According to Marr, a computational-level theory consists of two elements, the what and the why . This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: ( a ) that the Why element plays an explanatory role in computational-level theories, ( b ) that its goal is to explain why the computed function (specified by the What element) is appropriate for a given visual task, and ( c ) that the (...) explanation consists in showing that the functional relations between the representing cells are similar to the “external” mathematical relations between the entities that these cells represent. *Received September 2009; revised January 2010. †To contact the author, please write to: Departments of Philosophy and Cognitive Science, The Hebrew University, Jerusalem 91905, Israel; e-mail: [email protected]. (shrink)

The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's famous analysis (...) of the central problems in mathematics. The rest of the article is devoted to the eighteen problems. These are organized into five sections: problems in the analysis of the concept of information, in semantics, in the study of intelligence, in the relation between information and nature, and in the investigation of values. (shrink)

We show how an epistemology informed by cognitive science promises to shed light on an ancient problem in the philosophy of mathematics: the problem of exactness. The problem of exactness arises because geometrical knowledge is thought to concern perfect geometrical forms, whereas the embodiment of such forms in the natural world may be imperfect. There thus arises an apparent mismatch between mathematical concepts and physical reality. We propose that the problem can be solved by emphasizing the ways in which the (...) brain can transform and organize its perceptual intake. It is not necessary for a geometrical form to be perfectly instantiated in order for perception of such a form to be the basis of a geometrical concept. (shrink)

I address the problem of the distinction between semantic and conceptual representations from general considerations about how to distinguish a representational kind. I consider three different ways of telling representational kinds apart – in terms of structure, processing and content – and I examine if semantic representations may constitute a distinct kind with respect to each of them. I argue that the best options for semantic representation to be regarded as a distinct representational kind with respect to each of the (...) three criteria conflict with each other, since it appears respectively as an atomic representation, as a sort of procedural rule or as a structured complex. (shrink)

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In (...) this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism and connectionism on the other. We defend the relevance to cognitive science of both computation, in a generic sense that we fully articulate for the first time, and information processing, in three important senses of the term. Our account advances some foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects. (shrink)

The core of the language of thought program is the claim that thinking is the manipulation of symbols according to rules. Yet LOT has said little about symbol natures, and existing accounts are highly controversial. This is a major flaw at the heart of the LOT program: LOT requires an account of symbol natures to naturalize intentionality, to determine whether the brain even engages in symbol manipulations, and to understand how symbols relate to lower-level neurocomputational states. This paper provides the (...) much-needed theory of symbols, and in doing so, alters the LOT program in significant respects. (shrink)

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artificial life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. We propose to explicitly integrate (...) the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however, resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways. (shrink)

This paper considers an orectic penetration hypothesis which says that desires and desire-like states may influence perceptual experience in a non-externally mediated way. This hypothesis is clarified with a definition, which serves further to distinguish the interesting target phenomenon from trivial and non-genuine instances of desire-influenced perception. Orectic penetration is an interesting possible case of the cognitive penetrability of perceptual experience. The orectic penetration hypothesis is thus incompatible with the more common thesis that perception is cognitively impenetrable. It is of (...) importance to issues in the philosophy of mind and cognitive science, epistemology, and general philosophy of science. The plausibility of orectic perception can be motivated by some classic experimental studies, and some new experimental research inspired by those same studies. The general suggestion is that orectic penetration thus defined, and evidenced by the relevant studies, cannot be deflected by the standard strategies of the cognitive impenetrability theorist. (shrink)

The concept of modularity has loomed large in philosophy of psychology since the early 1980s, following the publication of Fodor’s landmark book The Modularity of Mind (1983). In the decades since the term ‘module’ and its cognates first entered the lexicon of cognitive science, the conceptual and theoretical landscape in this area has changed dramatically. Especially noteworthy in this respect has been the development of evolutionary psychology, whose proponents adopt a less stringent conception of modularity than the one advanced by (...) Fodor, and who argue that the architecture of the mind is more pervasively modular than Fodor claimed. Where Fodor (1983, 2000) draws the line of modularity at the relatively low-level systems underlying perception and language, post-Fodorian theorists such as Sperber (2002) and Carruthers (2006) contend that the mind is modular through and through, up to and including the high-level systems responsible for reasoning, planning, decision making, and the like. The concept of modularity has also figured in recent debates in philosophy of science, epistemology, ethics, and philosophy of language—further evidence of its utility as a tool for theorizing about mental architecture. (shrink)

