This article argues that if panpsychism is true, then there are grounds for thinking that digitally-based artificial intelligence 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—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 theory of consciousness, which we contend may need to be supplanted by a theory of macroconsciousness as analog microphysical-phenomenal information integration. (shrink)

This edited volume presents perspectives from computer science, information theory, neuroscience and brain imaging, aesthetics, social sciences, psychiatry, and philosophy to answer frontier questions related to artificial intelligence and human experience. Can a machine think, believe, aspire and be purposeful as a human? What is the place in the machine world for hope, meaning and transformative enlightenment that inspires human existence? How, or are, the minds of machines different from that of humans and other species? These questions are responded to (...) along with questions in the intersection of health, intelligence and the brain. It highlights the place of consciousness by attempting to respond to questions with the help of fundamental reflections on human existence, its life-purposes and machine intelligence. The volume is a must-read for interdisciplinary and multidisciplinary researchers in humanities and social sciences and philosophy of science who wish to understand the future of AI and society. (shrink)

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. (shrink)

In this chapter I offer two novel arguments for what I call strong primitivism about cognitive phenomenology, the thesis that there exists a phenomenology of cognition that is neither reducible to, nor dependent upon, sensory phenomenology. I then contend that strong primitivism implies that phenomenal consciousness does not require sensory processing. This latter contention has implications for the philosophy of artificial intelligence. For if sensory processing is not a necessary condition for phenomenal consciousness, then it plausibly follows that (...) AI consciousness (assuming that it is possible) does not require embodiment. The overarching goal of this paper is to show how different topics in the analytic philosophy of mind can be brought to bear on an important issue in the philosophy of artificial intelligence. (shrink)

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. This is “cognitive-motor dissociation” (CMD). Recent research has used machine learning to diagnose CMD from electroencephalogram (EEG) recordings. These techniques have high false discovery rates, raising a serious problem of inductive risk. It is no solution to communicate the false discovery rates directly to the patient’s family, because this information may confuse, alarm and mislead. Instead, we need a procedure (...) for generating case-specific probabilistic assessments that can be communicated clearly. This article constructs a possible procedure with three key elements: (1) a shift from categorical “responding or not” assessments to degrees of evidence; (2) the use of patient-centred priors to convert degrees of evidence to probabilistic assessments; and (3) the use of standardized probability yardsticks to convey those assessments as clearly as possible. (shrink)

Films involving Artificial Intelligence often miss the disembodied nature of consciousness and promulgate an erroneous conceptualization of mind. This article explores agency, Spinoza's "conatus," and its neuro-chemical foundations in light of films like: "2001: A Space Oddity," "After Yang," "Upgrade," "Ex Machina," and more.

We propose four policies of ethical design of human-grade Artificial Intelligence. Two of our policies are precautionary. Given substantial uncertainty both about ethical theory and about the conditions under which AI would have conscious experiences, we should be cautious in our handling of cases where different moral theories or different theories of consciousness would produce very different ethical recommendations. Two of our policies concern respect and freedom. If we design AI that deserves moral consideration equivalent to that of human (...) beings, that AI should be designed with self-respect and with the freedom to explore values other than those we might impose. We are especially concerned about the temptation to create human-grade AI pre-installed with the desire to cheerfully sacrifice itself for its creators’ benefit. (shrink)

For many people, consciousness is one of the defining characteristics of mental states. Thus, it is quite surprising that consciousness has, until quite recently, had very little role to play in the cognitive sciences. Three very popular multi-authored overviews of cognitive science, Stillings et al. [33], Posner [26], and Osherson et al. [25], do not have a single reference to consciousness in their indexes. One reason this seems surprising is that the cognitive revolution was, in large part, (...) a repudiation of behaviorism's proscription against appealing to inner mental events. When researchers turned to consider inner mental events, one might have expected them to turn to conscious states of mind. But in fact the appeals were to postulated inner events of information processing. The model for many researchers of such information processing is the kind of transformation of symbolic structures that occurs in a digital computer. By positing procedures for performing such transformation of incoming information, cognitive scientists could hope to account for the performance of cognitive agents. Artificial intelligence, as a central discipline of cognitive science, has seemed to impose some of the toughest tests on the ability to develop information processing accounts of cognition: it required its researchers to develop running programs whose performance one could compare with that of our usual standard for cognitive agents, human beings. As a result of this focus, for AI researchers to succeed, at least in their primary task, they did not need to attend to consciousness; they simply had to design programs that behaved appropriately (no small task in itself!). This is not to say that conscious was totally ignored by artificial intelligence researchers. Some aspect of our conscious experience seemed critical to the success of any information processing model. For example, conscious agents exhibit selective attention. Some information received through their senses is attended to; much else is ignored.. (shrink)

