Over the past several decades, the philosophical community has witnessed the emergence of an important new paradigm for understanding the mind.1 The paradigm is that of machine computation, and its influence has been felt not only in philosophy, but also in all of the empirical disciplines devoted to the study of cognition. Of the several strategies for applying the resources provided by computer and cognitive science to the philosophy of mind, the one that has gained the most attention from philosophers (...) has been the Computational Theory of Mind (CTM). CTM was first articulated by Hilary Putnam (1960, 1961), but finds perhaps its most consistent and enduring advocate in Jerry Fodor (1975, 1980, 1981, 1987, 1990, 1994). It is this theory, and not any broader interpretations of what it would be for the mind to be a computer, that I wish to address in this paper. What I shall argue here is that the notion of symbolic representation employed by CTM is fundamentally unsuited to providing an explanation of the intentionality of mental states (a major goal of CTM), and that this result undercuts a second major goal of CTM, sometimes refered to as the vindication of intentional psychology. This line of argument is related to the discussions of derived intentionality by Searle (1980, 1983, 1984) and Sayre (1986, 1987). But whereas those discussions seem to be concerned with the causal dependence of familiar sorts of symbolic representation upon meaning-bestowing acts, my claim is rather that there is not one but several notions of meaning to be had, and that the notions that are applicable to symbols are conceptually dependent upon the notion that is applicable to mental states in the fashion that Aristotle refered to as paronymy. That is, an analysis of the notions of meaning applicable to symbols reveals that they contain presuppositions about meaningful mental states, much as Aristotle's analysis of the sense of healthy that is applied to foods reveals that it means conducive to having a healthy body, and hence any attempt to explain mental semantics in terms of the semantics of symbols is doomed to circularity and regress. I shall argue, however, that this does not have the consequence that computationalism is bankrupt as a paradigm for cognitive science, as it is possible to reconstruct CTM in a fashion that avoids these difficulties and makes it a viable research framework for psychology, albeit at the cost of losing its claims to explain intentionality and to vindicate intentional psychology. I have argued elsewhere (Horst, 1996) that local special sciences such as psychology do not require vindication in the form of demonstrating their reducibility to more fundamental theories, and hence failure to make good on these philosophical promises need not compromise the broad range of work in empirical cognitive science motivated by the computer paradigm in ways that do not depend on these problematic treatments of symbols. (shrink)

In this paper I will attempt to explain why the controversy surrounding the alleged refutation of Mechanism by Gödel’s theorem is continuing even after its unanimous refutation by logicians. I will argue that the philosophical point its proponents want to establish is a necessary gap between the intended meaning and its formulation. Such a gap is the main tenet of philosophical hermeneutics. While Gödel’s theorem does not disprove Mechanism, it is nevertheless an important illustration of the hermeneutic principle. The ongoing (...) misunderstanding is therefore based in a distinction between a metalogical illustration of a crucial feature of human understanding, and a logically precise, but wrong claim. The main reason for the confusion is the fact that in order to make the claim logically precise, it must be transformed in a way which destroys its informal value. Part of this transformation is a clear distinction between the Turing Machine as a mathematical object and a machine as a physical device. (shrink)

Many requirements of rationality rely for their application on facts about identity at a time. Take the requirement not to have contradictory beliefs. It is irrational if a single agent bel...

Cognitivism in psychology and philosophy is roughly the position that intelligent behavior can (only) be explained by appeal to internal that is, rational thought in a very broad sense. Sections 1 to 5 attempt to explicate in detail the nature of the scientific enterprise that this intuition has inspired. That enterprise is distinctive in at least three ways: It relies on a style of explanation which is different from that of mathematical physics, in such a way that it is not (...) basically concerned with quantitative equational laws; the states and processes with which it deals are in the sense that they are regarded as meaningful or representational; and it is not committed to reductionism, but is open to reduction in a form different from that encountered in other sciences. Spelling these points out makes it clear that the Cognitivist study of the mind can be rigorous and empirical, despite its unprecedented theoretical form. The philosophical explication has another advantage as well: It provides a much needed framework for articulating questions about whether the Cognitivist approach is right or wrong. The last three sections take that advantage of the account, and address several such questions, pro and con. (shrink)

Williamson’s Knowledge and its Limits is the most important philosophical discussion of knowledge in many years. It sets the agenda for epistemology for the next decade and beyond.

Williamson’s Knowledge and its Limits is the most important philosophical discussion of knowledge in many years. It sets the agenda for epistemology for the next decade and beyond.

