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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.