Fodor advocates a view of cognitive processes as computations defined over the language of thought (or Mentalese). Even among those who endorse Mentalese, considerable controversy surrounds its representational format. What semantically relevant structure should scientific psychology attribute to Mentalese symbols? Researchers commonly emphasize logical structure, akin to that displayed by predicate calculus sentences. To counteract this tendency, I discuss computational models of navigation drawn from probabilistic robotics. These models involve computations defined over cognitive maps, which have geometric rather than logical (...) structure. They thereby demonstrate the possibility of rational cognitive processes in an exclusively non-logical representational medium. Furthermore, they offer much promise for the empirical study of animal navigation. (shrink)

Roughly speaking, computationalism says that cognition is computation, or that cognitive phenomena are explained by the agent‘s computations. The cognitive processes and behavior of agents are the explanandum. The computations performed by the agents‘ cognitive systems are the proposed explanans. Since the cognitive systems of biological organisms are their nervous 1 systems (plus or minus a bit), we may say that according to computationalism, the cognitive processes and behavior of organisms are explained by neural computations. Some people might prefer to (...) say that cognitive systems are ―realized‖ by nervous systems, and thus that—according to computationalism—cognitive computations are ―realized‖ by neural processes. In this paper, nothing hinges on the nature of the relation between cognitive systems and nervous systems, or between computations and neural processes. For present purposes, if a neural process realizes a computation, then that neural process is a computation. Thus, I will couch much of my discussion in terms of nervous systems and neural computation.1 Before proceeding, we should dispense with a possible red herring. Contrary to a common assumption, computationalism does not stand in opposition to connectionism. Connectionism, in the most general and common sense of the term, is the claim that cognitive phenomena are explained (at some level and at least in part) by the processes of neural networks. This is a truism, supported by most neuroscientific evidence. Everybody ought to be a connectionist in this general sense. The relevant question is, are neural processes computations? More precisely, are the neural processes to be found in the nervous systems of organisms computations? Computationalists say ―yes‖, anti-computationalists say ―no‖. This paper investigates whether any of the arguments on offer against computationalism have a chance at knocking it off.2 Ever since Warren McCulloch and Walter Pitts (1943) first proposed it, computationalism has been subjected to a wide range of objections.. (shrink)

The commentators do not contest the target article's claim that there is no compelling evidence of theory of mind in primates, and recent empirical studies further support this view. If primates lack theory of mind, they may still have other behavior control mechanisms that are adaptive in complex social environments. The Somatic Marker Mechanism (SMM) is a candidate, but the SMM hypothesis postulates a much weaker effect of natural selection on social cognition than the theory of mind hypothesis (on inputs (...) to cognitive mechanisms, not on the mechanisms themselves), and there is currently no evidence that it is specific to social stimuli or to primates. “Two Guesser” training would make the goggles test too chauvinistic, and in its current form the goggles problem could not be solved by physical matching because, while wearing goggles, an individual cannot see itself seeing. (shrink)

An important part of David Hume’s work is his attempt to put the natural sciences on a firmer foundation by introducing the scientific method into the study of human nature. This investigation resulted in a novel understanding of the mind, which in turn informed Hume’s critical evaluation of the scope and limits of the scientific method as such. However, while these latter reflections continue to influence today’s philosophy of science, his theory of mind is nowadays mainly of interest in terms (...) of philosophical scholarship. This paper aims to show that, even though Hume’s recognition in the cognitive sciences has so far been limited, there is an opportunity to reevaluate his work in the context of more recent scientific developments. In particular, it is argued that we can gain a better understanding of his overall philosophy by tracing the ongoing establishment of the enactive approach. In return, this novel interpretation of Hume’s ‘science of man’ is used as the basis for a consideration of the current and future status of the cognitive sciences. (shrink)