What counts as a computation and how it relates to cognitive function are important questions for scientists interested in understanding how the mind thinks. This paper argues that pragmatic aspects of explanation ultimately determine how we answer those questions by examining what is needed to make rigorous the notion of computation used in the (cognitive) sciences. It (1) outlines the connection between the Church-Turing Thesis and computational theories of physical systems, (2) differentiates merely satisfying a computational function from true computation, (...) and finally (3) relates how we determine a true computation to the functional methodology in cognitive science. All of the discussion will be directed toward showing that the only way to connect formal notions of computation to empirical theory will be in virtue of the pragmatic aspects of explanation. (shrink)

It is asked to what extent answers to such questions as ?Can machines think??, ?Could robots have feelings?? might be expected to yield insight into traditional mind?body questions. It has sometimes been assumed that answering the first set of questions would be the same as answering the second. Against this approach other philosophers have argued that answering the first set of questions would not help us to answer the second. It is argued that both of these assessments are mistaken. It (...) is then claimed, although not argued in detail, that the following three approaches to the first set of questions are mistaken: (1) machines (and robots) obviously cannot think, feel, create, etc., since they do only what they are programmed to do; (2) on the basis of ah analysis of the meaning of the words ?machine? ('robot?, ?think?, ?feel?, etc.) we can see that in principle it would be impossible for machines (or robots) to think, feel, create, etc.; (3) machines (and robots) obviously can (or could) think, feel, etc., since they do certain things which, if we were to do them, would require thought, feeling, etc. It is argued that, once it is seen why approach (2) is mistaken, it becomes desirable to decline ?in principle? approaches to the first set of questions and to favor ?piecemeal investigations? where attention is centered upon what is actually taking place in machine technology, the development of new programming techniques, etc. Some suggestions are made concerning the relevance of current computer simulation studies to traditional mind?body questions. A new set of questions is proposed as a substitute for the first set of questions. It is hoped that attempts to answer these may provide us with new and detailed portraits of the mind?body relationship. (shrink)

A prominent way of explaining how race is socially constructed appeals to social positions and social structures. On this view, the construction of a person’s race is understood in terms of the person occupying a certain social position in a social structure. The aim of this paper is to give a metaphysically perspicuous account of this form of race construction. Analogous to functionalism about mental states, I develop an account of a ‘race structure’ in which various races (Black, White, Asian, (...) etc.) are functionally defined social positions. Individual persons occupy these social positions by ‘playing the role’ characteristic of those positions. The properties by which a person plays a race role, are the realizers for one’s race. I characterize the social construction of a person’s race in terms of a realization relation that satisfies a ‘subset’ condition on the social powers of raced persons. Races, on this view, are functionally defined, multiply realizable social kinds. The final section of the paper outlines some explanatory benefits of the account. (shrink)

Turing made strong statements about the future of machines in society. This article asks how they can be interpreted to advance our understanding of Turing’s philosophy. His irony has been largely caricatured or minimized by historians, philosophers, scientists, and others. Turing is often portrayed as an irresponsible scientist, or associated with childlike manners and polite humor. While these representations of Turing have been widely disseminated, another image suggested by one of his contemporaries, that of a nonconformist, utopian, and radically progressive (...) thinker reminiscent of the English Romantic poet Percy B. Shelley, has remained largely underexplored. Following this image, I will reconstruct the argument underlying what Turing called (but denied being guilty of) his “Promethean irreverence” (1947–1951) as a utopian satire directed against chauvinists of all kinds, especially intellectuals who might sacrifice independent thought to maintain their power. These, Turing hoped, would eventually be rivaled and surpassed by intelligent machines and transformed into ordinary people, as work once considered “intellectual” would be transformed into non-intellectual, “mechanical” work. I study Turing’s irony in its historical context and follow the internal logic of his arguments to their limit. I suggest that Turing genuinely believed that the possibilities of the machines he envisioned were not utopian dreams, and yet he conceived them from a utopian frame of mind, aspiring to a different society. His ever-learning child machines, whose intelligence would grow out of their own individual experiences, would help distribute power. (shrink)

Do computers have beliefs? I argue that anyone who answers in the affirmative holds a view that is incompatible with what I shall call the commonsense approach to the propositional attitudes. My claims shall be two. First,the commonsense view places important constraints on what can be acknowledged as a case of having a belief. Second, computers – at least those for which having a belief would be conceived as having a sentence in a belief box – fail to satisfy some (...) of these constraints. This second claim can best be brought out in the context of an examination of the idea of computer self-knowledge and self-deception, but the conclusion is perfectly general: the idea that computers are believers, like the idea that computers could have self-knowledge or be self-deceived, is incompatible with the commonsense view. The significance of the argument lies in the choice it forces on us: whether to revise our notion of belief so as to accommodate the claim that computers are believers, or to give up on that claim so as to preserve our pretheoretic notion of the attitudes. We cannot have it both ways. (shrink)

