This article introduces three arguments that share a single conclusion: that a comprehensive science of language cannot describe relations of semantic reference, i.e. word–world relations. Spelling this out, if there is to be a genuine science of linguistic meaning, then a theory of meaning cannot involve assigning external, real-world, objects to names, nor sets of external objects to predicates, nor truth values to sentences. Most of the article tries to explain and defend this broad conclusion. The article also presents, in (...) a very limited way, a positive alternative to external-referent semantics for expressions. This alternative has two parts: first, that the meanings of words and sentences are mental instructions, not external things; second, that it is people who refer by using words and sentences, and word/sentence meanings play but a partial role in allowing speakers to talk about the world. (shrink)

John MacFarlane has made relativism popular again. Focusing just on his original discussion, I argue that the data he uses to motivate the position do not, in fact, motivatie it at all. Many of the points made here have since been made, independently, by Hermann Cappelen and John Hawthorne, in their book Relativism and Monadic Truth.

The externalist examples of Burge, Putnam etc. were offered as examples of how it is physically identical twins can differ in mental states such as belief, and little attention was paid to the interpretations the twins impose on their respective acoustic inputs. The received story today is that this form of interpretation—the semantic reading one assigns the sounds one hears—is the product of inference. The problem for this inferential model is simple to state: though the twins are physical doppelgangers and (...) don't differ in their acoustic inputs, they differ in the interpretations they impose on their respective inputs. I argue that the inferential model does not allow for how it is the twins arrive at these different interpretations. And, since the externalist examples are compelling, this tells against the inferential model. (shrink)

Is temporal representation constitutively necessary for perception? Tyler Burge (2010) argues that it is, in part because perception requires a form of memory sufficiently sophisticated as to require temporal representation. I critically discuss Burge’s argument, maintaining that it does not succeed. I conclude by reflecting on the consequences for the origins of temporal representation.

In this paper I outline an alternative to hermeneutic fictionalism, an alternative I call indifferentism, with the same advantages as hermeneutic fictionalism with respect to ontological issues but avoiding some of the problems that face fictionalism. The difference between indifferentism and fictionalism is this. The fictionalist about ordinary utterances of a sentence S holds, with more orthodox views, that the speaker in some sense commits herself to the truth of S. It is only that for the fictionalist this is truth (...) in the relevant fiction. According to the indifferentist, by contrast, we are simply non-committal – or indifferent – with respect to some aspects of what is literally said in our assertive utterances. (shrink)

This article defends the view that having a language just is knowing how to engage in communication with it. It also argues that, despite claims to the contrary, this view is compatible and complementary with the Chomskyan conception of language on which humans have languages in virtue of being in brain states realizing tacit knowledge of grammars for those languages.

Much of computational cognitive science construes human cognitive capacities as representational capacities, or as involving representation in some way. Computational theories of vision, for example, typically posit structures that represent edges in the distal scene. Neurons are often said to represent elements of their receptive fields. Despite the ubiquity of representational talk in computational theorizing there is surprisingly little consensus about how such claims are to be understood. The point of this chapter is to sketch an account of the nature (...) and function of representation in computational cognitive models. (shrink)