Computationalism has been the mainstream view of cognition for decades. There are periodic reports of its demise, but they are greatly exaggerated. This essay surveys some recent literature on computationalism. It concludes that computationalism is a family of theories about the mechanisms of cognition. The main relevant evidence for testing it comes from neuroscience, though psychology and AI are relevant too. Computationalism comes in many versions, which continue to guide competing research programs in philosophy of mind as well as psychology (...) and neuroscience. Although our understanding of computationalism has deepened in recent years, much work in this area remains to be done. (shrink)

Perceptual content is conceptual. In this paper, some arguments against this thesis are examined and rebutted. The Richness argument, that we could not have concepts for all the colours, is queried: Doesn't the Munsell system give us such concepts? The argument that we can perceive colours and shapes without possessing the relevant concepts is rebutted: we cannot do this, but the kind of concept-possession that is relevant here is not intellectual but perceptual.

The use of “levels of abstraction” in philosophical analysis (levelism) has recently come under attack. In this paper, I argue that a refined version of epistemological levelism should be retained as a fundamental method, called the method of levels of abstraction. After a brief introduction, in section “Some Definitions and Preliminary Examples” the nature and applicability of the epistemological method of levels of abstraction is clarified. In section “A Classic Application of the Method ofion”, the philosophical fruitfulness of the new (...) method is shown by using Kant’s classic discussion of the “antinomies of pure reason” as an example. In section “The Philosophy of the Method of Abstraction”, the method is further specified and supported by distinguishing it from three other forms of “levelism”: (i) levels of organisation; (ii) levels of explanation and (iii) conceptual schemes. In that context, the problems of relativism and antirealism are also briefly addressed. The conclusion discusses some of the work that lies ahead, two potential limitations of the method and some results that have already been obtained by applying the method to some long-standing philosophical problems. (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)

Eliminative materialism (or eliminativism) is the radical claim that our ordinary, common-sense understanding of the mind is deeply wrong and that some or all of the mental states posited by common-sense do not actually exist. Descartes famously challenged much of what we take for granted, but he insisted that, for the most part, we can be confident about the content of our own minds. Eliminative materialists go further than Descartes on this point, since they challenge of the existence of various (...) mental states that Descartes took for granted. (shrink)

Combining physics, mathematics and computer science, quantum computing and its sister discipline of quantum information have developed in the past few decades from visionary ideas to two of the most fascinating areas of quantum theory. General interest and excitement in quantum computing was initially triggered by Peter Shor (1994) who showed how a quantum algorithm could exponentially “speed-up” classical computation and factor large numbers into primes far more efficiently than any (known) classical algorithm. Shor’s algorithm was soon followed by several (...) other algorithms that aimed to solve combinatorial and algebraic problems, and in the years since theoretical study of quantum systems serving as computational devices has achieved tremendous progress. Common belief has it that the implementation of Shor’s algorithm on a large scale quantum computer would have devastating consequences for current cryptography protocols which rely on the premise that all known classical worst-case algorithms for factoring take time exponential in the length of their input (see, e.g., Preskill 2005). Consequently, experimentalists around the world are engaged in attempts to tackle the technological difficulties that prevent the realisation of a large scale quantum computer. But regardless whether these technological problems can be overcome (Unruh 1995; Ekert and Jozsa 1996; Haroche and Raimond 1996), it is noteworthy that no proof exists yet for the general superiority of quantum computers over their classical counterparts. -/- The philosophical interest in quantum computing is manifold. From a social-historical perspective, quantum computing is a domain where experimentalists find themselves ahead of their fellow theorists. Indeed, quantum mysteries such as entanglement and nonlocality were historically considered a philosophical quibble, until physicists discovered that these mysteries might be harnessed to devise new efficient algorithms. But while the technology for harnessing the power of 50–100 qubits (the basic unit of information in the quantum computer) is now within reach (Preskill 2018), only a handful of quantum algorithms exist, and the question of whether these can truly outperform any conceivable classical alternative is still open. From a more philosophical perspective, advances in quantum computing may yield foundational benefits. For example, it may turn out that the technological capabilities that allow us to isolate quantum systems by shielding them from the effects of decoherence for a period of time long enough to manipulate them will also allow us to make progress in some fundamental problems in the foundations of quantum theory itself. Indeed, the development and the implementation of efficient quantum algorithms may help us understand better the border between classical and quantum physics (Cuffaro 2017, 2018a; cf. Pitowsky 1994, 100), and perhaps even illuminate fundamental concepts such as measurement and causality. Finally, the idea that abstract mathematical concepts such as computability and complexity may not only be translated into physics, but also re-written by physics bears directly on the autonomous character of computer science and the status of its theoretical entities—the so-called “computational kinds”. As such it is also relevant to the long-standing philosophical debate on the relationship between mathematics and the physical world. (shrink)

