In a paper in this journal, Neil Levy challenges Nicholas Agar’s argument for the irrationality of mind-uploading. Mind-uploading is a futuristic process that involves scanning brains and recording relevant information which is then transferred into a computer. Its advocates suppose that mind-uploading transfers both human minds and identities from biological brains into computers. According to Agar’s original argument, mind-uploading is prudentially irrational. Success relies on the soundness of the program of Strong AI—the view that it may someday be possible to (...) build a computer that is capable of thought. Strong AI may in fact be false, an eventuality with dire consequences for mind-uploading. Levy argues that Agar’s argument relies on mistakes about the probability of failed mind-uploading and underestimates what is to be gained from successfully mind-uploading. This paper clarifies Agar’s original claims about the likelihood of mind-uploading failure and offers further defense of a pessimistic evaluation of success. (shrink)

This paper offers practical advice about how to interact with machines that we have reason to believe could have minds. I argue that we should approach these interactions by assigning credences to judgements about whether the machines in question can think. We should treat the premises of philosophical arguments about whether these machines can think as offering evidence that may increase or reduce these credences. I describe two cases in which you should refrain from doing as your favored philosophical view (...) about thinking machines suggests. Even if you believe that machines are mindless, you should acknowledge that treating them as if they are mindless risks wronging them. Suppose your considered philosophical view that a machine has a mind leads you to consider dating it. You may have reason to regret that decision should these dates lead on to a life-long relationship with a mindless machine. In the paper’s final section, I suggest that building a machine that is capable of performing all intelligent human behavior should produce a general increase in confidence that machines can think. Any reasonable judge should count this feat as evidence in favor of machines having minds. This rational nudge could lead to broad acceptance of the idea that machines can think. (shrink)

I argue that the Oxford school Everett interpretation is internally incoherent, because we cannot claim that in an Everettian universe the kinds of reasoning we have used to arrive at our beliefs about quantum mechanics would lead us to form true beliefs. I show that in an Everettian context, the experimental evidence that we have available could not provide empirical confirmation for quantum mechanics, and moreover that we would not even be able to establish reference to the theoretical entities of (...) quantum mechanics. I then consider a range of existing Everettian approaches to the probability problem and show that they do not succeed in overcoming this incoherence. (shrink)

Questions about the relationship between linguistic competence and expertise will be examined in the paper. Harry Collins and others distinguish between ubiquitous and esoteric expertise. Collins places considerable weight on the argument that ordinary linguistic competence and related phenomena exhibit a high degree of expertise. His position and ones which share close affinities are methodologically problematic. These difficulties matter because there is continued and systematic disagreement over appropriate methodologies for the empirical study of expertise. Against Collins, it will be argued (...) that the term ‘expertise’ should be reserved for expertise (esoteric experts) and exclude everyday performance (ubiquitous experts). Wittgensteinian ideas will be employed to maintain that it is mistaken and misleading to derive substantive conclusions about the epistemology of expertise from ordinary linguistic competence and vice versa. Significant attention will be devoted to the notion of following a rule with particular reference to the intelligibility of tacit rule following. A satisfactory theoretical approach to expertise should not involve making important claims about ordinary linguistic competence. (shrink)

The extended mind hypothesis (EMH) is the claim that the mind can and does extend beyond the human body. Adams and Aizawa (A&A) contend that arguments for EMH commit a ‘coupling constitution fallacy’. We deny that the master argument for EMH commits such a fallacy. But we think that there is an important question lurking behind A&A's allegation: under what conditions is cognition spread across a tightly coupled system? Building on some suggestions from Haugeland, we contend that the system must (...) exhibit a distinctive sort of semantic activity, semantic activity that the system as a whole takes responsibility for. (shrink)

The extended mind hypothesis (EMH) is the claim that the mind can and does extend beyond the human body. Adams and Aizawa (A&A) contend that arguments for EMH commit a ‘coupling constitution fallacy’. We deny that the master argument for EMH commits such a fallacy. But we think that there is an important question lurking behind A&A's allegation: under what conditions is cognition spread across a tightly coupled system? Building on some suggestions from Haugeland, we contend that the system must (...) exhibit a distinctive sort of semantic activity, semantic activity that the system as a whole takes responsibility for. (shrink)

