The idea that intentions make the difference between voluntary and non-voluntary behaviors is simple and intuitive. At the same time, we lack an understanding of how voluntary actions actually come about, and the unquestioned appeal to intentions as discrete causes of actions offers little if anything in the way of an answer. We cite evidence suggesting that the origin of actions varies depending on context and effector, and argue that actions emerge from a causal web in the brain, rather than (...) a central origin of intentional action. We argue that this causal web need not be confined to the central nervous system, and that proprioceptive feedback might play a counterintuitive role in the decision process. Finally we argue that the complex and dynamic origins of voluntary action and their interplay with the brain’s propensity to predict the immediate future are better studied using a dynamical systems approach. (shrink)

I argue against traditional virtue epistemology on which knowledge is a success due to a competence to believe truly, by revealing an in-principle problem with the traditional virtue epistemologist’s explanation of Gettier cases. The argument eliminates one of the last plausible explanation of Gettier cases, and so of knowledge, in terms of non-factive mental states and non-mental conditions. I then I develop and defend a different kind of virtue epistemology, on which knowledge is an exercise of a competence to know. (...) I show how the account, while circular, is not viciously so. It explains both how knowledge is a mental state, as well as the relationship between knowledge and justification, including justified false beliefs and Gettier cases. Moreover, although direct virtue epistemology is compatible with many views on the nature of belief, it can explain how knowledge might be metaphysically more fundamental than belief as well. (shrink)

Argues from the possibility of basic intentional action to a non-propositional theory of knowing how. The argument supports a broadly Anscombean conception of the will as a capacity for practical knowledge.

Tyler Burge presents an original study of the most primitive ways in which individuals represent the physical world. By reflecting on the science of perception and related psychological and biological sciences, he gives an account of constitutive conditions for perceiving the physical world, and thus aims to locate origins of representational mind.

In this paper, I argue that there is a notion of 'counterfactual success' which stands to knowledge how as true belief stands to propositional knowledge. (I attempt to avoid the question of whether knowledge how is a type of propositional knowledge.).

Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these questions. Justifying the role of computation (...) requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that (a) computation can specify general patterns of causal organization, and (b) mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science. (shrink)

The reference class problem arises when we want to assign a probability to a proposition (or sentence, or event) X, which may be classified in various ways, yet its probability can change depending on how it is classified. The problem is usually regarded as one specifically for the frequentist interpretation of probability and is often considered fatal to it. I argue that versions of the classical, logical, propensity and subjectivist interpretations also fall prey to their own variants of the reference (...) class problem. Other versions of these interpretations apparently evade the problem. But I contend that they are all “no-theory” theories of probability - accounts that leave quite obscure why probability should function as a guide to life, a suitable basis for rational inference and action. The reference class problem besets those theories that are genuinely informative and that plausibly constrain our inductive reasonings and decisions. I distinguish a “metaphysical” and an “epistemological” reference class problem. I submit that we can dissolve the former problem by recognizing that probability is fundamentally a two-place notion: conditional probability is the proper primitive of probability theory. However, I concede that the epistemological problem remains. (shrink)

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)

Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes. It is shown that many particular choices among possible neurophysiological assumptions (...) are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under the other and gives the same results, although perhaps not in the same time. Various applications of the calculus are discussed. (shrink)

When cognitive scientists are looking for the neural basis of consciousness or the computational processes underlying vision, what are they looking to find? I argue for a new account of this explanatory project in cognitive science (and the special sciences more generally) on which it is best understood on close analogy with causal explanation in the special sciences. Causal explanations cite causal difference-makers: they explain how certain events causally depend on other events. Generative explanations cite generative difference-makers: they explain how (...) certain events obtain in virtue of (and so are generated by) other events. I show how that this generative difference-making account (GDM) extends well regarded developments in philosophical work on causal explanation, helps to usefully clarify and expands the hypothesis space of a key project in cognitive science – that of understanding how underlying nonmental processes give rise to the mental, including consciousness. In section 2, I develop GDM by close analogy with causal explanation, and locate both of them as species of a more general project in the special sciences: that of discovering what makes a difference to what. In section 3, I motivate GDM by contrasting it with other rival accounts, including correlationist, identity, and grounding accounts, as well as Carl Craver’s constitutive relevance account. In section 4, I tie all of the strands of the preceding discussion together to show how GDM provides a new and compelling response to the so-called hard problem of consciousness. (shrink)

