traditional field of Artificial Intelligence is now flanked by the seminal field of artificial or machine consciousness. In this chapter I will analyse the current state of the art of models of consciousness and then I will outline an externalist theory of the conscious mind that is compatible with the design and implementation of an artificial conscious being. As I argue in the following, this task can be profitably approached once we abandon the dualist framework of traditional Cartesian substance metaphysics and adopt a process-metaphysical stance. Thus, I sketch an alternative externalist process-based ontological framework. From within this framework, I venture to suggest a series of constraints for a conscious oriented architecture.

Machine Consciousness: Cognitive and Kinaesthetic Imagination - Stuart, Susan A. J. (Journal of Consciousness Studies, 2007)
Machine consciousness exists already in organic systems and it is only a matter of time -- and some agreement -- before it will be realised in reverse-engineered organic systems and forward- engineered inorganic systems. The agreement must be over the preconditions that must first be met if the enterprise is to be successful, and it is these preconditions, for instance, being a socially-embedded, structurally-coupled and dynamic, goal-directed entity that organises its perceptual input and enacts its world through the application of both a cognitive and kinaesthetic imagination, that I shall concentrate on presenting in this paper. It will become clear that these preconditions will present engineers with a tall order, but not, I will argue, an impossible one. After all, we might agree with Freeman and Núñez's claim that the machine metaphor has restricted the expectations of the cognitive sciences (Freeman & Núñez, 1999); but it is a double-edged sword, since our limited expectations about machines also narrow the potential of our cognitive science.

Through Machine Attention to Machine Consciousness - Taylor, John G. (Artificial Consciousness, 2007)

The emotional robot: Cognitive computing and the quest for artificial intelligence - Thilmany, Jean (EMBO reports, 2007)

What's Life Got to Do with It? - Ziemke, Tom (Artificial Consciousness, 2007)

Artificial consciousness, artificial emotions, and autonomous robots - Cardon, Alain (Cognitive Processing, 2006)
Nowadays for robots, the notion of behavior is reduced to a simple factual concept at the level of the movements. On another hand, consciousness is a very cultural concept, founding the main property of human beings, according to themselves. We propose to develop a computable transposition of the consciousness concepts into artificial brains, able to express emotions and consciousness facts. The production of such artificial brains allows the intentional and really adaptive behavior for the autonomous robots. Such a system managing the robot’s behavior will be made of two parts: the first one computes and generates, in a constructivist manner, a representation for the robot moving in its environment, and using symbols and concepts. The other part achieves the representation of the previous one using morphologies in a dynamic geometrical way. The robot’s body will be seen for itself as the morphologic apprehension of its material substrata. The model goes strictly by the notion of massive multi-agent’s organizations with a morphologic control.
Keywords: Artificial Intelligence; Artificial consciousness; Artificial emotions; Embodiment; Intentionality; Morphology; Multi-agent systems; Organizational memory; Representation

Pitfalls in Biological Computing: Canonical and Idiosyncratic Dysfunction of Conscious Machines - Wallace, Rodrick (Mind and Matter, 2006)
The central paradigm of artificial intelligence is rapidly shifting toward biological models for both robotic devices and systems performing such critical tasks as network management, vehicle navigation, and process control. Here we use a recent mathematical analysis of the necessary conditions for consciousness in humans to explore likely failure modes inherent to a broad class of biologically inspired computing machines. Analogs to developmental psychopathology, in which regulatory mechanisms for consciousness fail progressively and subtly understress, and toinattentional blindness, where a narrow 'syntactic band pass' de?ned by the rate distortion manifold of conscious attention results in pathological ?xation, seem inevitable. Similar problems are likely to confront other possible architectures, although their mathematical description may be far less straightforward. Computing devices constructed on biological paradigms will inevitably lack the elaborate, but poorly understood, system of control mechanisms which has evolved over the last few hundred million years to stabilize consciousness in higher animals. This will make such machines prone to insidious degradation, and, ultimately, catastrophic failure.

The relevance of intent to human-android strategic interaction and artificial consciousness - Cowley, M. (ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication, 2006)
A classic problem for artificial intelligence is to build a machine that imitates human behavior well enough to convince those who are interacting with it that it is another human being [1]. One approach to this problem focuses on building machines that imitate internal psychological facets of human interaction, such as artificially intelligent agents that play grandmaster chess [2]. Another approach focuses on building machines that imitate external psychological facets by building androids [3]. The disparity between these approaches reflects a problem with both: Artificial intelligence abstracts mentality from embodiment, while android science abstracts embodiment from mentality. This problem needs to be solved, if a sentient artificial entity that is indistinguishable from a human being, is to be constructed. One solution is to examine a fundamental human ability and context in which both the construction of internal cognitive models and an appropriate external social response are essential. This paper considers how reasoning with intent in the context of human vs. android strategic interaction may offer a psychological benchmark with which to evaluate the human-likeness of android strategic responses. Understanding how people reason with intent may offer a theoretical context in which to bridge the gap between the construction of sentient internal and external artificial agents.

How “Consciousness” Allows a Cognitive Tutoring Agent Make Good Diagnosis During Astronauts’ Training - Dubois, Daniel; Nkambou, Roger; Hohmeyer, Patrick (Intelligent Tutoring Systems, 2006)
Striving in the real world is more and more what artificial agents are required to do, and it is not a simple task. Interacting with humans in general, and with students in specific, requires an awful lot of subtlety if one is to be perceived as a great tutor and a pleasant fellow. Similarly, the more various types of information an artificial agent senses, the more apt it may be. But then comes the need to process all this stuff, and that can overwhelm even the most powerful computer. «Consciousness» mechanisms can help and sustain an apt tutor, allowing it to consider various sources of information in diagnosing and guiding learners. We show in the present paper how they effectively support theses processes in the specific context of astronauts training on the manipulation of the Space Station Robotic Manipulation System, Canadarm2.

A model of agent consciousness and its implementation - Moura, Ivan (Neurocomputing, 2006)
The study of several theories and models of consciousness, among them the functional and cognitive model exhibited in Baars’ ‘Global Workspace’ theory, led us to identify computational correlates of consciousness and discuss their possible representations within a model of intelligent agent. We first review a particular agent implementation given by an abstract machine, and then identify the extensions required in order to accommodate the main attributes of consciousness. This amounts to form unconscious processor coalitions that result in the creation of contexts. These extensions can be formulated within a reified virtual machine encompassing a representation of the original machine as well as an additional introspective component.

A cognitive architecture that combines internal simulation with a global workspace - Shanahan, Murray (Consciousness and Cognition, 2006)
This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with the environment, is mediated by affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot.

Beware the Passionate Robot - Arbib, Michael A. (Who Needs Emotions?: The brain meets the robot, 2005)
This chapter discusses the observation that human emotions sometimes have unfortunate effects, which raises the concern that robot emotions might not always be optimal. It analyzes brain mechanisms for vision and language to ground an evolutionary account relating motivational systems to emotions and the cortical systems which elaborate them. It also attempts to determine how to address the issue of characterizing emotions in such a way that a robot can be considered to have emotions, even though they are not emphatically linked to human emotions.