Over the past decades, due to the course towards digitalization of all areas of life, interest in modeling and creating intelligent systems has increased significantly. However, there are now a stagnation in the industry, a lack of attention to analog and bionic approaches as alternatives to digital, numerous speculations on “neuro” issues for commercial and other purposes, and an increase in social and environmental risks. The article provides an overview of the development of artificial intelligence (AI) conceptions toward increasing the (...) human likeness of machines: from the key ideas of A. Turing and J. von Neumann, who initiated the digitalization of society, to discussions about the definition of AI and the emergence of conceptions of strong and weak AI. Special attention is paid to the approach of A. Sloman, to ideas about the architecture and design of complex artificial systems are considered, which make it possible to “emotionally” expand the idea of weak/strong AI. In the article's section on the necessity and possibility of incorporating emotions into the architecture of AI, the authors reveal the goals and methodological limitations for creating an emotional artificial agent. In addition, the article briefly presents the main principles of the authors' architectural approach to the creation of emotional intellectual systems on the example of the cognitive-affective model of architecture, which allow modeling the impact of emotions on the cognitive processes involved in decision-making processes. The described architectural approach to modeling intelligent systems can be used as a conceptual basis for discussing and formulating a strategy for the development of neurocomputing, philosophy of artificial intelligence, and experimental philosophy, for developing innovative research programs, formulating and solving theoretical and methodological problems. (shrink)

It is usually accepted that deductions are non-informative and monotonic, inductions are informative and nonmonotonic, abductions create hypotheses but are epistemically irrelevant, and both deductions and inductions can’t provide new insights. In this article, I attempt to provide a more cohesive view of the subject with the following hypotheses: (1) the paradigmatic examples of deductions, such as modus ponens and hypothetical syllogism, are not inferential forms, but coherence requirements for inferences; (2) since any reasoner aims to be coherent, any inference (...) must be deductive; (3) a coherent inference is an intuitive process where the premises should be taken as sufficient evidence for the conclusion, which on its turn should be viewed as necessary evidence for the premises in some modal range; (4) inductions, properly understood, are abductions, but there are no abductions beyond the fact that in any inference the conclusion should be regarded as necessary evidence for the premises; (5) monotonicity is not only compatible with the retraction of past inferences given new information, but it is a requirement for it; (6) this explanation of inferences holds true for discovery processes, predictions and trivial inferences. (shrink)

[This is an earlier (1997), much longer and more detailed version of my entry on LOTH in the _Stanford Encyclopedia of Philosophy_] The Language of Thought Hypothesis (LOTH) is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that (...) has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (shrink)

In this paper I argue that, given the way that AI models work and the way that ordinary human rationality works, it is very likely that people are anthropomorphizing AI, with potentially serious consequences. I start with the core idea, recently defended by Thomas Kelly (2022) among others, that bias involves a systematic departure from a genuine standard or norm. I briefly discuss how bias can take on different explicit, implicit, and “truly implicit” (Johnson 2021) forms such as bias by (...) proxy. I then discuss biased anthropomorphism of technology, focusing on the case of Large Language Models (LLMs) like chatGPT. As with other kinds of bias, there are importantly different kinds of anthropomorphism, some of which can persist without others, and some of which can encourage others. Anthropomorphism can take rather subtle, implicit forms, that can be difficult to detect, resist, and dislodge. Attention to these kinds of anthropomorphism can help us avoid confusing importantly different kinds of evaluation, better assess the risks, and inform strategies for bias prevention and mitigation. (shrink)

According to a recent philosophical claim, “works of fiction are thought experiments” (Elgin 2007: 47), though there are relevant differences, as the role of spoilers shows—they can ruin a novel but improve the understanding we can gain through a thought experiment. In the present article I will analyze the role of spoilers and argue for a more differentiated perspective on the relation between literature and thought experiments. I will start with a short discussion of different perspectives on thought experiments and (...) argue that the mental-model view and the conception of games of make-believe are most promising for developing the present analogy. Then I will assess the similarities and differences between thought experiments and other works of fiction. I will focus on the role of spoilers and, more generally, on the foretaste context, of which they are part. This context guides readers of literary works of art to draw their attention to the literary and aesthetic quality of the text. In the case of thought experiments, on the other hand, it (i) prompts them to accept the presence of fictional elements in worldly-cognitive works and (ii) draws their attention towards cognitively relevant elements of the story. A discussion of Borges’ Pierre Menard in the last part will show that literary works of art become thought experiments if they are embedded in an appropriate foretaste context. Spoilers, thus, unveil that even works which—due to their length or plenty of detail—usually are not considered thought experiments, can perform similar cognitive functions. (shrink)

When Ken Malone investigates a case of something causing mental static across the United States, he is teleported to a world that doesn't exist.

Dramatic changes or revolutions in a field of science are often made by outsiders or 'trespassers,' who are not limited by the established, 'expert' approaches. Each essay in this diverse collection shows the fruits of intellectual trespassing and poaching among fields such as economics, Kantian ethics, Platonic philosophy, category theory, double-entry accounting, arbitrage, algebraic logic, series-parallel duality, and financial arithmetic.

