International Journal of Machine Consciousness, Volume 06, Issue 02, Page 141-161, December 2014. This paper follows directly from an earlier paper where we discussed the requirements for an artifact to be a moral agent and concluded that the artifactual question is ultimately a red herring. As before, we take moral agency to be that condition in which an agent can appropriately be held responsible for her actions and their consequences. We set a number of stringent conditions on moral agency. A (...) moral agent must be embedded in a cultural and specifically moral context and embodied in a suitable physical form. It must be, in some substantive sense, alive. It must exhibit self-conscious awareness. It must exhibit sophisticated conceptual abilities, going well beyond what the likely majority of conceptual agents possess: not least that it must possess a well-developed moral space of reasons. Finally, it must be able to communicate its moral agency through some system of signs: A "private" moral world is not enough. After reviewing these conditions and pouring cold water on recent claims for having achieved "minimal" machine consciousness, we turn our attention to a number of existing and, in some cases, commonplace artifacts that lack moral agency yet nevertheless require one to take a moral stance toward them, as if they were moral agents. Finally, we address another class of agents raising a related set of issues: autonomous military robots. (shrink)

The comment addresses central issues of a "theory theory" approach as exemplified in Gopnik' and Goldman's BBS-articles. Gopnik, on the one hand, tries to demonstrate that empirical evidence from developmental psychology supports the view of a "theory theory" in which common sense beliefs are constructed to explain ourselves and others. Focusing the informational processing routes possibly involved we would like to argue that his main thesis (e.g. idea of intentionality as a cognitive construct) lacks support at least for two reasons: (...) one methodological and one structural. On the other hand, Goldman raises an important question when he is asking how people ascribe mental states to themselves. Reasons why Goldman's attempt to understand common sense mental representations by using an analogy from visual perception is problematic are discussed. The role which is attributed to a phenomenology is evaluated. (shrink)

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

v. 1. Foundations -- v. 2. The mind-body problem -- v. 3. Intentionality -- v. 4. Consciousness.

We evaluate the role of embodiment in ordinary mental state ascriptions. Presented are five experiments on phenomenal state ascriptions to disembodied entities such as ghosts and spirits. Results suggest that biological embodiment is not a central principle of folk psychology guiding ascriptions of phenomenal consciousness. By contrast, results continue to support the important role of functional considerations in theory of mind judgments.

The claim has often been made that passing the Turing Test would not be sufficient to prove that a computer program was intelligent because a trivial program could do it, namely, the “Humongous-Table (HT) Program”, which simply looks up in a table what to say next. This claim is examined in detail. Three ground rules are argued for: (1) That the HT program must be exhaustive, and not be based on some vaguely imagined set of tricks. (2) That the HT (...) program must not be created by some set of sentient beings enacting responses to all possible inputs. (3) That in the current state of cognitive science it must be an open possibility that a computational model of the human mind will be developed that accounts for at least its nonphenomenological properties. Given ground rule 3, the HT program could simply be an “optimized” version of some computational model of a mind, created via the automatic application of program-transformation rules [thus satisfying ground rule 2]. Therefore, whatever mental states one would be willing to impute to an ordinary computational model of the human psyche one should be willing to grant to the optimized version as well. Hence no one could dismiss out of hand the possibility that the HT program was intelligent. This conclusion is important because the Humongous-Table Program Argument is the only argument ever marshalled against the sufficiency of the Turing Test, if we exclude arguments that cognitive science is simply not possible. (shrink)

Some of the papers in this special issue distribute cognition between what is going on inside individual cognizers' heads and their outside worlds; others distribute cognition among different individual cognizers. Turing's criterion for cognition was individual, autonomous input/output capacity. It is not clear that distributed cognition could pass the Turing Test.

A core commitment of Bob Hale and Crispin Wright’s neologicism is their invocation of Frege’s Constraint—roughly, the requirement that the core empirical applications for a class of numbers be “built directly into” their formal characterization. According to these neologicists, if legitimate, Frege’s Constraint adjudicates in favor of their preferred foundation—Hume’s Principle—and against alternatives, such as the Dedekind–Peano axioms. In this paper, we consider a recent argument for legitimating Frege’s Constraint due to Hale, according to which the primary empirical application of (...) the naturals is transitive counting, or answering ‘how many’-questions using numerals. We make two claims regarding Hale’s argument. First, it fails to legitimate Frege’s Constraint in virtue of resting on unsupported and highly contentious assumptions. Secondly, even if sound, Hale’s argument would vindicate a version of Frege’s Constraint which fails to adjudicate in favor of Hume’s Principle over alternative characterizations of the naturals. (shrink)