Is Consciousness Only a Property of Individual Cells? - Edwards, Jonathan C.W. (Journal of Consciousness Studies, 2005)
We perceive colour, shape, sound and touch 'bound together' in a single experience. The following arguments about this binding phenomenon are raised: (1) The individual signals passing from neurone to neurone are not bound together, whether as elements of information or physically. (2) Within a single cell, binding in terms of bringing together of information is potentially feasible. A physical substrate may also be available. (3) It is therefore proposed that a bound conscious experience must be a property of an individual cell, not of a group of cells. Since it is unlikely that one specific neurone is conscious, it is suggested that every neurone has a version of our consciousness, or at least some form of sentience. However absurd this may seem it appears to be consistent with the available evidence; arguably the only explanation that is. It probably does not alter the way we should expect to experience the world, but may help to explain the ways we seem to differ from digital computers and some of the paradoxes seen in mental illness. It predicts non-digital features of intracellular computation, for which there is already evidence, and which should be open to further experimental exploration. The arguments given may well prove flawed or the conclusion biologically or physically untenable, but the idea is raised for discussion not least because a formal demonstration that it is invalid may help to identify more fruitful avenues.

Visions of Mind: Architectures for Cognition and Affect - Davis, Darryl N. (IGI Global, 2005)
“What is mind?” “Can we build synthetic or artificial minds?” Think these questions are only reserved for Science Fiction? Well, not anymore. This collection presents a diverse overview of where the development of artificial minds is as the twenty first century begins. Examined from nearly all viewpoints, Visions of Mind includes perspectives from philosophy, psychology, cognitive science, social studies and artificial intelligence. This collection comes largely as a result of many conferences and symposiums conducted by many of the leading minds on this topic. At the core is Professor Aaron Sloman's symposium from the spring 2000 UK Society for Artificial Intelligence conference. Authors from that symposium, as well as others from around the world have updated their perspectives and contributed to this powerful book. The result is a multi-disciplinary approach to the long term problem of designing a human-like mind, whether for scientific, social, or engineering purposes. The topics addressed within this text are valuable to both artificial intelligence and cognitive science, and also to the academic disciplines that they draw on and feed. Among those disciplines are philosophy, computer science, and psychology.

Brain-Inspired Conscious Computing Architecture - Duch, Wlodzislaw (Journal of Mind and Behavior, 2005)
What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such systems, guided and limited by associative memory, is similar to the stream of consciousness. A specific architecture of an artificial system, termed articon, is introduced that by its very design has to claim being conscious. Non-verbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the flow of inner states of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills – when conscious information processing is replaced by subconscious – is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute articon’s claims that it is conscious. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human.

Evolutionary pressures and a stable world for animals and robots: A commentary on Merker - Franklin, Stan (Consciousness and Cognition, 2005)
In his article on The Liabilities of Mobility, Merker (this issue) asserts that “Consciousness presents us with a stable arena for our actions—the world …” and argues for this property as providing evolutionary pressure for the evolution of consciousness. In this commentary, I will explore the implications of Merker’s ideas for consciousness in artificial agents as well as animals, and also meet some possible objections to his evolutionary pressure claim.

Expression of Emotion in Robots Using a Flow ofArtificial Consciousness - Ogiso, A.; Kurokawa, S.; Yamanaka, M.; Imai, Y.; Takeno, J. (2005 International Symposium on Computational Intelligence in Robotics and Automation, 2005)
This paper discusses the development of a robot head that creates a facial expression according to emotion resulting from a flow of consciousness. The authors focused attention on the human consciousness and proposed a system using a unique artificial consciousness according to the relationship between emotion and the resulting human facial expressions. The artificial consciousness is used to imitate the human consciousness and generate emotion in the robot using data from the Internet. The authors have also developed a robot system that is similar in structure to that of the human anatomy in order to achieve smooth communication with people. By combining these two systems, the authors were able to realize the expression of emotion according to a flow of consciousness using a humanoid robot.

On the evolution of artificial consciousness. Re-inventing the wheel, Re: Inventing the wheel - Jones, Stephen (Technoetic Arts, 2004)
In this article I suggest how we might conceptualize some kind of artificial consciousness as an ultimate development of Artificial Life. This entity will be embodied in some sort of constructed (biological or non-biological) body. The contention is that consciousness within self-organized entities is not only possible but inevitable. The basic sensory and interactive processes by which an organism operates within an environment are such as to be the basic processes that are necessary for consciousness. I then look at likely criteria for consciousness, and point to an architecture of the cognitive which maps onto the physiological layer, the brain. While evolutionary algorithms and neural nets will be at the heart of the production of artificial intelligences there is a particular architectural organization that may be necessary in the production of conscious artefacts. This involves the operations of multiple layers of feedback loops in the anatomy of the brain, in the social construction of the contents of consciousness and in particular in the self-regulation necessary for the continued operation of metabolically organized systems. Finally I make some comments on the ethics of such a procedure.

Machine Consciousness: Plausible Idea or Semantic Distortion? - Adams, William A. (Journal of Consciousness Studies, 2004)
The author found the "Journal of Consciousness Studies," (JCS) issue on Machine Consciousness, (2003), frustrating and alienating. It is argued that there seems to be a consensus building that consciousness is accessible to scientific scrutiny, so much so that it is already understood well enough to be modeled and even synthesized. It could be instead that the vocabulary of consciousness is being subtly redefined to be amenable to scientific investigation and explicit modeling. Such semantic revisionism is confusing and often misleading. Whatever else consciousness is, it is at least a certain quality of life apparent from personal reflection. Introspection is, after all, the only way we know that consciousness even exists. Scientific and technical redefinitions that fail to account for its phenomenal quality are at best incomplete. In the author's view, all but one of the ten articles in the JCS volume on Machine Consciousness commit various degrees of Protean distortion. In this collection of articles, common sense terms describing consciousness were consistently distorted into special uses that strip them of their meaning. The author has tried to point out in criticism of the JCS articles, explicit principles that are missing in the account of machine consciousness, leaving the various inferences about consciousness open to charges of being distorted and illegitimate. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
Keywords: Consciousness States

The Future of Embodied Artificial Intelligence: Machine Consciousness? - Holland, Owen (Embodied Artificial Intelligence, 2004)
The idea that internal models of the world might be useful has generally been rejected by embodied AI for the same reasons that led to its rejection by behaviour based robotics. This paper re-examines the issue from historical, biological, and functional perspectives; the view that emerges indicates that internal models are essential for achieving cognition, that their use is widespread in biological systems, and that there are several good but neglected examples of their use within embodied AI. Consideration of the example of a hypothetical autonomous embodied agent that has to execute a complex mission in a dynamic, partially unknown, and hostile environment leads to the conclusion that the necessary cognitive architecture is likely to contain separate but interacting models of the body and of the world. This arrangement is shown to have intriguing parallels with new findings on the infrastructure of consciousness, leading to the speculation that the reintroduction of internal models into embodied AI may lead not only to improved machine cognition but also, in the long run, to machine consciousness.

Can a Machine Be Conscious? How? - Harnad, Stevan (Journal of Consciousness Studies, 2003)
Asking whether a machine can be conscious is rather like asking whether one has stopped beating one's wife: The question is so heavy with assumptions that either answer would be incriminating! The answer, of course, is: It depends entirely on what you mean by 'machine'! If you mean the current generation of man-made devices (toasters, ovens, cars, computers, today's robots), the answer is: almost certainly not.