Peter Ludlow presents the first book on the philosophy of generative linguistics, including both Chomsky's government and binding theory and his minimalist ...

As testing of ChatGPT has shown, this form of artificial intelligence has the potential to develop, which requires improving its software and other hardware that allows it to learn, i.e., to acquire and use new knowledge, to contact its developers with suggestions for improvement, or to reprogram itself without their participation. Как показало тестирование ChatGPT, эта форма искусственного интеллекта имеет потенциал развития, для чего необходимо усовершенствовать её программное и прочее техническое обеспечение, позволяющее ей учиться, т.е. приобретать и использовать новые знания, (...) обращаться к её разработчикам с предложениями по усовершенствованию, или производить самопрограммирование без их участия. (shrink)

Online collection of papers by Devitt, Dretske, Guarino, Hochberg, Jackson, Petitot, Searle, Tye, Varzi and other leading thinkers on philosophy and the foundations of cognitive Science. Topics dealt with include: Wittgenstein and Cognitive Science, Content and Object, Logic and Foundations, Language and Linguistics, and Ontology and Mereology.

Cet article se propose de tracer les liens théoriques qu’entretiennent l’intelligence artificielle et certaines traditions philosophiques à propos de l’ontologie, du langage, et de l’esprit. On tâchera de mettre en perspective ce en quoi l’intelligence artificielle contemporaine hérite, poursuit, et renouvelle de façon pratique des problématiques anciennes concernant les caractéristiques de l’intelligence humaine et la représentation des connaissances. En introduisant les ontologies informatiques, on cherchera à présenter l’importance des sciences humaines aujourd’hui pour la recherche en intelligence artificielle, tout en soulignant (...) le dialogue permanent que celle-ci a pu entretenir avec la philosophie à travers l’histoire. On conclura en défendant l’intérêt de ces outils pour l’interdisciplinarité des sciences. (shrink)

Nous proposons une étude de la constitution du sens dans l'interaction humain-machine à partir des définitions que donnent Turing et Wittgenstein à propos de la pensée, la compréhension, et de la décision. Nous voulons montrer par l'analyse comparative des proximités et différences conceptuelles entre les deux auteurs que le sens commun entre humains et machines se co-constitue dans et à partir de l'action, et que c'est précisément dans cette co-constitution que réside la valeur sociale de leur interaction. Il s'agira pour (...) cela de problématiser l'interaction humain-machine autour de la question de ce que signifie « suivre une règle » pour définir et distinguer les modes interprétatifs et les comportements décisionnels de chacun. Nous en viendrons alors au constat que la mutualisation des signes qui s'opère à travers le dialogue humain-machine est au fondement de la constitution d'une société informatisée. (shrink)

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)

In this paper a possible extension of Turing test [1] will be presented, which is intended to overcome the limits highlighted by several researchers and scientists in the last seventy years. The main problem related to the execution in Turing test is substantially dealing with the trouble in identification of a human-like intelligence based on a pure evaluation of external behavior of a machine. In this work first of all a description of classical Turing test will be done. After that, (...) some of the main exceptions or oppositions to the Turing test ability to detect “intelligent machines” will be presented. The Lovelace test will be presented as well, as possible alternative to Turing Test, and some considerations on its scope and effectiveness will be made. Furthermore, some references to Penrose and Hofstadter ideas will be recalled, highlighting the strongest troubles in defining and detecting a human-like intelligence, intended as “self-consciousness”. Finally, the new approach will be explained, introducing the new test intended to overcome the troubles highlighted on Turing test execution, based on a model of the self-consciousness obtained by means of the hypersets theory. An example will be presented as well, in order to clarify the proposed approach and its goal. (shrink)