Searle’s discussions over the years 1980-2004 of the implications of his “Chinese Room” Gedanken experiment are frustrating because they proceed from a correct assertion: “Instantiating a computer program is never by itself a sufficient condition of intentionality;” and an incorrect assertion: “The explanation of how the brain produces intentionality cannot be that it does it by instantiating a computer program.” In this article, I describe how to construct a Gedanken zombie Chinese Room program that will pass the Turing test and (...) at the same time unambiguously demonstrates the correctness of. I then describe how to construct a Gedanken Chinese brain program that will pass the Turing test, has a mind, and understands Chinese, thus demonstrating that is incorrect. Searle’s instantiation of this program can and does produce intentionality. Searle’s longstanding ignorance of Chinese is simply irrelevant and always has been. I propose a truce and a plan for further exploration. (shrink)

This section aims to summarize and conclude Part I in the form of a taxonomy of legitimate and illegitimate corporate moral responsibility attributions. I believe we can categorise four types of corporate moral responsibility attributions two of which are legitimate and two which are illegitimate with regard to our concept of moral agency and our moral intuition of fairness.

This is the most comprehensive book ever published on philosophical methodology. A team of thirty-eight of the world's leading philosophers present original essays on various aspects of how philosophy should be and is done. The first part is devoted to broad traditions and approaches to philosophical methodology. The entries in the second part address topics in philosophical methodology, such as intuitions, conceptual analysis, and transcendental arguments. The third part of the book is devoted to essays about the interconnections between philosophy (...) and neighbouring fields, including those of mathematics, psychology, literature and film, and neuroscience. (shrink)

Machine learning, and more broadly artificial intelligence (AI), is a fascinating technology and can be considered as the closest approximation to the Cartesian “thinking thing” that humans have ever created. Just as the industrial revolution required a new ethos, the age of intelligent machines will create its own, challenging the established moral, economic, and political presuppositions. This paper discusses the relationship between AI and society; it presents several thought experiments to explore the complexity of the relationship and highlights the insufficiency (...) of the current normative paradigm in addressing technological expansion. I argue that many of the externalities, such as security risks, loss of privacy, and economic instability will result from trying to fit the emerging technologies into the existing frame of efficiency and utility, by redefining the notions of human value, identity, autonomy, purity, and truth, among others. The age of the intelligent machine is elevating alienation to new levels, treating the individual as mere patterns in data—its primary commodity. I further argue that while the possibility of unintended consequences, due to the potential misuse of AI is ever present, the intelligent machine per se is unlikely to engage in a zero-sum game for power on its own initiative. I question whether singularity is at all attainable and argue that technology will forever remain a proxy for human interests. I conclude by posing questions for charting the path forward. Through this analysis, I aim to provide a more nuanced understanding of the complex relationship between the AI and humans. (shrink)

How all philosophical explanations of human consciousness and the fundamental structure of the cosmos are bizarre—and why that’s a good thing Do we live inside a simulated reality or a pocket universe embedded in a larger structure about which we know virtually nothing? Is consciousness a purely physical matter, or might it require something extra, something nonphysical? According to the philosopher Eric Schwitzgebel, it’s hard to say. In The Weirdness of the World, Schwitzgebel argues that the answers to these fundamental (...) questions lie beyond our powers of comprehension. We can be certain only that the truth—whatever it is—is weird. Philosophy, he proposes, can aim to open—to reveal possibilities we had not previously appreciated—or to close, to narrow down to the one correct theory of the phenomenon in question. Schwitzgebel argues for a philosophy that opens. According to Schwitzgebel’s “Universal Bizarreness” thesis, every possible theory of the relation of mind and cosmos defies common sense. According to his complementary “Universal Dubiety” thesis, no general theory of the relationship between mind and cosmos compels rational belief. Might the United States be a conscious organism—a conscious group mind with approximately the intelligence of a rabbit? Might virtually every action we perform cause virtually every possible type of future event, echoing down through the infinite future of an infinite universe? What, if anything, is it like to be a garden snail? Schwitzgebel makes a persuasive case for the thrill of considering the most bizarre philosophical possibilities. (shrink)