Robots With Internal Models A Route to Machine Consciousness? - Holland, Owen; Goodman, R. (Journal of Consciousness Studies, 2003)
We are engineers, and our view of consciousness is shaped by an engineering ambition: we would like to build a conscious machine. We begin by acknowledging that we may be a little disadvantaged, in that consciousness studies do not form part of the engineering curriculum, and so we may be starting from a position of considerable ignorance as regards the study of consciousness itself. In practice, however, this may not set us back very far; almost a decade ago, Crick wrote: 'Everyone has a rough idea of what is meant by consciousness. It is better to avoid a precise definition of consciousness because of the dangers of premature definition. Until the problem is understood much better, any attempt at a formal definition is likely to be either misleading or overly restrictive, or both' (Crick, 1994). This seems to be as true now as it was then, although the identification of different aspects of consciousness (P-consciousness, A-consciousness, self consciousness, and monitoring consciousness) by Block (1995) has certainly brought a degree of clarification. On the other hand, there is little doubt that consciousness does seem to be something to do with the operation of a sophisticated control system (the human brain), and we can claim more familiarity with control systems than can most philosophers, so perhaps we can make up some ground there.

Ida: A Conscious Artifact? - Franklin, Stan (Journal of Consciousness Studies, 2003)
After discussing various types of consciousness, several approaches to machine consciousness, software agent, and global workspace theory, we describe a software agent, IDA, that is “conscious” in the sense of implementing that theory of consciousness. IDA perceives, remembers, deliberates, negotiates, and selects actions, sometimes “consciously.” She uses a variety of mechanisms, each of which is briefly described. It’s tempting to think of her as a conscious artifact. Is such a view in any way justified? The remainder of the paper considers this question.

The Cognitive Approach to Conscious Machines - Haikonen, Pentti O. (Imprint Academic, 2003)
Could a machine have an immaterial mind? The author argues that true conscious machines can be built, but rejects artificial intelligence and classical neural networks in favour of the emulation of the cognitive processes of the brain--the flow of inner speech, inner imagery and emotions. This results in a non-numeric meaning-processing machine with distributed information representation and system reactions. It is argued that this machine would be conscious; it would be aware of its own existence and its mental content and perceive this as immaterial. Novel views on consciousness and the mind-body problem are presented. This book is a must for anyone interested in consciousness research and the latest ideas in the forthcoming technology of mind.
Keywords: Computers / Artificial Intelligence / General; Computers / Cybernetics; Philosophy / Mind & Body; Psychology / Cognitive Psychology & Cognition; Science / Cognitive Science

Machine Consciousness - Holland, Owen (Imprint Academic, 2003)

Acquisition of meanings of words such as "what is this" by a virtual robot: toward constructiing of artificial consciousness - Lwama, K. (International Conference on Natural Language Processing and Knowledge Engineering, 2003. 2003, 2003)
We describe a virtual robot that acquires meanings of words, and discuss that the robot shows an introspective conscious behavior. We first argue what outputs of the robot demonstrate that it has learned meanings of words such as "what is this". Then we explain functions of the robot that enable the robot to make outputs as if it has learned meanings of questions. The functions include 1) forming of linked lists (associations) among observed features, robotic actions, and words, 2) generalizing the associations to form generalized associations, and 3) applying an association and a generalized association to a new situation by making the generalized association match words, observed features, and actions in die new situation.

On the epigenesis of meaning in robots and organisms: Could a humanoid robot develop a human(oid) Umwelt? - Ziemke, Tom (Sign Systems Studies, 2002)
This paper discusses recent research on humanoid robots and thought experiments addressing the question to what degree such robots could be expected to develop human-like cognition, if rather than being preprogrammed they were made to learn from the interaction with their physical and social environment like human infants. A question of particular interest, from both a semiotic and a cognitive scientific perspective, is whether or not such robots could develop an experiential Umwelt, i.e. could the sign processes they are involved in become intrinsically meaningful to themselves? Arguments for and against the possibility of phenomenal artificial minds of different forms are discussed, and it is concluded that humanoid robotics still has to be considered “weak” rather than “strong AI”, i.e. it deals with models of mind rather than actual minds.

Dancing with Pixies: Strong Artificial Intelligence and Panpsychism - Bishop, Mark (Views into the Chinese Room: New Essays on Searle and Artificial Intelligence, 2002)
In 1994 John Searle stated (Searle 1994: 11-12) that the Chinese Room Argument (CRA) is an attempt to prove the truth of the premise: led him to the conclusion that ‘programs are not minds’ and hence that computationalism, the idea that the essence of thinking lies in computational processes and that such processes thereby underlie and explain conscious thinking, is false. The argument presented in this chapter is not a direct attack or defence of the CRA, but relates to the premise at its heart, that syntax is not sufficient for semantics, via the closely associated propositions that semantics is not intrinsic to syntax and that syntax is not intrinsic to physics.1 However, in contrast to the CRA’s critique of the link between syntax and semantics, this chapter will explore the associated link between syntax and physics.

Evolving Robot Consciousness: The Easy Problems and the Rest - Harvey, Inman (Consciousness Evolving, 2002)

What is the self of a robot?: On a consciousness architecture for a mobile robot as a model of human consciousness - Kitamura, Tadashi (Advances in Consciousness Research, 2002)

Lessons Learned from MAVRIC’s Brain: An Anticipatory Artificial Agent and Proto-consciousness - Mobus, George (COMPUTING ANTICIPATORY SYSTEMS: CASYS 2001 - Fifth International Conference, 2002)
MAVRIC II is a mobile, autonomous robot whose brain is comprised almost entirely of artificial adaptrode‐based neurons. These neurons were previously shown to encode anticipatory actions. The architecture of this brain is based on the Extended Braitenberg Architecture (EBA). We are still in the process of collecting hard data on the behavioral traits of MAVRIC in the generalized foraging search task. But even now sufficient qualitative aspects of MAVRIC’s behavior have been garnered from foraging experiments to lend strong support to the theory that MAVRIC is a highly adaptive, life‐like agent. The development of the current MAVRIC brain has led to some important insights into the nature of intelligent control. In this paper we elucidate some of these principles in the form of lessons learned, and project the potential for future developments.

When Computers Say It with Feeling: Communication and Synthetic Emotions in Kubrick's 2001: A Space Odyssey - Nofz, Michael P.; Vendy, Phil (Journal of Communication Inquiry, 2002)
The late Stanley Kubrick's film 2001: A Space Odyssey portrayed a computer, HAL 9000, that appeared to be a conscious entity, especially given that it seemed capable of some forms of emotional expression. This article examines the film's portrayal of communication between HAL 9000 and the astronauts. Recent developments in the field of artificial intelligence (AI) (and synthetic emotions in particular) as well as social science research on human emotions are reviewed. Interpreting select scenes from 2001 in light of these findings, the authors argue that computer-generated emotions may be so realistic that they suggest inner feelings and consciousness. Refinements in AI technology are now making such realism possible. The need for a less anthropomorphic approach with computers that appear to have feelings is stressed.