(1) This is Part 2 of the semantic theory I call TM. In Part 1, I developed TM as a theory in the analytic philosophy of language, in lexical semantics, and in the sociology of relating occasions of statement production and comprehension to formal and informal lexicographic conclusions about statements and lexical items – roughly, as showing how synchronic semantics is a sociological derivative of diachronic, person-relative acts of linguistic behavior. I included descriptions of new cognitive psychology experimental paradigms which (...) would allow us to precisely measure the two constituents of semantics – meaning and reference – both at the level of individual speech acts and at the level of societal convergences, i.e. at both the token and type levels. -/- (2) In the Introduction, I recapitulate the arguments of Part 1. The Introduction also develops some analytic philosophical and lexical semantics themes not discussed in Part 1. -/- (3) After the Introduction, I present neural TM (nTM) as a theory of the neural mechanisms and processes which give rise to these person/occasion-relative acts of linguistic behavior. I develop nTM at three levels, the first two of which describe linguistic/semantic functions independently of their cortical locations. At the first level, I describe individual word-to-word and word-to-object connections. At the second level, I describe the corresponding structuralist networks of which they are the individual components. At this level, I introduce some key linguistic concepts of TM – its graded meaning, reference, and generalization sets, and the types of statements which express various levels of word-to-word and word-to-object relationships among lexical items which, because of the constraints they impose on the use of those lexical items in statements we produce and comprehend, are concepts. This constitutes the second structural level of nTM. -/- (4) At the third level, I associate the non-localized structures of the previous levels with cortically located neural structures and with the fasciculi that connect them. I distinguish neural areas in which primary (phonetic) and secondary (orthographic) lexicons are stored in long-term memory. I also describe the embodied concepts which co-exist in the anterior temporal lobes with the images they lexicalize. These concepts are often said to name physical objects and their features, although what they in fact name are kinds of physical objects and features. I describe how conceptual constraints and referential constraints interact to channel our intentions to say how things are into statements which are semantically well-formed, and which consequently successfully communicate information. -/- (5) Following this presentation of nTM, I examine five prominent neural semantic theories. I point out what is wrong with each of them as far as their explanations of semantics are concerned, and I also indicate how nTM can replace the “semantic cores” of those theories. -/- (6) The two basic mistakes made by neuroscience semantic theories, as I will explain, are (i) that all but one of them regard semantics as a matter of the association of words with perceptual images, and of generalizations from those associations; and (ii) that they all rely on an unspecified set of neural structures which purportedly encode the meaning of concepts in abstraction from their phonological and orthographic forms. nTM maintains, in contrast, that there are no abstract neural representations of semantic content. Neural constraints on our linguistic behavior, especially on our ascriptive and co-ascriptive use of words, express the semantic constraints on those words which make them concepts. That is the semantic content of words. -/- (7) I next consider several results from neuroscience experimental data which have been given one interpretation by one or another of the standard neurosemantic theories, but to which nTM gives a different interpretation. I include several predictions which I have found neither confirmed nor disconfirmed in the experimental neuroscience literature. -/- (8) After a concluding section in which I summarize the major changes to neurosemantic theory introduced by TM, and the analytic philosophy of language and lexical semantics contexts within which TM is situated, there follows an appendix in which I discuss neural net AI, and make some recommendations for implementing nTM in silicon. (shrink)

To make progress on the problem of consciousness, we have to confront it directly. In this paper, I first isolate the truly hard part of the problem, separating it from more tractable parts and giving an account of why it is so difficult to explain. I critique some recent work that uses reductive methods to address consciousness, and argue that such methods inevitably fail to come to grips with the hardest part of the problem. Once this failure is recognized, the (...) door to further progress is opened. In the second half of the paper, I argue that if we move to a new kind of nonreductive explanation, a naturalistic account of consciousness can be given. I put forward my own candidate for such an account: a nonreductive theory based on principles of structural coherence and organizational invariance, and a double-aspect theory of information. (shrink)

Saying that psychological states are functional states, the functionalist claims more than that psychological states have functions. Rather, functionalism is the theory that psychological states are defined and constituted by their functions. On this view, what it is to be a psychological state of a certain sort just is and consists entirely of having a certain function. Anything that has that function in a suitable system would therefore be that psychological state. If storing information for later use is the essential (...) function of memory, then anything that has that function counts as a memory. Similarly, one might say that anything that traps or kills mice counts as a mouse trap. (shrink)

Mental imagery (varieties of which are sometimes colloquially refered to as “visualizing,” “seeing in the mind's eye,” “hearing in the head,” “imagining the feel of,” etc.) is quasi-perceptual experience; it resembles perceptual experience, but occurs in the absence of the appropriate external stimuli. It is also generally understood to bear intentionality (i.e., mental images are always images of something or other), and thereby to function as a form of mental representation. Traditionally, visual mental imagery, the most discussed variety, was thought (...) to be caused by the presence of picturelike representations (mental images) in the mind, soul, or brain, but this is no longer universally accepted. (shrink)

I focus on and criticize John Searle's argument against a classical computational view of the mind according to which the attribution of syntax is observer relative (in Searle, Rediscovery of Mind, MIT Press, 1992). Searle's argument is interesting inasmuch as it differs from his previous and more well-known argument that syntax is not sufficient for semantics. This argument aims to undercut even the syntax as something that exists only in the eye of the beholder. I show that Searle's argument rests (...) on premises that go unsupported. (shrink)

Thesis (Ph. D.)--University of Hawaii at Manoa, 1996.