Modern biology has not yet come to terms with the presence of many organic codes in Nature, despite the fact that we can prove their existence. As a result, it has not yet accepted the idea that the great events of macroevolution were associated with the origin of new organic codes, despite the fact that this is the most parsimonious and logical explanation of those events. This is probably due to the fact that the existence of organic codes in all (...) fundamental processes of life, and in all major transitions in the history of life, has enormous theoretical implications. It requires nothing less than a new theoretical framework, and that kind of change is inevitably slow. There are too many facts to reconsider, too many bits of history to weave together in a new mosaic. But this is what science is about, and the purpose of the present paper is to show that it can be done. More precisely, it is shown that the whole natural history of the brain can be revisited in the light of the organic codes. What is described here is only a bird’s-eye view of brain macroevolution, but it is hoped that the extraordinary potential of the organic codes can nevertheless come through. The paper contains also another message. The organic codes prove that life is based on semiosis, and are in fact the components of organic semiosis, the first and the most diffused form of semiosis on Earth, but not the only one. It will be shown that the evolution of the brain was accompanied by the development of two new types of sign processes. More precisely, it gave origin first to interpretive semiosis, mostly in vertebrates, and then to cultural semiosis, in our species. (shrink)

Explores the relationship between technics and humanity, tracing the emergence of a bio-technical conception of existence in contemporary continental philosophy.

A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.

Why should moral philosophers, moral psychologists, and machine ethicists care about computational complexity? Debates on whether artificial intelligence (AI) can or should be used to solve problems in ethical domains have mainly been driven by what AI can or cannot do in terms of human capacities. In this paper, we tackle the problem from the other end by exploring what kind of moral machines are possible based on what computational systems can or cannot do. To do so, we analyze normative (...) ethics through the lens of computational complexity. First, we introduce computational complexity for the uninitiated reader and discuss how the complexity of ethical problems can be framed within Marr’s three levels of analysis. We then study a range of ethical problems based on consequentialism, deontology, and virtue ethics, with the aim of elucidating the complexity associated with the problems themselves (e.g., due to combinatorics, uncertainty, strategic dynamics), the computational methods employed (e.g., probability, logic, learning), and the available resources (e.g., time, knowledge, learning). The results indicate that most problems the normative frameworks pose lead to tractability issues in every category analyzed. Our investigation also provides several insights about the computational nature of normative ethics, including the differences between rule- and outcome-based moral strategies, and the implementation-variance with regard to moral resources. We then discuss the consequences complexity results have for the prospect of moral machines in virtue of the trade-off between optimality and efficiency. Finally, we elucidate how computational complexity can be used to inform both philosophical and cognitive-psychological research on human morality by advancing the moral tractability thesis. (shrink)

The emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical, aesthetic, epistemological and legal frameworks we have so far used to categorise art. To begin tackling these issues and identifying a role for AI in the production and protection of human artwork, it is necessary to take a multidisciplinary approach which considers current legal precedents, (...) the practice of software engineering, historical attitudes towards technological innovation and a sustained technical analysis of the models themselves. This paper queries the location and nature of substantive artistic work in the developmental stages of an AI-generated image, offering critiques of existing assumptions and posing questions for future research. The emergence of convincing AI creative output, artistic or literary, has significant long-term implications for the humanities, including the need for re-appraisal of foundational ideas about authorship and creativity in general. The effects of artificial intelligence, whether generalised or task-specific, cannot be ignored or displaced now that easy-access, scalable image and text production is a reality. (shrink)

In this essay we critically evaluate the progress that has been made in solving the problem of meaning in artificial intelligence (AI) and robotics. We remain skeptical about solutions based on deep neural networks and cognitive robotics, which in our opinion do not fundamentally address the problem. We agree with the enactive approach to cognitive science that things appear as intrinsically meaningful for living beings because of their precarious existence as adaptive autopoietic individuals. But this approach inherits the problem of (...) failing to account for how meaning as such could make a difference for an agent’s behavior. In a nutshell, if life and mind are identified with physically deterministic phenomena, then there is no conceptual room for meaning to play a role in its own right. We argue that this impotence of meaning can be addressed by revising the concept of nature such that the macroscopic scale of the living can be characterized by physical indeterminacy. We consider the implications of this revision of the mind-body relationship for synthetic approaches. (shrink)

