We argue that the most ambitious version of the mental files theory of singular thought, according to which mental files are a wide-ranging psychological natural kind underlying all and only singular thinking, is unsupported by the available psychological data. Nevertheless, critical examination of the theory from a psychological perspective opens up promising avenues for research, especially concerning the relationship between our perceptual capacity to individuate and track basic individuals, and our higher level capacities for singular thought.

This book discusses the two main construals of the explanatory goals of semantic theories. The first, externalist conception, understands semantic theories in terms of a hermeneutic and interpretive explanatory project. The second, internalist conception, understands semantic theories in terms of the psychological mechanisms in virtue of which meanings are generated. It is argued that a fruitful scientific explanation is one that aims to uncover the underlying mechanisms in virtue of which the observable phenomena are made possible, and that a scientific (...) semantics should be doing just that. If this is the case, then a scientific semantics is unlikely to be externalist, for reasons having to do with the subject matter and form of externalist theories. It is argued that semantics construed hermeneutically is nevertheless a valuable explanatory project. (shrink)

Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the “representation wars” of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing’s account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based (...) representational architecture with organism-relative contents that functions in the service of pragmatic success, not veridical representation. Finally, I argue that internal representation so understood is either impervious to the three anti-representationalist challenges I outline or can actively embrace them. (shrink)

This paper makes a phenomenological contribution to the distinction between personal and subpersonal types of explanation. I expound the little-known fact that Husserl gives an account of personal level explanation via his exposition of our capacity to express the understanding of another’s motivational nexus when we are in the personalistic attitude. I show that Husserl’s unique exposition of the motivational nexus conveys its concrete, internally coherent, and intentional nature, involving relationships amongst the sense contents of acts of consciousness. Moreover, the (...) motivational nexus is a generative space of possibility and choice. I show that, for these reasons, motivational explanation is not causal, nor deductive nomological, nor does it reduce to subpersonal explanation. I finish with the comment that the uniqueness of personal level explanation points towards the possibility that the human sciences ought also employ types of explanations not found in natural sciences. (shrink)

Hubert Dreyfus once noted that it would be difficult to ascertain whether Edmund Husserl had a computational theory of mind. I provide evidence that he had one. Both Steven Pinker and Steven Horst think that the computational theory of mind must have two components: a representational-symbolic component and a causal component. Bearing this in mind, we proceed to a close-reading of the sections of “On the Logic of Signs” wherein Husserl presents, if I’m correct, his computational theory of mind embedded (...) in a language of thought. My argument goes like this: the computational theory of mind is the idea, following Haugeland, that the mind comes prepackaged as, or is endogenously constrained to be, an automatic formal system; this explains, according to Husserl, why automatic trains of thought without logical intent resemble arguments exhibiting deductive structure with logical intent. In general, an automatic formal system yields true results provided that the syntactic symbols with which they compute are univocal and are semantically evaluable, and the mechanized inferences they perform are valid and preserve truth. These two conditions describe a computational cognitive process: the first condition connects representations to syntax, and the second condition uses the syntax, in inauthentic judging, to arrive at true conclusions through blind causality. Now, in point of textual fact, these are the conditions which Husserl attributes to our “natural psychological mechanism of symbolic inference” which typically yields true results. Since a formal system attributed to the “internal structure” of the mind, and guided by blind causality, just is the computational theory of mind, it follows, I think, that Husserl had a computational theory of mind. This computational theory is, moreover, embedded in a language of thought, since Husserl attributes a language-like form to our thoughts so that they may be mechanically processed. I conclude with a discussion of my results. (shrink)

In the paper I present an application of Jerzy Pelc’s functional semiotics to contemporary cognitive science. I argue that, even though the original theory addressed only linguistic representations, it can be fruitfully applied to mental representations. I show how Pelc’s distinction between use and usage helps us clarify the notion of mental representations and how it makes it immune to skeptical challenges presented in contemporary cognitive science literature.

When we think about what others believe and want, we are usually affected by what we know about their attitudes. If I’m aware that another person believes something, I have an opportunity to agree or disagree with it. If I think that another person wants something, I can endorse or disapprove of her desire. The importance of such reactions to attributed beliefs and desires has thus far been overlooked in philosophy of mind where the focus has been on explanatory and (...) predictive roles of attitude attribution. The primary goal of this thesis is to fill this lacuna and to articulate the indispensability of such reactions – agreement/disagreement and endorsement/disapproval – for social cognition. In the process of doing it I also show how these initial reactions ground certain further possible responses in intersubjective communication: manipulation, negotiation or adoption of attributed attitudes. The second aim of this thesis is to explicate what is it about belief and desire attributions that makes the responses I’ve described possible. Because one can agree or disagree both with beliefs and assertions and endorse or disapprove both desires and requests, I argue that we should understand belief attributions in terms of assertions and desire attributions in terms of requests. When we think what someone believes and wants, we treat her as a conversation partner because her attitudes call for the same responses as speech acts do, even if she hasn’t made any explicit assertion or request herself. In short, beliefs and desires have communicative significance. Given such significance, we can also see what one needs to take into consideration when attributing these attitudes to another. My answer in the thesis is that belief and desire attributions have to be grounded in facts about the behaviour and well-being of attributees and that these facts also constitute the nature of beliefs and desires. (shrink)

Recently, Piccinini and Craver have stated three theses concerning the relations between functional analysis and mechanistic explanation in cognitive sciences: No Distinctness: functional analysis and mechanistic explanation are explanations of the same kind; Integration: functional analysis is a kind of mechanistic explanation; and Subordination: functional analyses are unsatisfactory sketches of mechanisms. In this paper, I argue, first, that functional analysis and mechanistic explanations are sub-kinds of explanation by scientific (idealized) models. From that point of view, we must take into account (...) the tradeoff between the representational/explanatory goals of generality and precision that govern the practice of model-building. In some modeling scenarios, it is rational to maximize explanatory generality at the expense of mechanistic precision. This tradeoff allows me to put forward a problem for the mechanist position. If mechanistic modeling endorses generality as a valuable goal, then Subordination should be rejected. If mechanists reject generality as a goal, then Integration is false. I suggest that mechanists should accept that functional analysis can offer acceptable explanations of cognitive phenomena. (shrink)