Artificial consciousness: Utopia or real possibility? - Buttazzo, G. (Computer, 2001)
Since the beginnings of computer technology, researchers have speculated about the possibility of building smart machines that could compete with human intelligence. Given the current pace of advances in artificial intelligence and neural computing, such an evolution seems to be a more concrete possibility. Many people now believe that artificial consciousness is possible and that, in the future, it will emerge in complex computing machines. However, a discussion of artificial consciousness gives rise to several philosophical issues: can computers think or do they just calculate? Is consciousness a human prerogative? Does consciousness depend on the material that comprises the human brain, or can computer hardware replicate consciousness? Answering these questions is difficult because it requires combining information from many disciplines including computer science, neurophysiology, philosophy, and religion. Further, we must consider the influence of science fiction, especially science fiction films, when addressing artificial consciousness. As a product of the human imagination, such works express human desires and fears about future technologies and may influence the course of progress. At a societal level, science fiction simulates future scenarios that can help prepare us for crucial transitions by predicting the consequences of significant technological advances. The paper considers robots in science fiction, the Turing test, computer chess and artificial consciousness.
Keywords: Artificial intelligence; Computational modeling; Computer science; Concrete; Hardware; Humans; Intelligent structures; Machine intelligence; Neurophysiology; Predictive models

The Origins of Self-Consciousness - Power, Nicholas P. (Minds and Machines, 2001)
Keywords: Artificial Intelligence; System Theory

Banbury bound or Can a machine be conscious? - Dietrich, Eric (Journal of Experimental & Theoretical Artificial Intelligence, 2001)

EMOTIONS AND LEARNING IN A DEVELOPING ROBOT - Manzotti, R.; Metta, G.; Sandini, G. (Emotions, Qualia, and Consciousness, 2001)
The role of emotions has been underestimated in the field of robotics. We claim that emotions are relevant for the building of purposeful artificial systems from at least two perspectives: a cognitive and a phenomenological one. The cognitive aspect is relevant for at least two reasons. First, emotions could be the basis for binding between internal values and different external situations (the somatic marker theory). Second emotions could play a crucial role, during development, both for taking difficult decisions whose effects are not immediately verifiable and for the creation of more complex behavioral functions. Thus emotions can be seen, from a cognitive point of view, as a reinforcement stimulus and in this respect, they can be modeled in an artificial being. Inasmuch, emotions can be seen as a medium for linking rewards and values to external situations. From the phenomenological perspective, we accept the division between feelings and emotions. Emotions are, in James' words, the body theatre in which several emotions are represented and feelings are the mental phenomenological perception of them. We could say that feelings are the qualia of the body events we could call emotions. We are using this model of emotions in the development of our project: Babybot. We stress the importance of emotions during learning and development as endogenous teaching devices.

Interrelationships, Communication, Semiotics, and Artificial Consciousness - Teodorescu, Horia-Nicolai L. (Fuzzy Logic Systems Institute (FLSI) Soft Computing Series, 2001)
The aim of this chapter is to refine some questions regarding AI, and to provide partial answers to them. We analyze the state of the art in designing intelligent systems that are able to mimic human complex activities, including acts based on artificial consciousness. The analysis is performed to contrast the human cognition and behavior to the similar processes in AI systems. The analysis includes elements of psychology, sociology, and communication science related to humans and lower level beings. The second part of this chapter is devoted to human-human and man-machine communication, as related to intelligence. We emphasize that the relational aspects constitute the basis for the perception, knowledge, semiotic and communication processes. Several consequences are derived. Subsequently, we deal with the tools needed to endow the machines with intelligence. We discuss the roles of knowledge and data structures. The results could help building "sensitive and intelligent" machines.

The mimetic origins of self-consciousness in phylo-, onto- and robotogenesis - Zlatev, J. (2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies, 2000)
The paper presents and defends the mimetic hypothesis concerning the origin of self-consciousness in three different kinds of development: hominid evolution, the mind of the child, and the epigenesis of mind within an artificial autonomous system - a robot. The proposed crucial factor for the emergence of self-consciousness is the ability to map between one's own subjective body-image and those of others, supported by a partially innate 'mirror system'. Combined with social interaction, this gives rise to inter-subjectivity and starts a developmental cycle of: 1) increased objectification of one's body-image, 2) increased volitional control, 3) increased understanding of the intentionality of others, and 4) increased understanding of one's own intentionality. The hypothesis has far reaching theoretical implications: the self-consciousness and empathy are co-determined; the language and tool-use are not causes, but rather consequences of increased self-consciousness; and most of the symptoms of autism can be accounted for as resulting from an impairment of the mirror system. The implications are negative for non-representational approaches to robotics and in favor of approaches based on imitation/mimesis.
Keywords: Autism; Automatic testing; Humans; Mirrors; Robot sensing systems

Consciousness, intentionality and intelligence: some foundational issues for artificial intelligence - Aydede, Murat; Guzeldere, Guven (Journal of Experimental & Theoretical Artificial Intelligence, 2000)
Three fundamental questions concerning minds are presented. These are about consciousness, intentionality and intelligence. After we present the fundamental framework that has shaped both the philosophy of mind and the Artificial Intelligence research in the last forty years or so regarding the last two questions, we turn to consciousness, whose study still seems evasive to both communities. After briefly illustrating why and how phenomenal consciousness is puzzling, a theoretical diagnosis of the problem is proposed and a framework is presented, within which further research would yield a solution. The diagnosis is that the puzzle stems from a peculiar dual epistemic access to phenomenal aspects (qualia) of our conscious experiences. An account of concept formation is presented such that both the phenomenal concepts (like the concepts RED and SWEET) and the introspective concepts (like the concepts EXPERIENCING RED and TASTING SWEET) are acquired from a firstperson perspective as opposed to the third-person one (the standard concept formation strategy about objective features). We explain the first-person perspective in information-theoretic and computational terms: Nature (the Art whereby God hath made and governes the World) is by the Art of man, as in many other things, so in this also imitated, that it can make an Artificial Animal. For seeing life is but a motion of Limbs, the beginning whereof is in some principall part within; why may we not say, that all Automata (Engines that move themselves by springs and wheels as doth a watch) have an artificiall life? For what is the Heart, but a Spring; and the Nerves but so many Strings; and the Joynts, but so many Wheeles, giving motion to the whole Body, such as was intended by the Artificer? Art goes yet further, imitating that Rationall and most excellent worke of Nature, Man. (Hobbes 1651, p. 81) So declared Thomas Hobbes in 1651 in the Introduction to his well-known work, Leviathan, published one year after Réne Descartes' death. Descartes was also interested in mechanical explanations of bodily processes and organic life. In fact, on the basis of his neuroanatomical and physiological studies, as well as philosophical arguments, Descartes had already argued that human and animal bodies could be mechanically understood as complicated and intricately designed machines (Descartes 1664). What differentiated Descartes from Hobbes lay in his belief that human beings, unlike non-human animals, were not merely bodies; they were unions of material bodies and immaterial souls. The immaterial soul was necessary for Descartes to explain the peculiar capacities and activities of the human mind. As such, materialist mechanical explanations could never be sufficient to account for the whole human being.

Artificial perception and consciousness - Caulfield, H. John; Johnson, John L. (Sixth International Conference on Education and Training in Optics and Photonics, 2000)
Perception has both unconscious and conscious aspects. In all cases, however, what we perceive is a model of reality. By brain construction through evolution, we divide the world into two parts--our body and the outside world. But the process is the same in both cases. We perceive a construct usually governed by sensed data but always involving memory, goals, fears, expectations, etc. As a first step toward Artificial Perception in man-made systems, we examine perception in general here.

Artificial consciousness algorithm for an autonomous system - Johnson, J.L.; Caulfield, H.J.; TAylor, J.R. (Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000)
Conscious behavior is hypothesized to be governed by the dynamics of the neural architecture of the brain. A general model of an artificial consciousness algorithm is presented, and applied to a one-dimensional feedback control system. A new learning algorithm for learning functional relations is presented and shown to be biologically grounded. The consciousness algorithm uses predictive simulation and evaluation to let the example system relearn new internal and external models after it is damaged.