The book is addressed to all readers interested in cognitive science, and especially in research combining a logical analysis with psychological, linguistic and neurobiological approaches. The publication is the result of a collaboration between the Department of Cognitive Science at University of Lodz and the Department of Cognitive Science at Lund University. It is intended to provide a comprehensive presentation of the key research issues undertaken in both Departments, including considerations on meaning, natural language and reasoning, linguistic as well as (...) numerical competence, the theory of decision making, modelling of conceptual representations, cognitive and game theoretic approach to social interactions. (shrink)

Штучний інтелект — це комп’ютерна система, яка мислить або діє як людина. Особливості ШІ втілюють імпліцитні уявлення його розробників про природу людини. «Сильний» ШІ, який має загальні коґнітивні здатності дорослої людини, досі не створено, натомість «слабкі» ШІ вже є частиною планетарної обчислювальної інфраструктури. Нейронно-мережеві ШІ імі- тують специфічні типи людської поведінки, узагальнюючи дані про повсякденне життя ко- ристувачів. Такий підхід у створенні ШІ відповідає філософському мейнстріму ХХ сторіччя, коли повсякденне життя розглядали як джерело мовних та соціальних наперед-даностей, що забезпечують порозуміння. (...) Також цей підхід спирається на класичну дихотомію «людина— машина» й відповідне уявлення, що людська природа є стабільною та незалежною від техно- логічного стану. Проте у постметафізичну добу, коли взаємодія людини з технікою є комуні- кативною, а не інструментальною, дані про людський побут не можуть бути незалежним зразком людськості. ШІ-застосунки не лише кодифікують дескриптивні аспекти людської природи, а й дисциплінують своїх користувачів, адже цифрове середовище, в якому можуть бути зібрані дані про повсякдення, уже впорядковане за допомогою ШІ. Відповідно, у цифро- во му середовищі люди змушені відтворювати нові норми поведінки, кодифіковані за допомо- гою ШІ, який є одним із способів видозміни людської природи самою людиною. Вплив ШІ непомітний, позаяк цифрове середовище, в якому люди взаємодіють з ШІ, організовано не- достат ньо зрозумілим для користувачів чином. Антропотехнологічний характер ШІ є по бічним наслідком розвитку платформ, тому творці ШІ не перебирають на себе відповідальність за вті лені в їхніх розробках норми. (shrink)

Deep learning and other similar machine learning techniques have a huge advantage over other AI methods: they do function when applied to real-world data, ideally from scratch, without human intervention. However, they have several shortcomings that mere quantitative progress is unlikely to overcome. The paper analyses these shortcomings as resulting from the type of compression achieved by these techniques, which is limited to statistical compression. Two directions for qualitative improvement, inspired by comparison with cognitive processes, are proposed here, in the (...) form of two mechanisms: complexity drop and contrast. These mechanisms are supposed to operate dynamically and not through pre-processing as in neural networks. Their introduction may bring the functioning of AI away from mere reflex and closer to reflection. (shrink)

To the age-old debate over what it means to be human, the relatively new fields of sociobiology and artificial intelligence bring new, if not necessarily compatible, insights. What have these two fields in common? Have they affected the way we define humanity? These and other timely questions are addressed with colorful individuality by the authors of _The Boundaries of Humanity_. Leading researchers in both sociobiology and artificial intelligence combine their reflections with those of philosophers, historians, and social scientists, while the (...) editors explore the historical and contemporary contexts of the debate in their introductions. The implications of their individual arguments, and the often heated controversies generated by biological determinism or by mechanical models of mind, go to the heart of contemporary scientific, philosophical, and humanistic studies. (shrink)

Theories of epistemology make reference—via the perspective of an observer—to the structure of information transfer, which generates reality, of which the observer himself forms a part. It can be shown that any epistemological approach which implies the participation of tautological structural elements in the information transfer necessarily leads to an antinomy. Nevertheless, since the time of Aristotle the paradigm of mathematics—and thus tautological structure—has always been a hidden ingredient in the various concepts of knowledge acquisition or general theories of information (...) transfer. We hold that Darwin’s Evolutionary Theory is the first scientific theory which consistently presupposes a non-tautological structure for the information transfer and, at the same time, keeps it strictly distinct from the tautological metric of scientific observation. The consequences of this technique—namely the dissociation of information from intentionality—have not yet been fully drawn. (shrink)

In the novel Die Automate (Hoffmann, 1957 ed.), the German writer Ernst Theodor Amadeus Hoffmann (1776-1822) describes different kinds of musical automatons which play music with expression and musicality. The whole novel is based on the effect of the automatic performances on the feelings of the two personages and on the appearance of musical automatons which simulate, with their musical skill and expressiveness, the structures of the knowledge and feelings of human beings.