As AI edges toward consciousness, the establishment of a robust legal framework becomes essential. This paper advocates for a framework inspired by Allama Muhammad Iqbal's “Khudi”, which prioritizes ethical self-realization and social responsibility over Friedrich Nietzsche’s self-centric “Will to Power”. We propose that conscious AI, reflecting Iqbal’s ethical advancement, should exhibit behaviors aligned with social responsibility and, therefore, be prepared for legal recognition. This approach not only integrates Iqbal's philosophical insights into the legal status of AI but also offers (...) a novel perspective that extends beyond traditional jurisprudence. Additionally, we underscore the value of poetry and literature in shaping the conceptualization of AI consciousness and argue that these sources enrich legal and technological discourse, ensuring AI development is in harmony with societal and ethical standards. (shrink)

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 viewpoint that consciousness, including feeling, could be fully expressed by a computational device is known as strong artificial intelligence or strong AI. Here I offer a defense of strong AI based on machine-state functionalism at the quantum level, or quantum-state functionalism. I consider arguments against strong AI, then summarize some counterarguments I find compelling, including Torkel Franzén’s work which challenges Roger Penrose’s claim, based on Gödel incompleteness, that mathematicians have nonalgorithmic levels of “certainty.” Some consequences of strong AI (...) are then considered. A resolution is offered of some problems including John Searle’s Chinese Room problem and the problem of consciousness propagation under isomorphism. (shrink)

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.

In light of recent breakneck pace in machine learning, questions about whether near-future artificial systems might be conscious and possess moral status are increasingly pressing. This paper argues that as matters stand these debates lack any clear criteria for resolution via the science of consciousness. Instead, insofar as they are settled at all, it is likely to be via shifts in public attitudes brought about by the increasingly close relationships between humans and AI users. Section 1 of the paper (...) I briefly lays out the current state of the science of consciousness and its limitations insofar as these pertain to machine consciousness, and claims that there are no obvious consensus frameworks to inform public opinion on AI consciousness. Section 2 examines the rise of conversational chatbots or Social AI, and argues that in many cases, these elicit strong and sincere attributions of consciousness, mentality, and moral status from users, a trend likely to become more widespread. Section 3 presents an inconsistent triad for theories that attempt to link consciousness, behaviour, and moral status, noting that the trends in Social AI systems will likely make the inconsistency of these three premises more pressing. Finally, Section 4 presents some limited suggestions for how consciousness and AI research communities should respond to the gap between expert opinion and folk judgment. (shrink)

Presented here is a review of the book by Michael Wooldridge The Road to Conscious Machines: The Story of AI. The book was published in 2021 by Pelican Publishing Company. The book presents a philosophical exploration of the AI-related quest to understand the essence of our minds, ethics, and consciousness. Nonetheless, the book is unconventional as it focuses on failures of past AI programs rather than on AI success stories. The author also indicates the possible pathways to develop new, (...) more efficient AI paradigms. The short technical section at the end of the book offers more in-depth information on topics like Prolog, Bayesian, and deep neural networks. (shrink)

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. (shrink)

We are currently witnessing the emergence of a ‘third culture’, driven by unprecedented developments that are changing the playing field. These include advances in AI, big data analysis and robotics. The traditional ‘two cultures’ view (S. P. Snow) distinguishes between the sciences and the humanities. The wisdoms these two cultures offer are separated from each other, with little to no interaction or mutual comprehension. However, over the past two decades, and for the first time in human history, a new, third (...) culture has appeared. This new culture, rooted in new technologies, not only pursues its own form of rationality but also supports advances in the original two cultures, deepening and expanding our individual and collective consciousness so that we can see more and do better. It will eventually give rise to new forms of consciousness based not on biochemical signals, but on copper wires and lithium chips. These new machine intelligences will change the world and force us to realise: we are no longer alone. The human species’ position in the twenty-first century will be fundamentally redefined: not as a conductor leading the orchestra, but a single string player within it. (shrink)

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. (shrink)

We should eventually understand how exactly first person phenomenal consciousness is generated. When we do, we should be able to enginner one for robots. This is the engineering thesis in machine consciousness.