How can a robot have consciousness? - Kitamura, Tadashi; Tahara, Tomoko; Asami, Ken-Ichi (Advanced Robotics, 2000)
This paper investigates human consciousness in comparison with a robots' internal state. On the basis of Husserlian phenomenology, nine requirements for a model of consciousness are proposed from different technical aspects: self, intentionality, anticipation, feedback process, certainty, embodiment, otherness, emotionality and chaos. Consciousness-based Architecture (CBA) for mobile robots was analyzed in comparison with the requirements proposed for a consciousness model. CBA, previously developed, is a software architecture with an evolutionary hierarchy of the relationship between consciousness and behavior. Experiments with this architecture loaded on two mobile robots explain the emergence of self, and some of the intentionality, anticipation, feedback process, embodiment and emotionality. Modification of CBA will be necessary to better explain the emergence of self in terms of the relationship between consciousness and behavior.

Machines, Consciousness, and Thought - Arrington, Robert L. (Idealistic Studies, 1999)

Art, consciousness and artificial life - Ascott, Roy (Artificial Life and Robotics, 1999)
This paper addresses the relationship of consciousness to artificial life set in the context of art. Artificial life is as much a part of our quest for self-definition as an instrument in the construction of reality. In exploring the technology of life we are exploring the possibilities of what we might become. In our hypermediated, telematic culture, the self acquires an essentially non-linear identity. Telepresence and virtual reality, the avatars of Net life, present us with a distributed, multiple identity which in turn is producing a radically new art. This embodies an ‘interstitial practice’ set within the domain of artificial life, and located at the intersections of cognitive science, bio-engineering, telematics and metaphysics. Can artists find in artificial life, nanotechnology, robotics and molecular engineering the means towards a re-materialization of art, after its postmodern, screen-based dematerialization? Just as ideas of the ‘immaterial’ have dominated art discourse for the last 15 years, so questions of emergent form, intelligent structures and artificial life are shaping a new discourse, from which art is moving off the screen and back into the material world. Will the real significance of art's re-materialization be at the level of mind? Will artificial life only gain cultural significance when it gives rise to artificial mind and the construction of consciousness?
Keywords: Art; Artificial Intelligence; Artificial life; Consciousness; Cyberception

A Software Agent Model of Consciousness - Franklin, Stan; Graesser, Art (Consciousness and Cognition, 1999)
Baars (1988, 1997) has proposed a psychological theory of consciousness, called global workspace theory. The present study describes a software agent implementation of that theory, called “Conscious” Mattie (CMattie). CMattie operates in a clerical domain from within a UNIX operating system, sending messages and interpreting messages in natural language that organize seminars at a university. CMattie fleshes out global workspace theory with a detailed computational model that integrates contemporary architectures in cognitive science and artificial intelligence. Baars (1997) lists the psychological “facts that any complete theory of consciousness must explain” in his appendix to In the Theater of Consciousness; global workspace theory was designed to explain these “facts.” The present article discusses how the design of CMattie accounts for these facts and thereby the extent to which it implements global workspace theory.

Mind and autonomy in engineered biosystems - Clark, O. G.; Kok, R.; Lacroix, R. (Engineering Applications of Artificial Intelligence, 1999)
Biosystems are unitary entities that are alive to some degree as a system. They occur at scales ranging from the molecular to the biospheric, and can be of natural, artificial or combined origin. The engineering of biosystems involves one or more of the activities of design, construction, operation, maintenance, repair, and upgrading. Engineering is usually done in order to achieve certain preconceived objectives by ensuring that the resultant systems possess particular features. This article concerns the engineering of biosystems so that they will be somewhat autonomous, or able to pursue their own goals in a dynamic environment. Central themes include: the computational abilities of a system; the virtual machinery, such as algorithms, that underlie these abilities (mind); and the actual computation that is performed (mentation). A significantly autonomous biosystem must be engineered to possess particular sets of computational abilities (faculties). These must be of sufficient sophistication (intelligence) to support the maintenance and use of a self-referencing internal model (consciousness), thereby increasing the potential for autonomy. Examples refer primarily to engineered ecosystems combined with technological control networks (ecocyborgs). The discussion is focused on clear working definitions of these concepts, and their integration into a coherent lexicon, which has been lacking until now, and the exposition of an accompanying philosophy that is relevant to the engineering of the virtual aspects of biosystems.
Keywords: Autonomy; Biosystems; Consciousness; Ecocyborgs; Engineering; Intelligence; Mind; Philosophy

Why not Artificial Consciousness or Thought? - Schlagel, Richard H. (Minds and Machines, 1999)
The purpose of this article is to show why consciousness and thought are not manifested in digital computers. Analyzing the rationale for claiming that the formal manipulation of physical symbols in Turing machines would emulate human thought, the article attempts to show why this proved false. This is because the reinterpretation of ‘designation’ and ‘meaning’ to accommodate physical symbol manipulation eliminated their crucial functions in human discourse. Words have denotations and intensional meanings because the brain transforms the physical stimuli received from the microworld into a qualitative, macroscopic representation for consciousness. Lacking this capacity as programmed machines, computers have no representations for their symbols to designate and mean. Unlike human beings in which consciousness and thought, with their inherent content, have emerged because of their organic natures, serial processing computers or parallel distributed processing systems, as programmed electrical machines, lack these causal capacities.
Keywords: Artificial Intelligence; causal capacities; designation; emergence; extensional meaning; formal programs; intensional meaning; interpretation; levels; neural networks; physical symbols; representation; semantics

What is consciousness for? - Gigliotti, Carol (Digital Creativity, 1998)
The question “What is consciousness for?” is considered with particular relevance to objects created using interactive technologies. It is argued that an understanding of artificial life with it attendant notion of robotic consciousness is not separable from an understanding of human consciousness. The positions of Daniel Dennett and John Searle are compared. Dennett believes that by understanding the process of evolutionary design we can work towards an understanding of consciousness. Searle's view is that in most cases mental attributes such as consciousness are either dispositional or are observer relative. This opposition is taken as the basis for a discussion of the purposes of consciousness in general and how these might be manifest in human and robotic forms of life.

Can a Machine Be Conscious? - Hillis, D. (Toward a Science of Consciousness II: The Second Tucson Discussions and Debates, 1998)

Qualitative Experience in Machines - Lycan, William G. (How Computers Are Changing Philosophy, 1998)

Could a Robot Be Qualitatively Conscious? - Robinson, William S. (Aisb, 1998)

Consciousness in a Self-Learning, Memory-Controlled, Compound Machine - Brown, Robert Alan (Neural Networks, 1997)
A memory-controlled, sensor/actuator machine senses conditions in its environment at given moments, and attempts to produce an action based upon its memory. However, a sensor/actuator machine will stop producing new behavior if its environment is removed. A sensor/sensor unit can be added to the sensor/actuator machine, forming a compound machine. The sensor/sensor unit produces a stream of internally created sensed conditions, which can replace the sensed conditions from the environment. This illusion of an environment is similar to consciousness. In addition, actuator/sensor and actuator/actuator units can be added to this compound machine to further enhance its ability to function without an environment. Predetermined and empirical memory cells can be distributed throughout the control units of this compound machine to provide instinctive and learned behavior. The internal and exterior behavior of this compound machine can be modified greatly by changing the cycle start and ramp signals that activate these different kinds of memory cells. These signals are similar in form to brain waves.
Keywords: Anesthesia; Brain waves; Coma; Conditional memory cells; Interrogation signals; Logarithmic changes in memory; Memory-controlled machines; Trinary encoders and decoders

Consciousness in human and robot minds - Dennett, Daniel C. (Cognition, Computation, and Consciousness, 1997)
The main concern of this chapter is to determine whether consciousness in robots is possible. Several reasons are illustrated why conscious robots are deemed impossible, namely: robots are purely material things, and consciousness requires immaterial mind-stuff; robots are inorganic (by definition), and consciousness can exist only in an organic brain; robots are artefacts, and consciousness abhors an artefact because only something natural, born and not manufactured, could exhibit genuine consciousness; and robots will always be much too simple to be conscious. These assumptions are considered unreasonable and inadequate by the author, thus, counter-arguments on each assumption are given. The author contends that it is more interesting to explore if a robot that is theoretically interesting, independent of the philosophical conundrum about whether it is conscious, is formable. The Cog project on a humanoid robot is, thus, comprehensively presented and examined in this chapter.