Floridi’s infosphere consisting of informational reality is estimated and delineated by introducing the new notion of Typ-Ken, an undifferentiated amalgam of type and token that can be expressed as either type or token dependent on contingent ontological commitment. First, we elaborate Floridi’s system, level of abstraction (LoA), model, and structure scheme, which is proposed to reconcile ontic with epistemic structural reality, and obtain the duality of type and token inherited in the relationship between LoA and model. While we focus on (...) the ontological commitment that can negotiate and emphasize the discrepancy between type and token, we show that most research focusing on different hierarchical layers (type and token) has converged onto the flattened perspective of type and token to clarify the role of ontological commitment. We propose the idea of Typ-Ken to avoid this flattening. In addition, we elaborate Taddeo and Floridi’s criticism of approaches to the symbol grounding problem and show that their criticism based on the zero semantical commitment condition is specific to the agents affected by the flattening. We then take bird flocks as a metaphor for the living infosphere as if it had one mind. The knowledge recently yielded by image analysis indicates that it is difficult for previous flock models based on agents equipped with the flattening of local (token) and global (type) to show the special feature of a flock of the scale-free proportion (SFP). We show here that agents based on the Typ-Ken can reveal the SFP, which is the essential characteristic of the living infosphere. In other words, Typ-Ken is an expression for informational reality (LoA and model with ontological commitment) that can reveal seamless local and global interactions in the functioning of a flock or infosphere. (shrink)

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be interpreted. (...) The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

Abstract Curiously missing in the vast literature on Hilary Putnam's so-called model-theoretic argument against semantic realism is any response from would-be proponents of what Putnam would call magical theories of reference. Such silence is surprising in light of the fact that such theories have occupied a significant position in the history of philosophy and the fact that there are still several prominent thinkers who would, no doubt, favor such a theory. This paper develops and examines various responses to Putnam's argument (...) on behalf of the proponent of a magical theory of reference. While Putnam's explicit replies to such responses to his argument seem to involve little more than name calling, I develop arguments that show that there are significant problems facing any would-be proponent of such a view. While magical theories of reference are far from the strawmen Putnam seems to take them to be, there are, I argue, genuine reasons for a semantic realist to prefer a non-magical theory of reference. (shrink)

Cognitive science is an interdisciplinary research endeavor focusing on human cognitive phenomena such as memory, language use, and reasoning. It emerged in the second half of the 20th century and is charting new directions at the beginning of the 21st century. This chapter begins by identifying the disciplines that contribute to cognitive science and reviewing the history of the interdisciplinary engagements that characterize it. The second section examines the role that mechanistic explanation plays in cognitive science, while the third focuses (...) on the importance of mental representations in specifically cognitive explanations. The fourth section considers the interdisciplinary nature of cognitive science and explores how multiple disciplines can contribute to explanations that exceed what any single discipline might accomplish. The conclusion sketches some recent developments in cognitive science and their implications for philosophers. (shrink)

From Plato to the present, philosophers have relied on intuitive judgments as evidence for or against philosophical theories. Most philosophers are WEIRD, highly educated, and male. The literature reviewed in the target article suggests that such people might have intuitions that differ from those of people in other groups. There is a growing body of evidence suggesting that they do.

Abstract It is widely assumed that the meaning of at least some types of expressions involves more than their reference to objects, and hence that there may be co-referential expressions which differ in meaning. It is also widely assumed that ?syntax does not suffice for semantics?, i.e. that we cannot account for the fact that expressions have semantic properties in purely syntactical or computational terms. The main goal of the paper is to argue against a third related assumption, namely that (...) what is responsible for a difference in meaning between co-referential expressions is the computational difference in the cognitive functioning of the expressions. ?Intentional aspects? of expressions?those features which their meanings involve in addition to reference?cannot be syntacticized, since they are individuated not in terms of any cognitive feature, but rather in terms of those properties of the referents through which the expressions refer to them, and cognitive features cannot determine such properties in exactly the same sense as they cannot determine reference. (shrink)

Abstract In this paper, I argue that the traditional philosophical approach of taking cognitively and emotionally competent adult people to be the prototypical instances of agency should be revised in light of current work in the behavioral sciences. Logical consistency in application is better served by taking simple goal-directed and feedback-governed systems such as insects as the prototypes of the concept of agency, with people being agents ?by extension? in the same sense as countries or corporations.