I'll show that the kind of analogy between life and information [argued for by authors such as Davies (2000), Walker and Davies (2013), Dyson (1979), Gleick (2011), Kurzweil (2012), Ward (2009)] – that seems to be central to the effect that artificial mind may represent an expected advance in the life evolution in the Universe – is like the design argument, and that if the design argument is unfounded and invalid, the argument to the effect that artificial mind may represent (...) an expected advance in the life evolution in the Universe is also unfounded and invalid. However, if we are prepared to admit (though we should not do so) this method of reasoning as valid, I'll show that the analogy between life and information to the effect that artificial mind may represent an expected advance in the evolution of life in the Universe seems to suggest some type of reductionism of life to information, but biology respectively chemistry, or physics are not reductionist, contrary to what seems to be suggested by the analogy between life and information. (shrink)

This entry provides a substantive overview of research and debates concerning creativity in philosophy and related fields. Topics covered include definitions of creativity, whether creativity can be learned, whether it can be explained, attempts to explain creativity in cognitive science, and whether computer programs or AI systems can be creative.

This research is concerned with the innate predispositions underlying human intentional communication. Human communication is currently defined as a circular and overt attempt to modify a partner's mental states. This requires each party involved to posse ss the ability to represent and understand the other's mental states, a capability which is commonly referred to as mindreading, or theory of mind (ToM). The relevant experimental literature agrees that no such capability is to be found in the human speci es at least (...) during the first year of life, and possibly later. This paper aims at advancing a solution to this theoretical problem. We propose to consider sharedness as the basis for intentional communication in the infant and to view it as a primitive, i nnate component of her cognitive architecture. Communication can then build upon the mental grounds that the infant takes as shared with her caregivers. We view this capability as a theory of mind in a weak sense.›. (shrink)

We argue that the locomotion of organisms is better understood as a form of interaction with a subjective environment, rather than as a set of behaviors allegedly amenable to objective descriptions. An organism's interactions with its subjective environment are in turn understandable in terms of its cognitive architecture. We propose a large-scale classification of the possible types of cognitive architectures, giving a sketch of the subjective structure that each of them superimposes on space and of the relevant consequences on locomotion. (...) The classification comprises a main division between nonrepresentational and representational architectures and further subdivisions. (shrink)

In the last forty years, significant developments in neuroscience, psychology, and robotic technology have been cause for major trend changes in the philosophy of mind. One such shift has been the reallocation of focus from entirely brain-centered theories of mind to more embodied, embedded, and even extended answers to the questions, what are cognitive processes and where do we find such phenomena? Given that hypotheses such as Clark and Chalmers‘ (1998) Extended Mind or Hutto‘s (2006) Radical Enactivism, systematically undermine the (...) organism-bound, internal, and static pictures of minds and allow instead for the distribution of cognitive processes among brains, bodies, and worlds, a worry that arises is that the very subject of cognitive science, the ‗cognizer‘ will be hopelessly opaque, its mind leaking out into the world all over the place, thereby making it impossible to rein in and properly study. A seemingly unrelated and yet parallel trend has also taken place in feminist theorizing about the body over the last forty years. Whereas feminism of the 1970s and early 1980s tended to view ‗the body‘ as the site and matter of biological sex, while gender was a more fluid and socially constituted mode of existence, more recent feminist theory has questioned the givenness of bodies themselves. In other words, rather than seeing gender categories as manifestations of the already given sexed body, thinkers such as Butler (2000) and Lorber (1992) argue that the very notion of a body is often a product of scientific inquiry, which is itself a product of the power structures aiming to maintain a rigid binary between feminine and masculine gender roles. If the world at large plays such a constitutive role in determining who we are, then this implies that the tools we use, the language we speak, and the power relationships in which we are enmeshed are components of what it means to be embodied in any genuine sense. For thinkers like Haraway (1988) the image of the cyborg is most fitting for this new understanding of embodied subjects, as the cyborg is a coupling of machine and human. Gender and even biological sex will always be a technologically hybridized ‗monster‘ consisting of matter, machine, and mind. The overall aim of my project is thus to bring the two concurrent developments in theorizing about embodied subjects into discourse. As the cyborg features largely in recent feminist thought about embodiment, so too has it been a prominent metaphor in philosophy of mind, ever since Clark (2003) claimed that we ought to think of our ‗selves‘ more appropriately as Natural-Born Cyborgs. I therefore focus on this imagery as I go on to make the argument that this distributed account of cognition as well as of sexual identity is more fruitful for making progress in understanding ‗the human‘ more generally. Likewise, I argue that bringing the discussion of sex and gender into the arena of an otherwise asexual philosophy of mind, will shed light on some important facets of embodiment that have been overlooked but that ought to be addressed if we are to have an adequate account of ‗the proper subject of cognitive science.‘ My chapters include 1) a survey of the discourse between science and philosophy of mind leading to these embodied and extended approaches, 2) a first attempt at defending the extended mind thesis, 3) a discussion of how even the supposed resolution to the objections raised against extended cognition fails to properly take into account just how problematic subjectivity is, regardless of its being defined entirely organismic or not, as organisms themselves are highly malleable and socially constituted, 4) an explanation concerning how the same problematization of embodied subjectivity is ongoing in feminist theory, especially considering the phenomenology of transgendered embodiment, intersex, and technologically mediated bodies, 5) further elaboration on technologically enhanced bodies, exposing what I see as a continuum between bodies modified by ‗hard‘ technologies, such as implants, prostheses or surgeries, and those modified by ‗soft‘ technologies, such as gender norms, the social gaze, and technologically mediated metacognition, and last, 6) an argument for the image of the cyborg to replace ‗organism‘ in cognitive science, along with the corollary argument that cyborgs ought to represent not just embodied minds, but should also be the metaphor in attempting to understand ‗embodiment‘ more generally, which must, at its roots, be underpinned by gender and sexual identity. I argue that the imagery is fitting for the proper study of cognitive subjects as well as sexed and gendered bodies, but moreover, that just as the cyborg suggests a blending and hybridizing of seemingly unrelated elements, so too should the two areas of inquiry, philosophy of mind and feminist theory, pay heed to one another‘s use of this imagery and themselves begin to be more integrative in their approaches. (shrink)