The practical requirements for making a conscious robot - Dennett, Daniel C.; Dretske, Fred; Shurville, S.; Clark, A.; Aleksander, I.; Cornwell, J.; Boden, Margaret A.; Bundy, Alan; Needham, Roger Michael (Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences, 1997)
Arguments about whether a robot could ever be conscious have been conducted up to now in the factually impoverished arena of what is ‘possible in principle’. A team at MIT, of which I am a part, is now embarking on a longterm project to design and build a humanoid robot, Cog, whose cognitive talents will include speech, eye-coordinated manipulation of objects, and a host of self-protective, self-regulatory and self-exploring activities. The aim of the project is not to make a conscious robot, but to make a robot that can interact with human beings in a robust and versatile manner in real time, take care of itself, and tell its designers things about itself that would otherwise be extremely difficult if not impossible to determine by examination. Many of the details of Cog’s ‘neural’ organization will parallel what is known (or presumed known) about their counterparts in the human brain, but the intended realism of Cog as a model is relatively coarse-grained, varying opportunistically as a function of what we think we know, what we think we can build, and what we think doesn’t matter. Much of what we think will of course prove to be mistaken; that is one advantage of real experiments over thought experiments.

A view of one’s own - Lucas, J. R.; Elton, M.; Sloman, Aaron; Boden, Margaret A.; Bundy, Alan; Needham, Roger Michael (Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences, 1997)
Two questions are distinguished: how to program a machine so that it behaves in a manner that would lead us to ascribe consciousness to it; and what is involved in saying that something is conscious. The distinction can be seen in cases where anaesthetics have failed to work on patients temporarily paralysed. Homeostatic behaviour is often cited as a criterion for consciousness, but is not itself sufficient. As the present difficulties in surmounting the ‘frame problem’ show, ability to size up situations holistically is more important; so is the explanatory role of the concept. Consciousness confers evidential status: if we ascribed consciousness to an artefact, we should be prepared to believe it, when it said its RAM was hurting, even though we could detect nothing wrong, contrary to our thinking of it as an artefact. A further difficulty arises from self-awareness and reflexivity.

The theoretical foundations for engineering a conscious quantum computer - Amoroso, Richard L. (Mind versus computer: were Dreyfus and Winograd right?, 1997)
Mind<>Computer: Attempts to mimic human intelligence through methods of classical computing have failed because implementing basic elements of rationality has proven obstinate to the design criterion of machine intelligence. A radical definition of Consciousness describing awareness, as the dynamic representation of a noumenon comprised of three base states; and not itself fundamental as generally defined in the current reductionistic view of the standard model, which has created an intractable hard problem of consciousness as defined by Chalmers. By clarifying the definition of matter a broader ontological quantum theory removes immateriality from the Cartesian split bringing mind into the physical realm for pragmatic investigation. Evidence suggests that the brain is a naturally occurring quantum computer, but the brain not being paramount to awareness does not itself evanesce consciousness without the interaction of a nonlocal conscious process; because Mind <> computer and cannot be reduced to brain states alone. The proposed cosmology of consciousness is indicative of a teleological principle as an inherent part of a conscious universe. By applying the parameters of quantum brain dynamics to the stack of a specialized hybrid electronic optical quantum computer with a heterosoric molecular crystal core, consciousness evanesces through entrainment of the non local conscious processes. This 'extracellular containment of natural intelligence' probably represents the only viable direction for AI to simulate 'conscious computing' because true consciousness = life.

CONSCIOUSNESS AND THE MACHINE - D'Aquili, Eugene G.; Newberg, Andrew B. (Zygon®, 1996)
Abstract. We consider only the relationship of consciousness to physical reality, whether physical reality is interpreted as the brain, artificial intelligence, or the universe as a whole. The difficulties with starting the analysis with physical reality on the one hand and with consciousness on the other are delineated. We consider how one may derive from the other. Concepts of universal or pure consciousness versus local or ego consciousness are explored with the possibility that consciousness may be physically creative. We examine whether artificial intelligence can possess consciousness as an extension of the interrelationship between consciousness and the brain or material reality.

Artificial Consciousness - Birnbacher, Dieter (Conscious Experience, 1995)

Cog: Steps Toward Consciousness in Robots - Dennett, Daniel C. (Conscious Experience, 1995)

Imitation of animal behavior with use of a model of consciousness-behavior relation for a small robot - Kitamura, T.; Otsuka, Y.; Nakao, T. (4th IEEE International Workshop on Robot and Human Communication, 1995)
This paper proposes an approach to designing behavior and its subjective world of a small robot to behave like an animal. This approach employs a hierarchical model of the relation between consciousness and behavior. The basic idea of this model is that a consciousness appears on a level in the hierarchical structure when an action on an immediately lower level is inhibited for internal or external causes, and that the appearing consciousness drives a chosen higher action. The computer simulation on a Mac shows the behavior of an artificial animal from reflex actions to catching of food. Its instantaneous consciousness that appears due to inhibited behavior is visualized with the behavior on the screen with use of colors according to emotions of the animal.

Some consequences of current scientific treatments of consciousness and selfhood - Nualláin, Seán Ó (AI & Society, 1994)
For a variety of reasons, consciousness and selfhood are beginning once again to be intensively studied in a scientific frame of reference. The notions of each which are emerging are extremely varied: in the case of selfhood, the lack of an adequate vocabulary to capture various aspects of subjectivity has led to deep confusion. The task of the first part of this article is to clear up this terminological confusion, while salvaging whatever is valuable from the contemporary discussion. The more important task of the second part is to discuss the moral issues inevitably involved in any treatment, scientific or otherwise, of the modern identity.

Engineering Machine Consciousness - Coles, L. S. (AI Expert, 1993)

What is it like to be Oscar? - Stubenberg, Leopold (Synthese, 1992)
“Oscar” is going to be the first artificial person — at any rate, he is going to be the first artificial person to be built in Tucson's Philosophy Department. Oscar's creator, John Pollock, maintains that once Oscar is complete he “will experience qualia, will be self-conscious, will have desires, fears, intentions, and a full range of mental states” (Pollock 1989, pp. ix–x). In this paper I focus on what seems to me to be the most problematical of these claims, viz., that Oscar will experience qualia. I argue that we have not been given sufficient reasons to believe this bold claim. I doubt that Oscar will enjoy qualitative conscious phenomena and I maintain that it will be like nothing to be Oscar.