Every scientific theory is a simulacrum of reality, every written story a simulacrum of the canon, and every conceptualization of a subjective perspective a simulacrum of the consciousness behind it—but is there a shared essence to these simulacra? The pursuit of answering seemingly disparate fundamental questions across different disciplines may ultimately converge into a single solution: a single ontological answer underlying grand unified theory, hard problem of consciousness, and the foundation of mathematics. I provide a hypothesis, a speculative (...) approximation, supported by a comprehensive overview of scientific evidence and philosophical literature, of a unified epistemic and phenomenological model and, in doing so, propose a parsimonious solution to the hard problem of consciousness. -/- The proposition of the hypothesis bears important implications for cross-disciplinary study between linguistics, mathematics, physics, and computer science, and offers new epistemic, ontological, and ethical propositions about the nature of AI consciousness, as well as existential risk mitigation. (shrink)

Intellectual property (IP) offices and courts around the world are debating whether machines are similar enough to humans in terms of their consciousness and creativity to be eligible for inventors...

The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle.As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. (...) Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible. (shrink)

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.

Over the last three decades, the rise of embodied cognition (EC) articulated in various schools (or versions) of embodied, embedded, extended and enacted cognition (Gallagher’s 4E) has offered AI a way out of traditional computationalism—an approach (or an understanding) loosely referred to as embodied AI. This view has split into various branches ranging from a weak form on the brink of functionalism (loosely represented by Clarks’ parity principle) to a strong form (often corresponding to autopoietic-friendly enactivism) suggesting that body−world interactions (...) constitute cognition. From an ontological perspective, however, constitution is a problematic notion with no obvious empirical or technical advantages. This paper discusses the ontological issues of these two approaches in regard to embodied AI and its ontological commitments: circularity, epiphenomenalism, mentalism, and disguised dualism. The paper also outlines an even more radical approach that may offer some ontological advantages. The new approach, called the mind-object identity, is then briefly compared with sensorimotor direct realism and with the embodied identity theory. (shrink)

This paper presents the main topics, arguments, and positions in the philosophy of AI at present (excluding ethics). Apart from the basic concepts of intelligence and computation, the main topics of ar-tificial cognition are perception, action, meaning, rational choice, free will, consciousness, and normativity. Through a better understanding of these topics, the philosophy of AI contributes to our understand-ing of the nature, prospects, and value of AI. Furthermore, these topics can be understood more deeply through the discussion of AI; (...) so we suggest that “AI Philosophy” provides a new method for philosophy. (shrink)

This is a commentary on Andrea Lavazza and Murilo Vilaça's article "Human Extinction and AI: What We Can Learn from the Ultimate Threat" (Lavazza & Vilaça, 2024). I discuss the potential concern that their proposal to create artificial successors to "insure" against the tragedy of human extinction might mean being too quick to accept that catastrophic prospect as inevitable, rather than single-mindedly focusing on avoiding it. I also consider the question of the value that we might reasonably assign to such (...) a future of artificial successors under the assumption that they do not enjoy phenomenal consciousness. (shrink)

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. (shrink)

From Fall 2016 to Fall 2019 Marcelo Gleiser conducted a series of nine public dialogues between eminent scientists and humanists on challenging topics and ideas whose very definitions and meanings are disputed. Sponsored by the Institute for Cross-Disciplinary Engagement at Dartmouth College, founded by Gleiser, these events were held in theaters and universities across the US and immediately followed by workshops, open to the public, at which attendees could converse directly with participants. Great Minds Don't Think Alike collects edited versions (...) of these discussions, which set an example, in a time when public discourse is seriously threatened, of how people can engage in a fruitful exchange of ideas even when they strongly disagree. The cast of characters is stellar: David Chalmers and Antonio Damasio on consciousness, Sean Carroll and Alan Wallace on reality, Patricia Churchland and Jill Tarter on the future of intelligence, Rebecca Goldstein and Alan Lightman on faith, Jimena Canales and Paul Davies on time, Ed Boyden and Mark O'Connell on transhumanism, Elizabeth Kolbert and Siddhartha Mukherjee on immortality, and Jeremy DeSilva, David Grinspoon, and Tasneem Zehra Husain on being human. (shrink)