I will argue that the scientific investigation of philosophical intuition ('experimental philosophy') is of philosophical interest. I will defend the significance of experimental philosophy against two important types of objection. I will term the first objection 'eliminativism' about intuitions: roughly, it is the claim that philosophical methodology does not in fact rely on intuition, and thus experimental philosophy's investigation is ill-conceived—in the words of one such opponent, 'a big mistake.' I will then consider a second objection, the 'expertise' defence. The (...) expertise defence argues that the expert intuitions of professional philosophers are distinct, and to be preferred to those of the 'folk.' Against the eliminativists, I will argue that an ineliminable mental component remains that can be subject of fruitful empirical investigation. Against the expertise defence I will argue that, at least in the context of philosophy of language, expertise is itself a potential source of bias. Since expertise is domain-specific, however, a general rebuttal will not be given. I will conclude that experimental philosophy has much to contribute. (shrink)

Heuristics are often invoked in the philosophical, psychological, and cognitive science literatures to describe or explain methodological techniques or "shortcut" mental operations that help in inference, decision-making, and problem-solving. Yet there has been surprisingly little philosophical work done on the nature of heuristics and heuristic reasoning, and a close inspection of the way(s) in which "heuristic" is used throughout the literature reveals a vagueness and uncertainty with respect to what heuristics are and their role in cognition. This dissertation seeks to (...) remedy this situation by motivating philosophical inquiry into heuristics and heuristic reasoning, and then advancing a theory of how heuristics operate in cognition. I develop a positive working characterization of heuristics that is coherent and robust enough to account for a broad range of phenomena in reasoning and inference, and makes sense of empirical data in a systematic way. I then illustrate the work this characterization does by considering the sorts of problems that many philosophers believe heuristics solve, namely those resulting from the so-called frame problem. Considering the frame problem motivates the need to gain a better understanding of how heuristics work and the cognitive structures over which they operate. I develop a general theory of cognition which I argue underwrites the heuristic operations that concern this dissertation. I argue that heuristics operate over highly organized systems of knowledge, and I offer a cognitive architecture to accommodate this view. I then provide an account of the systems of knowledge that heuristics are supposed to operate over, in which I suggest that such systems of knowledge are concepts. The upshot, then, is that heuristics operate over concepts. I argue, however, that heuristics do not operate over conceptual content, but over metainformational relations between activated and primed concepts and their contents. Finally, to show that my thesis is empirically adequate, I consider empirical evidence on heuristic reasoning and argue that my account of heuristics explains the data. (shrink)

This paper argues that the “Canberra Plan” picture of physicalistic reduction of mind--a picture shared by both its proponents and opponents, philosophers as diverse as David Armstrong, David Chalmers Frank Jackson, Jaegwon Kim, Joe Levine and David Lewis--neglects ground (Fine, 2001, 2012). To the extent that the point of view endorsed by the Canberra Plan has an account of the physical/functional ground of mind at all, it is in one version trivial and in another version implausible. In its most general (...) form, the point of view of the Canberra Plan is committed to unacceptably treating indexical or name-related facts as part of the ultimate physical/functional ground of the mental. (shrink)