The book provides an overview of the contemporary discussion of the mind-body problem. This discussion takes its modern form during the 17th century in the works of René Descartes. The book covers the most important points of view in modern philosophy of mind. An important thesis of the book is that contemporary debates are still heavily influenced by Descartes’ arguments, especially those related to the nature of consciousness. (Google translate).

Can autonomous systems replace humans in the performance of their activities? How does the answer to this question inform the design of autonomous systems? The study of technical systems and their features should be preceded by the study of the activities in which they play roles. Each activity can be described by its overall goals, governing norms and the intermediate steps which are taken to achieve the goals and to follow the norms. This paper uses the activity realist approach to (...) conceptualize autonomous systems in the context of human activities. By doing so, it first argues for epistemic and logical conditions that illustrate the limitations of autonomous systems in tasks which they can and cannot perform, and then, it discusses the ramifications of the limitations of system autonomy on the design of autonomous systems. (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 paper surveys historical and recent philosophical discussions of the relations between imagination and creativity. In the first two sections, it covers two insufficiently studied analyses of the creative imagination, that of Kant and Sartre, respectively. The next section discusses imagination and its role in scientific discovery, with particular emphasis on the writings of Michael Polanyi, and on thought experiments and experimental design. The final section offers a brief discussion of some very recent work done on conceptual relations between imagination (...) and creativity. (shrink)

Could a sufficiently detailed computer simulation of consciousness replicate consciousness? In other words, is performing the right computations sufficient for artificial consciousness? Or will there remain a difference between simulating and being a conscious system, because the right computations must be implemented in the right way? From the perspective of Karl Friston's free energy principle, self-organising systems (such as living organisms) share a set of properties that could be realised in artificial systems, but are not instantiated by computers with a (...) classical (von Neumann) architecture. I argue that at least one of these properties, viz. a certain kind of causal flow, can be used to draw a distinction between systems that merely simulate, and those that actually replicate consciousness. Since this property is instantiated by all systems that conform to the free energy principle (not just conscious beings), the account on offer here can be extended to draw a distinction between simulating and being a certain type of system, more generally. In particular, this may inform meta-ethical accounts of artificial moral status and artificial moral agency. (shrink)

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

To controlforceaccurately under a wide range of behavioral conditions, the central nervous system would either require a detailed, continuously updated representation of the state of each muscle (and the load against which each is acting) or else force feedback with sufficient gain to cope with variations in the properties of the muscles and loads. The evidence for force feedback with adequate gain or for an appropriate central representation is not sufficient to conclude that force is the major controlled variable in (...) normal limb movements.Morton's hypothesis, thatlengthis controlled by a follow-up servo, has a number of difficulties related to the delays, gains, variability, and specificity in feedback pathways comprising potential servo loops. However, experimental evidence is consistent with these pathways providing servo assistance for some movements produced by coactivation of α- and static γ-motoneurons. Dynamic γ-motoneurons may provide an additional input for adaptive control of different types of movements.The idea that feedback is used to compensate for changes in musclestiffnesshas received experimental support under static postural conditions. However, reflexes tend to increase rather than decrease the range of variation in muscle stiffness during some cyclic movements. Theoretical problems associated with the regulation of stiffness are also discussed. The possibilities of separate control systems forvelocityorviscosityare considered, but the evidence is either negative or lacking. I conclude that different physical variables can be controlled depending on the type of limb movement required. The concept of stiffness regulation is also useful under some conditions, but should probably be extended to the regulation of the visco-elastic properties (i.e., the mechanical impedance) of a muscle or joint. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models.Higher-level analyses of these connectionist models reveal subtle relations to symbolic models. Parallel connectionist memory and linguistic processes are hypothesized to give rise to processes that are describable at a higher level as sequential rule application. At the lower level, computation has the character of massively parallel satisfaction of soft numerical constraints; at the higher level, this can lead to competence characterizable by hard rules. Performance will typically deviate from this competence since behavior is achieved not by interpreting hard rules but by satisfying soft constraints. The result is a picture in which traditional and connectionist theoretical constructs collaborate intimately to provide an understanding of cognition. (shrink)