The ordinary understanding and ascription of mental states is a multiply complex subject. Widely discussed approaches to the subject, such as functionalism and the theory-theory (TT), have many variations and interpretations. No surprise, then, that there are misunderstandings and disagreements, which place many items on the agenda. Unfortunately, the multiplicity of issues raised by the commentators and the limitations of space make it impossible to give a full reply to everyone. My response is divided into five topics: (1) Which version(s) (...) of functionalism are candidates for an account of folk psychology, and is any such version satisfactory? (2) Where does TT stand in light of the two target articles and commentaries? (3) Does a phenomenological story provide a promising account of mental states, and is there special first-person authority about them? (4) What are suitable methodological assumptions for our subject matter? (5) How well does the simulation theory fare as an account of third-person mentalistic ascription? (shrink)

“Triviality arguments” against functionalism in the philosophy of mind hold that the claim that some complex physical system exhibits a given functional organization is either trivial or has much less content than is usually supposed. I survey several earlier arguments of this kind, and present a new one that overcomes some limitations in the earlier arguments. Resisting triviality arguments is possible, but requires functionalists to revise popular views about the “autonomy” of functional description.

While the concept of multiple realizability is widely used, it is seldom rigorously characterized. This paper defends a liberal conception of multiple realizability as sameness of type through _any_ differences in the (lower-level) conditions that give rise to instances of that type. This kind of “sameness through difference” is contrasted with another type of asymmetric dependency relation between properties, multiple _specification_. This liberal conception is then defended from objections, and it is augmented by a concept of relativized multiple realizability. The (...) last section presents a survey of the ontological, explanatory, and methodological consequences of this analysis of multiple realizability. (shrink)

There is a steadily growing literature on the role of the immune system in psychiatric disorders. So far, these advances have largely taken the form of correlations between specific aspects of inflammation (e.g. blood plasma levels of inflammatory markers, genetic mutations in immune pathways, viral or bacterial infection) with the development of neuropsychiatric conditions such as autism, bipolar disorder, schizophrenia and depression. A fundamental question remains open: why are psychiatric disorders and immune responses intertwined? To address this would require a (...) step back from a historical mind–body dualism that has created such a dichotomy. We propose three contributions of active inference when addressing this question: translation, unification, and simulation. To illustrate these contributions, we consider the following questions. Is there an immunological analogue of sensory attenuation? Is there a common generative model that the brain and immune system jointly optimise? Can the immune response and psychiatric illness both be explained in terms of self-organising systems responding to threatening stimuli in their external environment, whether those stimuli happen to be pathogens, predators, or people? Does false inference at an immunological level alter the message passing at a psychological level (or vice versa) through a principled exchange between the two systems? (shrink)

In this paper, I present an informational approach to the nature of personal identity. In “Plato and the problem of the chariot”, I use Plato’s famous metaphor of the chariot to introduce a specific problem regarding the nature of the self as an informational multiagent system: what keeps the self together as a whole and coherent unity? In “Egology and its two branches” and “Egology as synchronic individualisation”, I outline two branches of the theory of the self: one concerning the (...) individualisation of the self as an entity, the other concerning the identification of such entity. I argue that both presuppose an informational approach, defend the view that the individualisation of the self is logically prior to its identification , and suggest that such individualisation can be provided in informational terms. Hence, in “A reconciling hypothesis: the three membranes model”, I offer an informational individualisation of the self, based on a tripartite model, which can help to solve the problem of the chariot. Once this model of the self is outlined, in “ICTs as technologies of the self” I use it to show how ICTs may be interpreted as technologies of the self. In “The logic of realisation”, I introduce the concept of “realization” (Aristotle’s anagnorisis ) and support the rather Spinozian view according to which, from the perspective of informational structural realism, selves are the final stage in the development of informational structures. The final “Conclusion: from the egology to the ecology of the self” briefly concludes the article with a reference to the purposeful shaping of the self, in a shift from egology to ecology. (shrink)

Recently, Horsman et al. have proposed a new framework, Abstraction/Representation theory, for understanding and evaluating claims about unconventional or non-standard computation. Among its attractive features, the theory in particular implies a novel account of what is means to be a computer. After expounding on this account, I compare it with other accounts of concrete computation, finding that it does not quite fit in the standard categorization: while it is most similar to some semantic accounts, it is not itself a semantic (...) account. Then I evaluate it according to the six desiderata for accounts of concrete computation proposed by Piccinini. Finding that it does not clearly satisfy some of them, I propose a modification, which I call Agential AR theory, that does, yielding an account that could be a serious competitor to other leading account of concrete computation. (shrink)