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.

This paper deals with the question: how is computation best individuated? -/- 1. The semantic view of computation: computation is best individuated by its semantic properties. 2. The causal view of computation: computation is best individuated by its causal properties. 3. The functional view of computation: computation is best individuated by its functional properties. -/- Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated (...) semantically. I criticize the reasons in support of this view and its presupposition of representation and semantics. Furthermore, I argue that the only justified appeal to a representational individuation of computation might be that it is partly individuated by implicit intrinsic representations. (shrink)

This commentary elaborates on Gray's conclusion that his neurophysiological model of consciousness might explain how consciousness arises from the brain, but does not address how consciousness evolved, affects behaviour or confers survival value. The commentary argues that such limitations apply to all neurophysiological or other third-person perspective models. To approach such questions the first-person nature of consciousness needs to be taken seriously in combination with third-person models of the brain.

The aim of this paper is to demonstrate that empirically delimited structures of mind are also differentiable by means of systematic logical analysis. In the sake of this aim, the paper first summarizes Demetriou's theory of cognitive organization and growth. This theory assumes that the mind is a multistructural entity that develops across three fronts: the processing system that constrains processing potentials, a set of specialized structural systems (SSSs) that guide processing within different reality and knowledge domains, and a hypecognitive (...) system that monitors and controls the functioning of all other systems. In the second part the paper focuses on the SSSs, which are the target of our logical analysis, and it summarizes a series of empirical studies demonstrating their autonomous operation. The third part develops the logical proof showing that each SSS involves a kernel element that cannot be reduced to standard logic or to any other SSS. The implications of this analysis for the general theory of knowledge and cognitive development are discussed in the concluding part of the paper. (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)

This paper compares and contrasts Mencius's moral philosophy with recent development in cognitive science regarding mental capacity to understand moral rules and principles. Several cognitive scientists argue that the human mind has innate cognitive and emotive foundations of morality. In this paper, Mencius's moral theory is interpreted from the perspective of faculty psychology and cognitive modularity, a theoretical hypothesis in cognitive science in which the mind is understood as a system of specialized mental components. Specifically, Mencius's Four Beginnings (the basic (...) human emotions that serve as the foundations of morality) are interpreted as vertical faculties, comparable to Scottish philosopher Thomas Reid's moral faculties. (shrink)

I offer an explication of the notion of computer, grounded in the practices of computability theorists and computer scientists. I begin by explaining what distinguishes computers from calculators. Then, I offer a systematic taxonomy of kinds of computer, including hard-wired versus programmable, general-purpose versus special-purpose, analog versus digital, and serial versus parallel, giving explicit criteria for each kind. My account is mechanistic: which class a system belongs in, and which functions are computable by which system, depends on the system's mechanistic (...) properties. Finally, I briefly illustrate how my account sheds light on some issues in the history and philosophy of computing as well as the philosophy of mind. (shrink)

We outline a theory of one puzzling aspect of human cognition: a tendency to exaggerate the degree to which agency is manifested in the world. We call this over‐coherent thinking. We use Pylyshyn's idea of cognitive penetrability to help characterize this notion. We argue that this kind of thinking is essentially narrative in form rather than theoretical. We develop a theory of the relation between the degree of narrativity in a representation and its aptness to represent, and to express, mind. (...) We review the prospects for several theories about how over‐coherent thinking gains a purchase on motivation. We argue that progress in this difficult area may require the abandonment of a categorical belief/imagination distinction in favour of vaguely specified clusterings in a many‐dimensional cognitive space. We conclude with the idea that an error‐prone system for the retention of ideas that are low in some of the characteristics generally thought desirable in belief might emerge as a result of an arms‐race between deceivers and deceiver‐detectors. (shrink)