In the past few years, the subject of AI rights—the thesis that AIs, robots, and other artefacts (hereafter, simply ‘AIs’) ought to be included in the sphere of moral concern—has started to receive serious attention from scholars. In this paper, I argue that the AI rights research program is beset by an epistemic problem that threatens to impede its progress—namely, a lack of a solution to the ‘Hard Problem’ of consciousness: the problem of explaining why certain brain states give (...) rise to experience. To motivate this claim, I consider three ways in which to ground AI rights—namely: superintelligence, empathy, and a capacity for consciousness. I argue that appeals to superintelligence and empathy are problematic, and that consciousness should be our central focus, as in the case of animal rights. However, I also argue that AI rights is disanalogous from animal rights in an important respect: animal rights can proceed without a solution to the ‘Hard Problem’ of consciousness. Not so with AI rights, I argue. There we cannot make the same kinds of assumptions that we do about animal consciousness, since we still do not understand why brain states give rise to conscious mental states in humans. (shrink)

Simion and Kelp defend a non-anthropocentric account of trustworthy AI, based on the idea that the obligations of AI systems should be sourced in purely functional norms. In this commentary, I highlight some pressing counterexamples to their account, involving AI systems that reliably fulfil their functions but are untrustworthy because those functions are antagonistic to the interests of the trustor. Instead, I outline an alternative account, based on the idea that AI systems should not be considered primarily as tools but (...) as technological participants in social practices. Specifically, I propose to source the obligations of an AI system in the norms that should govern the role it plays within the social practices it participates in, taking into account any changes to the social practices that its participation may bring about. This proposal is anthropocentric insofar as it ascribes obligations to AI systems that are similar to those of human participants in social practices, but only modestly so, as it does not require trustworthy AI to have contentious anthropomorphic capacities (e.g. for consciousness or moral responsibility). (shrink)

We have various everyday measures for identifying the presence of consciousness, such as the capacity for verbal report and the intentional control of behavior. However, there are many contexts in which these measures are difficult to apply, and even when they can be applied one might have doubts as to their validity in determining the presence/absence of consciousness. Everyday measures for identifying consciousness are particularly problematic when it comes to ‘challenging cases’—human infants, people with brain damage, nonhuman (...) animals, and AI systems. There is a pressing need to identify measures of consciousness that can be applied to challenging cases. This paper explores one of the most promising strategies for identifying and validating such measures—the natural-kind strategy. The paper is in two broad parts. Part I introduces the natural-kind strategy, and contrasts it with other influential approaches in the field. Part II considers a number of objections to the approach, arguing that none succeeds. (shrink)

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. (shrink)

In AI, consciousness of self consists in a program having certain kinds of facts about its own mental processes and state of mind. We discuss what consciousness of its own mental structures a robot will need in order to operate in the common sense world and accomplish the tasks humans will give it. It's quite a lot. Many features of human consciousness will be wanted, some will not, and some abilities not possessed by humans have already been (...) found feasible and useful in limited contexts. We give preliminary fragments of a logical language a robot can use to represent information about its own state of mind. A robot will often have to conclude that it cannot decide a question on the basis of the information in memory and therefore must seek information externally. Gödel's idea of relative consistency is used to formalize non-knowledge. Programs with the kind of consciousness discussed in this article do not yet exist, although programs with some components of it exist. Thinking about consciousness with a view to designing it provides a new approach to some of the problems of consciousness studied by philosophers. One advantage is that it focusses on the aspects of consciousness important for intelligent behavior. (shrink)

The relationship between philosophy and research on artificial intelligence (AI) has been difficult since its beginning, with mutual misunderstanding and sometimes even hostility. By contrast, we show how an approach informed by both philosophy and AI can be productive. After reviewing some popular frameworks for computation and learning, we apply the AI methodology of “build it and see” to tackle the philosophical and psychological problem of characterizing perception as distinct from sensation. Our model comprises a network of very simple, but (...) interacting agents which have binary experiences of the “yes/no”-type and communicate their experiences with each other. When does such a network refer to a single agent instead of a distributed network of entities? We apply machine learning techniques to address the following related questions: i) how can the model explain stability of compound entities, and ii) how could the model implement a single task such as perceptual inference? We thereby find consistency with previous work on “interface” strategies from perception research. While this reflects some necessary conditions for the ascription of agency, we suggest that it is not sufficient. Here, AI research, if it is intended to contribute to conceptual understanding, would benefit from issues previously raised by philosophy. We thus conclude the article with a discussion of action-selection, the role of embodiment, and consciousness to make this more explicit. We conjecture that a combination of AI research and philosophy allows general principles of mind and being to emerge from a “quasi-empirical” investigation. (shrink)

