Search

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.

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.

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.

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.

<div> Understanding consciousness remains one of neuroscience’s greatest challenges. While classical neurophysiology explains many features of brain activity,

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.

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.

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).

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.

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.

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.

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.