A taped conversational interview with Daniel Dennett and Bill Uzgalis covers a wide range of topics arising from Dennett’s thoughts about computing and human beings. The background of Dennett’s work is explored as are his views about mind-brain identity theory, artificial intelligence, functionalism, human exceptionalism, animal culture, language, pain, freedom and determinism, and quality of life.

Summary Searle claims that for a machine to have intentional states it is not sufficient that a formal programme be instantiated. Various types of objections to this claim have been brought up by Searle's critics. Searle's replies to some of these objections are analysed. It turns out that it is more to these objections than Searle wants to make us believe. What is crucial, however, is that Searle's „Gedankenexperiment results in a dilemma. At the outset of the dilemma there are (...) two ways of not understanding. According to one of these ways a person (Searle's homunculus) does not understand something without knowing that s/he does not understand. While in the other mode the person knows that s/he doesn't understand. In the first case the inference from facts about the homunculus to facts about the computer is not valid whereas in the second case one would attribute mental states to the computer. Thereby Searle's claim turns out to be unfounded. (shrink)

In recent years evolutionary psychologists have developed and defended the Massive Modularity Hypothesis, which maintains that our cognitive architecture—including the part that subserves ‘central processing’ —is largely or perhaps even entirely composed of innate, domain-specific computational mechanisms or ‘modules’. In this paper I argue for two claims. First, I show that the two main arguments that evolutionary psychologists have offered for this general architectural thesis fail to provide us with any reason to prefer it to a competing picture of the (...) mind which I call the Library Model of Cognition. Second, I argue that this alternative model is compatible with the central theoretical and methodological commitments of evolutionary psychology. Thus I argue that, at present, the endorsement of the Massive Modularity Hypothesis by evolutionary psychologists is both unwarranted and unmotivated. (shrink)

The aim of this article is to strengthen links between cognitive brain research and formal logic. The work covers three fundamental sorts of logical inferences: reasoning in the propositional calculus, i.e. inferences with the conditional “if...then”, reasoning in the predicate calculus, i.e. inferences based on quantifiers such as “all”, “some”, “none”, and reasoning with n-place relations. Studies with brain-damaged patients and neuroimaging experiments indicate that such logical inferences are implemented in overlapping but different bilateral cortical networks, including parts of the (...) fronto-temporal cortex, the posterior parietal cortex, and the visual cortices. I argue that these findings show that we do not use a single deterministic strategy for solving logical reasoning problems. This account resolves many disputes about how humans reason logically and why we sometimes deviate from the norms of formal logic. (shrink)

This paper examines the idea, commonly presupposed but seldom explicitly stated in discussions of certain philosophical problems, that the objects and phenomena of the world are structured in a hierarchy of "levels", from the bottom level of microparticles to the levels of cells and biological organisms and then to the levels of creatures with mentality and social groups of such creatures. Parallel to this "layered model" of the natural world is an ordering of the sciences, with physics as our "basic" (...) science and the "special sciences" forming a ladder-like hierarchy, from chemistry to biology to psychology and the social sciences, all grounded in basic physics. Focusing on two formulations of this model, the emergentist model of C. Lloyd Morgan and the reductionist model due to Paul Oppenheim and Hilary Putnam, the paper discusses such questions as these:What makes a given level of objects "higher" or "lower" than another? What makes a given property "higher" or "lower" than another property. Are objects and properties always comparable with respect to "higher" and "lower"? Can an overarching hierarchy of entities and properties be developed that comprehends the entire natural order? The issues turn out to be quite complex, and no definitive general conclusions are reached. (shrink)

Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. Zenon (...) Pylyshyn, in his influential book Computation and Cognition, claimed that both Newell and Fodor deeply influenced his ideas on cognition as computation. This probably added to the confusion, as many people still consider Pylyshyn’s book as paradigmatic of the computational approach in the study of the mind. Since then, cognitive scientists, AI researchers and also philosophers of the mind have been asked to take sides on different “paradigms” that have from time to time been proposed as opponents of (classic or symbolic) computationalism. Examples of such oppositions are: -/- computationalism vs. connectionism, computationalism vs. dynamical systems, computationalism vs. situated and embodied cognition, computationalism vs. behavioural and evolutionary robotics. -/- Our preliminary claim in section 1 is that computationalism should not be identified with what we would call the “paradigm (based on the metaphor) of the computer” (in the following, PoC). PoC is the (rather vague) statement that the mind functions “as a digital computer”. Actually, PoC is a restrictive version of computationalism, and nobody ever seriously upheld it, except in some rough versions of the computational approach and in some popular discussions about it. Usually, PoC is used as a straw man in many arguments against computationalism. In section 1 we look in some detail at PoC’s claims and argue that computationalism cannot be identified with PoC. In section 2 we point out that certain anticomputationalist arguments are based on this misleading identification. In section 3 we suggest that the view of the levels of explanation proposed by David Marr could clarify certain points of the debate on computationalism. In section 4 we touch on a controversial issue, namely the possibility of developing a notion of analog computation, similar to the notion of digital computation. A short conclusion follows in section 5. (shrink)

I discuss the philosophical implications that the rising new science of quantum computing may have on the philosophy of computer science. While quantum algorithms leave the notion of Turing-Computability intact, they may re-describe the abstract space of computational complexity theory hence militate against the autonomous character of some of the concepts and categories of computer science.

This review essay critically discusses Andre Kukla's Methods of theoretical psychology. It is argued that Kukla mistakenly tries to build his case for theorizing in psychology as a separate discipline on a dubious distinction between theory and observation. He then argues that the demise of empiricism implies a return of some form of rationalism, which entails an autonomous role for theorizing in psychology. Having shown how this theory-observation dichotomy goes back to traditional and largely abandoned ideas in epistemology, an alternative (...) is presented in the guise of the pragmatist or functionalist tradition, where the interdependence of theory, observation and action is emphasized and the positivist dichotomy of pure observations and pure theory is rejected. Furthermore, we show how recent work on "active" perception supports the functionalist approach. Although the authors agree with Kukla that theory has a legitimate place in psychology, it is suggested that he needlessly limits its scope to autonomous domain-neutral theorizing, and that broadening its perspective to analyzing the presuppositions and implications of empirical work is a more fruitful approach. In fact, the attempt to find the epistemological and philosophical implications of empirical work in perception that is sketched in this review essay is, in the authors' view, a case of theorizing in psychology. (shrink)

We respond to Morris and Richardson 's claim that Pickering and Chater's arguments about the lack of a relation between cognitive science and folk psychology are flawed. We note that possible controversies about the appropriate uses for the two terms do not affect our arguments. We then address their claim that computational explanation of knowledge-rich processes has proved possible in the domains of problem solving, scientific discovery, and reasoning. We argue that, in all cases, computational explanation is only possible for (...) aspects of those processes that do not make reference to general knowledge. We conclude that consideration of the issues raised by Morris and Richardson reinforces our original claim that there are two fundamentally distinct projects for understanding the mind, one based on justification, and the other on computational explanation, and that these apply to non-overlapping aspects of mental life. (shrink)

This paper presents a position called Scheme-based Alethic Realism, which reconciles a realist position on the nature of truth with a pluralistic Kantian perspective that allows for multiple environments in which truthmaking relationships are established. We argue that truthmaking functions are constrained by a stable phenomenal world and a stable cognitive architecture. This account takes truth as normatively distinct from epistemic justification while relativizing the truth conditions of our statements to what we call Frameworks. The pluralistic aspect allows that these (...) stable elements, while constraining representational and linguistic schemes, do not define a single framework for truthmaking relations. We strengthen this position by considering themes on situated rational agency from cognitive science and artificial intelligence, arguing that whatever enables or supports rational action within a particular environment must figure into some account of truth and truthmaking, and vice versa. (shrink)