Due to his significant role in the development of computer technology and the discipline of artificial intelligence, Alan Turing has supposedly subscribed to the theory of mind that has been greatly inspired by the power of the said technology which has eventually become the dominant framework for current researches in artificial intelligence and cognitive science, namely, computationalism or the computational theory of mind. In this essay, I challenge this supposition. In particular, I will try to show that there is no (...) evidence in Turing’s two seminal works that supports such a supposition. His 1936 paper is all about the notion of computation or computability as it applies to mathematical functions and not to the nature or workings of intelligence. On the other hand, while his 1950 work is about intelligence, it is, however, particularly concerned with the problem of whether intelligence can be attributed to computing machines and not of whether computationality can be attributed to human intelligence or to intelligence in general. (shrink)

The ethics of emerging forms of artificial intelligence has become a prolific subject in both academic and public spheres. A great deal of these concerns flow from the need to ensure that these technologies do not cause harm—physical, emotional or otherwise—to the human agents with which they will interact. In the literature, this challenge has been met with the creation of artificial moral agents: embodied or virtual forms of artificial intelligence whose decision procedures are constrained by explicit normative principles, requiring (...) the implementation of what is commonly called artificial morality into these agents. To date, the types of reasoning structures and principles which inform artificial morality have been of two kinds: first, an ethically maximal vision of artificial morality which relies on the strict implementation of traditional moral theories such as Kantian deontology or Utilitarianism, and second, a more minimalist vision which applies stochastic AI techniques to large data sets of human moral preferences so as to illicit or intuit general principles and preferences for the design of artificial morality. Taken individually, each approach is unable to fully answer the challenge of producing inoffensive behavior in artificial moral agents, most especially since both forms are unable to strike a balance between the ideal set of constraints which morality imposes on one hand, and the types of constraints public acceptability imposes, on the other. We provide an alternative approach to the design of artificial morality, the Ethical Valence Theory, whose purpose is to accommodate this balance, and apply this approach to the case of autonomous vehicles. (shrink)

Artificial intelligence (AI) technologies are used in various domains of human activities, and one of these domains is scientific research. Now, researchers in many scientific areas try to apply AI technologies to their research and automate it. These researchers claim that the ‘automation of science’ will liberate people from non-creative tasks in scientific research, and radically change the overall state of science and technology so that large-scale innovation results. As I see it, the automation of science is remarkable in another (...) respect: since science is one of the most distinctive human activities, the tendency of automating it prompts us to reconsider the aspects of our humanity itself. One of these aspects is concerned with human creativity, on which this article focuses. In this article, I address two questions concerning the automation of science: first, ‘Can AI makes creative discovery?’; second, ‘What implications may the automation of science have on science and society?’. Scientific discovery is said to be one of the most creative phases of scientific research. I show that, though there are no reasons in principle why AI could not make creative discovery, we do not at present have enough knowledge how to realize it. If the automation of science nevertheless proceeds, the cultural values science as a creative activity has might be reduced, and it might alter the state of scientific community and its relationship with society in some undesirable way. Therefore, I conclude, we need to specify desirable ways of introducing AI technologies into science and devise measures against demerits of automating science. (shrink)

In this section, we will start with an influential attempt to define `intelligence', and then we will move to a consideration of how human intelligence is to be investigated on the machine model. The last part of the section will discuss the relation between the mental and the biological.

The human brain consists of approximately 100 billion electrically active neurones that generate an endogenous electromagnetic field, whose role in neuronal computing has not been fully examined. The source, magnitude and likely influence of the brain's endogenous em field are here considered. An estimate of the strength and magnitude of the brain's em field is gained from theoretical considerations, brain scanning and microelectrode data. An estimate of the likely influence of the brain's em field is gained from theoretical principles and (...) considerations of the experimental effects of external em fields on neurone firing both in vitro and in vivo. Synchronous firing of distributed neurones phase-locks induced em field fluctuations to increase their magnitude and influence. Synchronous firing has previously been demonstrated to correlate with awareness and perception, indicating that perturbations to the brain's em field also correlate with awareness. The brain's em field represents an integrated electromagnetic field representation of distributed neuronal information and has dynamics that closely map to those expected for a correlate of consciousness. I propose that the brain's em information field is the physical substrate of conscious awareness - the cemi field - and make a number of predictions that follow from this proposal. Experimental evidence pertinent to these predictions is examined and shown to be entirely consistent with the cemi field theory. This theory provides solutions to many of the intractable problems of consciousness - such as the binding problem - and provides new insights into the role of consciousness, the meaning of free will and the nature of qualia. It thus places consciousness within a secure physical framework and provides a route towards constructing an artificial consciousness. (shrink)