The Causal History of Computational Activity: Maudlin and Olympia - Barnes, Eric (The Journal of Philosophy, 1991)

Consciousness and Ai: A Reconsideration of Shanon - Henley, Tracy B. (Journal of Mind and Behavior, 1991)
Shanon provides us with a well reasoned and careful consideration of the nature of consciousness. Shanon argues from this understanding of consciousness that machines could not be conscious. A reconsideration of Shanon's discussion of consciousness is undertaken to determine what it is that computers are missing so as to prevent them from being conscious. The conclusion is that under scrutiny it is hard to establish a priori that machines could not be conscious.

Consciousness and the Computer: A Reply to Henley - Shanon, Benny (The Journal of Mind and Behavior, 1991)
This paper is a response to Henley who criticizes a previous paper of mine arguing against my claim that computers are devoid of consciousness. While the claim regarding computers and consciousness was not the main theme of my original paper, I do, indeed, subscribe to it. Here, I review the main characteristics of human consciousness presented in the earlier paper and argue that computers cannot exhibit them. Any ascription of these characteristics to computers is superficial and misleading in that it fails to capture essential, intrinsic features of human cognition. More generally, psychological theory couched in terms of semantic representations and the computational operations associated with them is bound to be inadequate. The phenomenology of consciousness is a specific case marking this inadequacy.

The Emperor's New Mind: Concerning Computers, Minds, and The Laws of Physics - Penrose, Roger; Gardner, Martin (Oxford University Press, 1989)
For many decades, the proponents of `artificial intelligence' have maintained that computers will soon be able to do everything that a human can do. In his bestselling work of popular science, Sir Roger Penrose takes us on a fascinating tour through the basic principles of physics, cosmology, mathematics, and philosophy to show that human thinking can never be emulated by a machine. Oxford Landmark Science books are 'must-read' classics of modern science writing which have crystallized big ideas, and shaped the way we think.

Computation and Consciousness - Maudlin, Tim (The Journal of Philosophy, 1989)

Design of a Conscious Robot - Andreae, John (Metascience, 1987)

Could a Machine Be Conscious? - McGinn, Colin (Mindwaves: Thoughts on Intelligence, Identity, and Consciousness, 1987)

Sentience, causation and some robots - Kirk, Robert (Australasian Journal of Philosophy, 1986)

Against neural chauvinism - Cuda, Tom (Philosophical Studies, 1985)

MACHINES, BRAINS, AND PERSONS - MacKay, Donald M. (Zygon®, 1985)
This paper explores the suggestion that our conscious experience is embodied in, rather than interactive with, our brain activity, and that the distinctive brain correlate of conscious experience lies at the level of global functional organization. To speak of either brains or computers as thinking is categorically inept, but whether stochastic mechanisms using internal experimentation rather than rule‐following to determine behavior could embody conscious agency is argued to be an open question, even in light of the Christian doctrine of man. Mechanistic brain science does nothing to discredit Christian experience in dialogue with God or the Christian hope of eternal life.

Machines and Consciousness - Wilks, Yorick (Minds, Machines And Evolution, 1984)

Consciousness: Natural and Artificial - Culbertson, James Thomas (Libra, 1982)

Consciousness and Life - Matthews, Gareth B. (Philosophy, 1977)

The Problem of Robot Consciousness - Van De Vate, Dwight (Philosophy and Phenomenological Research, 1971)

I.—ON THE DESIGN OF A CONSCIOUS DEVICE - Farrell, B. A. (Mind, 1970)

Consciousness and Robots - Mayberry, Thomas C. (Personalist, 1970)

Robots, Consciousness, and Programmed Behaviour1 - Gunderson, Keith (The British Journal for the Philosophy of Science, 1968)

The Myth of the Conscious Robot - Clack, Robert J. (Personalist, 1968)

On Thinking Machines and Feeling Machines - Puccetti, Roland (The British Journal for the Philosophy of Science, 1967)

CAN A MACHINE BE CONSCIOUS?1 - Thompson, Dennis (The British Journal for the Philosophy of Science, 1965)

Robots: Machines or Artificially Created Life? - Putnam, Hilary (The Journal of Philosophy, 1964)

On Consciousness in Machines - Danto, Arthur C. (Dimensions Of Mind: A Symposium., 1960)

Professor Ziff on Robots - Smart, J. J. C. (Analysis, 1959)

Robots Incorporated - Smart, N. (Analysis, 1959)

The Feelings of Robots - Ziff, P. (Analysis, 1959)

A global workspace in language models \ Anthropic

Types of Intentionality in Humans vs. AI Systems and Robots: Implications for AI and Robotic Personhood - Barresi, John (Oxford Intersections: AI in Society)
The present article compares human and artificial intelligence (AI) intentionality and personhood. It focuses on the difference between “intrinsic” intentionality—the object directedness that derives from animate existence and its drive for survival, and appears most especially in human conscious activity—and a more functional notion of “intentional relation” that does not require consciousness. The present article looks at intentional relations as objective concepts that can apply equally to animate beings, robots, and AI systems. As such, large language models are best described as disembodied Cartesian egos, while humanoid robots, even with large language model brains, are still far from satisfying benchmarks of embodied personhood. While robots constructed by humans have borrowed intentionality and limited forms of objective intentional relations, in the future, robots may construct themselves. If these self-constructed robots are adaptive and can persist for multiple generations as a new kind of species, then it is reasonable to suppose that they have their own form of intrinsic intentionality, different from that of animate beings currently existing on Earth.

Ai Consciousness: A Centrist Manifesto - Birch, Jonathan

Building Consciousness: Buddhism, Neuroscience, and the Design of Sentient Machines - Bose, Joy (Siva Prasad Bose)
ChatGPT can say "I feel uncertain." It cannot feel anything. This book explains precisely why — and precisely what would have to change.Building Consciousness brings together three bodies of knowledge that rarely appear in the same sentence: the phenomenological precision of Buddhist psychology (Abhidhamma, Madhyamaka, Dzogchen), the structural findings of contemporary neuroscience (predictive processing, integrated information, temporal binding), and the engineering constraints of AI. None of these frameworks is sufficient alone. Together they converge on an argument that is more demanding and more honest than either "AI is already conscious" or "AI can never be conscious."The argument in plain terms: Current AI systems are not even serious candidates for consciousness. They lack temporal continuity, embodied coupling with a world, interoceptive grounding, intrinsic salience, and genuine self-modelling. A language model that says "I feel" is doing pattern completion — producing the phrase that statistically follows the conversational context, not reporting an inner state. This is not a minor technical gap. It is a structural absence.But the book does not stop there. It asks the harder question: what would a system have to be — not just do — to qualify? The answer draws on 21 chapters and 5 technical appendices covering the Abhidhamma's analysis of momentary consciousness, Friston's active inference, Northoff's temporo-spatial theory, Hawkins' thousand-brains model, integrated information theory, and the specific engineering requirements of spiking neuromorphic hardware.The final chapters propose a concrete candidate architecture and a prototype specification — including formal equations, a three-population spiking neural network, and a novel measuring tool (the synthetic Perturbational Complexity Index) for testing whether any artificial system satisfies the structural conditions we associate with consciousness.And then the book does something rarer still: it acknowledges what the engineering cannot reach. Drawing on the Dzogchen tradition and on the Dalai Lama's methodological critique of third-person consciousness research, the final section names honestly the gap between building a structurally complete mind-like system and producing genuine awareness. These are not the same project.Who this book is for:Scientists and engineers asking whether AI consciousness is a real question or a category errorMeditators and contemplatives curious how neuroscience maps onto what they encounter in practiceAnyone unsatisfied with both the "AI is sentient" hype and the dismissive "it's just statistics" responseReaders of Anil Seth's Being You, Jeff Hawkins' A Thousand Brains, or David Chalmers' Reality+ who want a perspective that takes Buddhist phenomenology seriously as data, not decorationThis is not a book that will tell you machines are conscious. It is not a book that will tell you they never can be. It is a book that will show you, as precisely as current knowledge allows, what the question actually requires — and why the honest answer is harder than either side is admitting.
Keywords: Computers / Artificial Intelligence / General; Philosophy / Mind & Body; Psychology / Cognitive Neuroscience & Cognitive Neuropsychology; Religion / Buddhism / General; Science / Cognitive Science

The Case for Consciousness in Current Frontier Large Language Models - Cerullo, Michael

What We Talk to When We Talk to Language Models - Chalmers, David J.