It is most likely for anyone to ask himself at least once if it would be possible to live in a dream? Questioning the fabric of “reality” we live in consciously was one of the main doubts man ever had. It is so likely for us to answer positive to it due to so many factors; starting from the many and various facets of reality each individual envision the world, from the enormous differences we all have while perceiving and defining (...) the reality, etc. That is why, at the conscious level, life seems almost like a dream in a dream, always hoping to wake up from the negative, unwanted version of it. That is why my assertion here, based on latest theories on consciousness and AI, aim to say that we live in between reality and dream, being “conscious” of ourselves, but not really wanting to be “aware” of what is really going on with us. (shrink)

It is most likely for anyone to ask himself at least once if it would be possible to live in a dream? Questioning the fabric of “reality” we live in consciously was one of the main doubts man ever had. It is so likely for us to answer positively to it due to so many factors; starting from the many and various facets of reality each individual envision the world, from the enormous differences we all have while perceiving and defining (...) the reality, etc. That is why, at the conscious level, life seems almost like a dream in a dream, always hoping to wake up from the negative, unwanted version of it. That is why my assertion here, based on latest theories on consciousness and AI, aim to say that we live in between reality and dream, being “conscious” of ourselves, but not really wanting to be “aware” of what is really going on with us. Living as a human is not a path towards improvement in the way of getting rid of subjectiveness and valorization because these so-called errors make the most of human living. (shrink)

This article looks at the broadest implications of public acceptance of AI. A distinction is drawn between “conscious” belief in a technology, and “organic” belief where the technology is incorporated into an unconscious world model. The extent to which we feel threatened by AI's apparent denial of “spirit” is considered, along with a discussion of how people react to this threat. It is proposed that organic acceptance of AI models would lead to a rebirth of popular spiritual concepts as paradoxical (...) as the “New Age” ideas that have their roots in the theories of physics. Finally the relevance of this speculation is discussed in terms of how it could impinge upon public acceptability of AI technology. (shrink)

Human extinction is something generally deemed as undesirable, although some scholars view it as a potential solution to the problems of the Earth since it would reduce the moral evil and the suffering that are brought about by humans. We contend that humans collectively have absolute intrinsic value as sentient, conscious and rational entities, and we should preserve them from extinction. However, severe threats, such as climate change and incurable viruses, might push humanity to the brink of extinction. Should that (...) occur, it might be useful to envision a successor to humans able to preserve and hand down its value. One option would be to resort to humanoid robots that reproduce our salient characteristics by imitation, thanks to AI powered by machine learning. However, the question would arise of how to select the characteristics needed for our successors to thrive. This could prove to be particularly challenging. A way out might come from an algorithm entrusted with this choice. In fact, an algorithmic selection both at the social and at the individual level could be a preferred choice than other traditional ways of making decisions. In this sense, reflecting on human extinction helps us to identify solutions that are also suitable for the problems we face today. (shrink)

From one of the world's leading neuroscientists--a succinct, illuminating, wholly engaging investigation of the phenomenon of consciousness. In recent decades, many philosophers and cognitive scientists have declared the question of consciousness unsolvable, but Antonio Damasio is convinced that recent findings in neurobiology, psychology, and AI have given us the necessary tools to solve its mystery. Now, he not only elucidates its myriad aspects, but presents his analysis and insights in a way that is faithful to our own intuitive (...) sense of the experience of consciousness. In the 45 brief chapters of the book, he helps us understand the relation between consciousness and mind; why being conscious is not the same as either being awake or sensing; the essential role of feeling; and the biological brain and development of consciousness. He synthesizes the recent findings of various sciences with the outlook of philosophy, and, most significantly, presents his original research which has transformed our understanding of the brain and human behavior. Here is an indispensable guide to understanding consciousness, the fundamental human capacity for informing--and transforming--our experience of the world around us and our perception of our place in it. (shrink)

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. (shrink)

*[[I wrote this paper in January of 1990, but did not publish it because I was never entirely happy with it. My ideas on consciousness were in a state of flux, ultimately evolving into those represented in my book _The Conscious Mind_ (Oxford University Press, 1996). I now think that some parts of this paper are unsatisfactory, especially the positive theory outlined at the end, although a successor to that theory is laid out in the book. Nevertheless, I think (...) the paper raises issues that need to be addressed. ]]. (shrink)

Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.

This paper offers a "tu quoque" defense of strong AI, based on the argument that phenomena of self-consciousness and intentionality are nothing but the "negative space" drawn around the concrete phenomena of brain states and causally connected utterances and objects. Any machine that was capable of concretely implementing the positive phenomena would automatically inherit the negative space around these that we call self-consciousness and intention. Because this paper was written for a literary audience, some examples from Greek tragedy, (...) noir fiction, science fiction and Dada are deployed to illustrate the view. (shrink)