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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.

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.

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.

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.

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.

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 (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.

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.

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.

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.

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.

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.

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.

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.