In this paper, I use the comparison between human beings and intelligent machines to shed light on the concept of teleology. What characterizes human beings and distinguishes them from a robot capable of achieving complex objectives? In the first place, by stipulating that what characterizes human beings are mental states, I consider the mark of the mental. A smart robot probably has no consciousness but we might have reason for doubt while interacting with it. And a smart robot shows intentionality. (...) I focus on the type of naturalized intentionality that is at stake here. Then I go back to the traditional idea of teleology, and to the scientific criticism of it, through the question of the kind of purposes that artificial intelligence (AI) may set itself. Husserl's basic idea of teleology therefore serves to have an authoritative term of comparison and to introduce the intuitive difference between human beings and intelligent machines based on the homo pictor thought experiment proposed by Jonas. My conclusion is that a specific finalism, understood in a non-criterial sense, is what qualifies the human being and differentiates the latter (for now) from smart robots. (shrink)

As a step towards comprehensive computer models of communication, and effective human machine dialogue, some of the relationships between communication and affect are explored. An outline theory is presented of the architecture that makes various kinds of affective states possible, or even inevitable, in intelligent agents, along with some of the implications of this theory for various communicative processes. The model implies that human beings typically have many different, hierarchically organized, dispositions capable of interacting with new information to produce affective (...) states, distract attention, interrupt ongoing actions, and so on. High "insistence" of motives is defined in relation to a tendency to penetrate an attention filter mechanism, which seems to account for the partial loss of control involved in emotions. One conclusion is that emulating human communicative abilities will not be achieved easily. Another is that it will be even more difficult to design and build computing systems that reliably achieve interesting communicative goals. (shrink)

Ita La recensione presenta la prospettiva enattivista difesa da Alva Noë, e ne discute alcuni aspetti specifici. Il pensiero, la coscienza e la cognizione non sono pienamente comprensibili, secondo l’enattivismo di Noë, senza un’adeguata considerazione del ruolo ricoperto dal corpo e dall’ambiente. Sarebbe quindi sbagliato continuare a pensare che il cervello da solo sia responsabile dei processi cognitivi umani: il programma che ricerca i correlati neurali della coscienza sarebbe quindi destinato al fallimento dal principio, perché tralascia in partenza corpo e (...) ambiente; i programmi di ricerca nel campo dell’intelligenza artificiale sarebbero ugualmente compromessi, non solo con una concezione computazionalista della cognizione, ma anche con la vecchia idea che un cervello artificiale sia sufficiente alla cognizione quanto un cervello naturale. Di seguito si prendono in esame due prospettive sperimentali su cui Noë fa grande affidamento: gli studi sulla plasticità neurale dei furetti svolti da Mriganka Sur e altri, e la realizzazione di un sistema di sostituzione visuo-tattile da parte di Paul Bach-Y-Rita. Per Noë si tratta di elementi cruciali in supporto alla propria prospettiva: in realtà, come emerge dalla breve analisi, l’attribuire loro un significato così chiaro e univoco pro-enattivismo è qualcosa di molto meno scontato. Infine, segue un breve bilancio del libro di Noë, dove gli elementi d’interesse del volume sono presentati insieme all’individuazione di alcuni punti deboli, che il testo condivide con la gran parte degli studi che in vario modo fanno leva sull’intuizione legata all’embodiement: da un lato una difficoltà strutturale riguarda la possibilità di identificare con chiarezza gli elementi costitutivi del mentale; dall’altro lato, il riferimento a forme di esternalismo radicale sembra ugualmente comportare diversi problemi. -/- Abstract Eng The review presents Alva Noë’s enactivist view, and aims at discussing some of its ideas. Thought, consciousness, and cognition are not understandable, Noë claims, without taking into proper consideration the role played by the body and the environment. It would be wrong indeed to go on thinking that our brain alone is responsible for human cognitive processes: the program searching for the neural correlates of consciousness is hopeless in principle, because it neglects from the beginning the body and the environment; research programs in artificial intelligence are as well compromised, not only with a computationalist view of cognition, but also with the old idea that an artificial brain will suffice for cognition just like a natural one. Thereafter, two experimental perspectives, that Noë uses to support his view, are examined: Mriganka Sur’s studies on neural plasticity of ferrets, and Paul Bach-Y-Rita’s tactile-visual substitution system. Noë argues that these results are crucial in supporting his view, but, as the discussion highlights, their pro-enactivism meaning is not so clear and unambiguous. Finally, a balance of the book follows, where the many elements of interest are presented together with the acknowledgment of some weak points, that the book shares with the majority of the proposals that deal with the embodiment’s insight: on the one hand, a structural difficulty concerns the possibility to identify clearly the constitutive elements of the mental; on the other hand, the reference to radical versions of externalism seems to entail many difficulties as well. (shrink)