The aims of this paper are threefold: To show that game-playing (GP), the discipline of Artificial Intelligence (AI) concerned with the development of automated game players, has a strong epistemological relevance within both AI and the vast area of cognitive sciences. In this context games can be seen as a way of securely reducing (segmenting) real-world complexity, thus creating the laboratory environment necessary for testing the diverse types and facets of intelligence produced by computer models. This paper aims to promote (...) the belief that games represent an excellent tool for the project of computational psychology (CP). To underline how, despite this, GP has mainly adopted an engineering-inspired methodology and in doing so has distorted the framework of cognitive functionalism. Many successes (i.e. chess, checkers) have been achieved refusing human-like reasoning. The AI has appeared to work well despite ignoring an intrinsic motivation, that of creating an explanatory link between machines and mind. To assert that substantial improvements in GP may be obtained in the future only by renewed interest in human-inspired models of reasoning and in other cognitive studies. In fact, if we increase the complexity of games (from NP-Completeness to AI-Completeness) in order to reproduce real-life problems, computer science techniques enter an impasse. Many of AI’s recent GP experiences can be shown to validate this. The lack of consistent philosophical foundations for cognitive AI and the minimal philosophical commitment of AI investigation are two of the major reasons that play an important role in explaining why CP has been overlooked. (shrink)

There is currently a significant amount of interest in understanding and developing theories of realization. Naturally arguments have arisen about the adequacy of some theories over others. Many of these arguments have a point. But some can be resolved by seeing that the theories of realization in question are not genuine competitors because they fall under different conceptual traditions with different but compatible goals. I will first describe three different conceptual traditions of realization that are implicated by the arguments under (...) discussion. I will then examine the arguments, from an older complaint by Norman Malcolm against a familiar functional theory to a recent argument by Thomas Polger against an assortment of theories that traffic in inherited causal powers, showing how they can be resolved by situating the theories under their respective conceptual traditions. (shrink)

I use Carl Gillett’s much heralded dimensioned theory of realization as a platform to develop a plausible part–whole theory. I begin with some basic desiderata for a theory of realization that its key terms should be defined and that it should be explanatory. I then argue that Gillett’s original theory violates these conditions because its explanatory force rests upon an unspecified “in virtue of” relation. I then examine Gillett’s later version that appeals instead to theoretical terms tied to “mechanisms.” Yet (...) I argue that it too violates the desiderata, since it defines realization for mechanisms in terms of two undefined ideas whose explanatory credentials have not been established—“implementation” and “grounds.” Thus I drop those ideas in favor of an explicit constraint that the parts and properties provide a mechanistic explanation. I also distinguish a special mechanistic theory from a preferred general theory that incorporates other kinds of part–whole explanations that target causal powers or capacities. The result is a theory that has the explanatory virtues of mechanistic theories as well as a broader scope desired by Gillett. I also compare the result to a similar idea from Robert Cummins that has been neglected in recent discussions of realization, namely, his general property analysis rather than his functional analysis. Finally, I defend the preferred general theory against possible objections that attempt to show a conflict between metaphysical demands on a theory of realization versus facts about good scientific explanation. (shrink)

We examine the philosophical disputes among computer scientists concerning methodological, ontological, and epistemological questions: Is computer science a branch of mathematics, an engineering discipline, or a natural science? Should knowledge about the behaviour of programs proceed deductively or empirically? Are computer programs on a par with mathematical objects, with mere data, or with mental processes? We conclude that distinct positions taken in regard to these questions emanate from distinct sets of received beliefs or paradigms within the discipline: – The rationalist (...) paradigm, which was common among theoretical computer scientists, defines computer science as a branch of mathematics, treats programs on a par with mathematical objects, and seeks certain, a priori knowledge about their ‘correctness’ by means of deductive reasoning. – The technocratic paradigm, promulgated mainly by software engineers and has come to dominate much of the discipline, defines computer science as an engineering discipline, treats programs as mere data, and seeks probable, a posteriori knowledge about their reliability empirically using testing suites. – The scientific paradigm, prevalent in the branches of artificial intelligence, defines computer science as a natural (empirical) science, takes programs to be entities on a par with mental processes, and seeks a priori and a posteriori knowledge about them by combining formal deduction and scientific experimentation. We demonstrate evidence corroborating the tenets of the scientific paradigm, in particular the claim that program-processes are on a par with mental processes. We conclude with a discussion in the influence that the technocratic paradigm has been having over computer science. (shrink)