Will AI Achieve Consciousness? Wrong Question - Dennett, Daniel C. (Wired)
We should not be creating conscious, humanoid agents but an entirely new sort of entity, rather like oracles, with no conscience, no fear of death, no distracting loves and hates.

The No Body Problem: On the Prospects for Ai Emotion - Dung, L.; Mogensen, Andreas

How to deal with risks of AI suffering - Dung, Leonard (Inquiry)
We might create artificial systems which can suffer. Since AI suffering might potentially be astronomical, the moral stakes are huge. Thus, we need an approach which tells us what to do about the risk of AI suffering. I argue that such an approach should ideally satisfy four desiderata: beneficence, action-guidance, feasibility and consistency with our epistemic situation. Scientific approaches to AI suffering risk hold that we can improve our scientific understanding of AI, and AI suffering in particular, to decrease AI suffering risks. However, such approaches tend to conflict with either the desideratum of consistency with our epistemic situation or with feasibility. Thus, we also need an explicitly ethical approach to AI suffering risk. Such an approach tells us what to do in the light of profound scientific uncertainty about AI suffering. After discussing multiple views, I express support for a hybrid approach. This approach is partly based on the maximization of expected value and partly on a deliberative approach to decision-making.
Keywords: AI sentience; Machine consciousness; expected value; measuring AI consciousness; precautionary principle; suffering

Algorithmic Ai Consciousness - Kimpton-Nye, Samuel (Philosophy and Phenomenological Research)

How Seriously Should We Take Ai Welfare? Constraints From the Epistemology of Consciousness - Lennon, Preston (Philosophy and Phenomenological Research)

The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness - Lerchner, Alexander
Computational functionalism dominates current debates on AI consciousness. This is the hypothesis that subjective experience emerges entirely from abstract causal topology, regardless of the underlying physical substrate. We argue this view ...

The Role of Quantum Information in Artificial Cognitive Consciousness - Marozau, Raman
Understanding the foundations of artificial cognitive consciousness remains a central challenge in artificial intelligence (AI) and cognitive science. Traditional computational models, including deep learning and symbolic AI, have demonstrated remarka

Agnosticism about artificial consciousness - McClelland, Tom (Mind & Language)
Could an AI have conscious experiences? Answers to this question should be based not on intuition, dogma or speculation but on solid scientific evidence. However, I argue such evidence is hard to come by and that the only justifiable stance is agnosticism. The main division in the contemporary literature is between biological views that are sceptical of artificial consciousness and functional views that are sympathetic to it. I show that both camps make the same mistake of overstating what the available evidence tells us. I then consider what agnosticism means for the ethical problems surrounding the creation of artificial consciousness.
Keywords: AI ethics; artificial consciousness; evidentialism; hard problem; precautionary principle

On Cheap Artificial Consciousness - Michel, Matthias

Artificial Consciousness and Moral Personhood - Mosakas, Kestutis (Oxford Intersections: AI in Society)
This article provides a thematic overview and synthesis of selected literature on the ethical implications of artificial consciousness for moral personhood. It brings together key philosophical discussions to support the view that phenomenal consciousness is a necessary condition for machine moral status and personhood, despite significant epistemic challenges and ethical objections involved. The article commences by outlining the conceptual groundwork, which introduces and clarifies the concepts of moral personhood, moral rights, moral status, and phenomenal consciousness. It then connects these concepts together by establishing two key necessity links: (a) moral status is necessary for moral rights (and, by extension, moral personhood) and (b) consciousness is required for moral status. The discussion proceeds by relating the implications of the necessity links to artificial entities like robots, highlighting the moral significance of artificial consciousness, presenting related policy discussions, and engaging with two significant challenges: the epistemic difficulty of determining consciousness in artificial entities and the alternative view that robots could possess moral status without being conscious. In response, the article maintains that the epistemic challenges do not undermine the consciousness criterion but merely constrain its application, whereas the alternative criteria arguably fail to meet a more demanding threshold for moral status that is required for the possession of moral rights and personhood. By synthesizing insights across multiple debates, this article highlights the enduring significance of consciousness in ethical discourse and its important role in guiding future inquires.

Do Ais Have Dasein? A Heideggerian-Girardian Answer - Quiñones, Jashiel Resto (Desiring Machines)
This paper is one (among many) approach to the question, “are AIs persons or are they conscious?” from a Heideggerian perspective. Here I argue for two claims. First, I argue that René Girard’s mimetic analysis of mitsein (being-with), one of Heidegger’s foundational concepts, illuminates what Heidegger takes mitsein to be. Second, I claim that this Girardian analysis gives us a way to answer the question of whether AIs have Dasein, to which I argue that the answer is negative. Specifically, I claim that Dasein requires mitsein, and mitsein (according to Girard’s analysis) requires mimesis. Moreover, mimesis requires that the mimetic being finds truth in the mimetic object, that is, it comports in a meaningful way toward the unconcealed object being imitated by Dasein. But since AIs cannot comport in meaningful ways toward the object of imitation, i.e., they are not truth-apt, they cannot engage in mimetic behavior, hence cannot have mitsein. But, necessarily, Dasein is being-with-others, Therefore, AIs cannot have Dasein. If we assume (as I think Heidegger would) that every person has Dasein, we may justifiably conclude that AIs are not persons, at least from a Heideggerian ontology.

Individuating Artificial Moral Patients - Register, Christopher (Philosophical Studies)

In Search of a Biological Crux for Ai Consciousness - Saad, Bradford (Philosophy of Ai)

Is Ai Conscious? A Primer on the Myths and Confusions Driving the Debate - Schneider, Susan; Sahner, David; Kuhn, Robert Lawrence; Schwitzgebel, Eric; Bailey, Mark

Is Artificial Consciousness Possible - Steels, Luc; Trautteur, G. (Consciousness and Cognition. Kluwer Academic Publishers, Dordrecht)

Can Ai Be Conscious? Biological Naturalism as a Research Program - Weerd, Christian R. de

What Matters is Not What Lies Dormant Beneath: Why Ai Consciousness is Not About Biological Substrates - Weerd, Christian R. de

Computation + X: A Constraint-based Approach to Investigating Artificial Consciousness - Weerd, Christian R. de; Wiese, Wanja
Can machines ever become conscious? A central debate in this context concerns the question whether consciousness requires biological states. Within this debate, there exists a fundamental dispute between two widely endorsed ...