I extend my direct virtue epistemology to explain how a knowledge-first framework can account for two kinds of positive epistemic standing, one tracked by externalists, who claim that the virtuous duplicate lacks justification, the other tracked by internalists, who claim that the virtuous duplicate has justification, and moreover that such justification is not enjoyed by the vicious duplicate. It also explains what these kinds of epistemic standing have to do with each other. I argue that all justified beliefs are good (...) candidates for knowledge, and are such because they are exercises of competences to know. However, there are two importantly different senses in which a belief may be a good candidate for knowledge, one corresponding to an externalist kind of justification and the other corresponding to an internalist one. I show how the account solves the new evil demon problem in a more satisfactory way than existing accounts. We end up with a view of knowledge, justification, and rationality that is plausible, motivated, and theoretically unified. (shrink)

Contrastive neuroimaging is often taken to provide evidence about the localization of cognitive functions. After canvassing some problems with this approach, I offer an alternative: neuroimaging gives evidence about regions of the brain that bear difference-making relationships to psychological processes of interest. I distinguish between the specificity and what I call the systematicity of a difference-making relationship, and I show how at least some neuroimaging experiments can give evidence for systematic difference-making.

The two major modern accounts of explanation are the causal and unification accounts. My aim in this paper is to provide a kind of unification of the causal and the unification accounts, by using the central technical apparatus of the unification account to solve a central problem faced by the causal account, namely, the problem of determining which parts of a causal network are explanatorily relevant to the occurrence of an explanandum. The end product of my investigation is a causal (...) account of explanation that has many of the advantages of the unification account. (shrink)

Many philosophers worry that the classical computational theory of mind (CTM) engenders epiphenomenalism. Building on Block’s (1990) discussion, I formulate a particularly troubling version of this worry. I then present a novel solution to CTM’s epiphenomenalist conundrum. I develop my solution within an interventionist theory of causal relevance. My solution departs substantially from orthodox versions of CTM. In particular, I reject the widespread picture of digital computation as formal syntactic manipulation.1.

The charge that anthropomorphizing nonhuman animals is a fallacy is itself largely misguided and mythic. Anthropomorphism in the study of animal behavior is placed in its original, theological context. Having set the historical stage, I then discuss its relationship to a number of other, related issues: the role of anecdotal evidence, the taxonomy of related anthropomorphic claims, its relationship to the attribution of psychological states in general, and the nature of the charge of anthropomorphism as a categorical claim. I then (...) argue that the categorical reading of anthropomorphism cannot work and that it misrepresents what is being claimed when one claims that traits are shared between humans and nonhumans. We should think of such claims not as anthropomorphic per se– because that implies the trait is intrinsically human and only derivatively nonhuman. Instead, traits shared with mammals are mammalomorphic, for example, or primatomorphic when shared by primates. (shrink)

I develop a new account of perception on which it is metaphysically and explanatorily prior to illusion, hallucination, and perceptual experience. I argue that this view can rival the mainstream experience-first representationalist approach in explanatory power by using competences as a key theoretical tool: it can help to explain the nature of perception, how illusion and hallucination depend on it, and how cognitive science can help to explain in virtue of what we perceive. According to the Competence View, perception is (...) a kind of target-oriented activity that manifests the agent’s perceptual competence. This characterization of perception helps to explain the role of the subject in perception, as well as how perception has accuracy conditions. Illusion and hallucination are explained as degenerate exercises of perceptual competences. Lastly, I show the Competence View provides a flexible and robust framework for investigation in cognitive science. (shrink)

In this paper I reconstruct and evaluate the validity of two versions of causal exclusion arguments within the theory of causal Bayes nets. I argue that supervenience relations formally behave like causal relations. If this is correct, then it turns out that both versions of the exclusion argument are valid when assuming the causal Markov condition and the causal minimality condition. I also investigate some consequences for the recent discussion of causal exclusion arguments in the light of an interventionist theory (...) of causation such as Woodward's (2003) and discuss a possible objection to my causal Bayes net reconstruction. (shrink)

Abstract Mental representations, Swiatczak (Minds Mach 21:19–32, 2011) argues, are fundamentally biochemical and their operations depend on consciousness; hence the computational theory of mind, based as it is on multiple realisability and purely syntactic operations, must be wrong. Swiatczak, however, is mistaken. Computation, properly understood, can afford descriptions/explanations of any physical process, and since Swiatczak accepts that consciousness has a physical basis, his argument against computationalism must fail. Of course, we may not have much idea how consciousness (itself a rather (...) unclear plurality of notions) might be implemented, but we do have a hypothesis—that all of our mental life, including consciousness, is the result of computational processes and so not tied to a biochemical substrate. Like it or not, the computational theory of mind remains the only game in town. Content Type Journal Article Pages 1-8 DOI 10.1007/s11023-012-9271-5 Authors David Davenport, Computer Engineering Department, Bilkent University, 06800 Ankara, Turkey Journal Minds and Machines Online ISSN 1572-8641 Print ISSN 0924-6495. (shrink)