What, in essence, characterizes the mind? According to Searle, the potential to be conscious provides the only definitive criterion. Thus, conscious states are unquestionably "mental"; "shallow unconscious" states are also "mental" by virtue of their capacity to be conscious (at least in principle); but there are no "deep unconscious mental states" - i.e. those rules and procedures without access to consciousness, inferred by cognitive science to characterize the operations of the unconscious mind are not mental at all. Indeed, according to (...) Searle, they have no ontological status - they are simply ways of describing some interesting facets of purely physiological phenomena. (shrink)

Social scientists have not integrated relevant knowledge from the biological sciences into their explanations of human behavior. This failure is due to a longstanding antireductionistic bias against the natural sciences, which follows on a commitment to the view that social facts must be explained by social laws. This belief has led many social scientists into the error of reifying abstract analytical constructs into entities that possess powers of agency. It has also led to a false nature-culture dichotomy that effectively undermines (...) the place of biology in social scientific explanation. Following the principles of methodological individualism, we show how behavioral explanations supported by data and theory from the neurosciences can be used to correct the errors of reificationist thinking in the social sciences. We outline a mechanistic approach to the explanation of human behavior with the hope that the biological sciences will begin to find greater acceptance among social scientists. (shrink)

Noam Chomsky and other linguists and psychologists have suggested that human linguistic behavior is somehow governed by a mental representation of a transformational grammar. Challenges to this controversial claim have often been met by invoking an explicitly computational perspective: It makes perfect sense to suppose that a grammar could be represented in the memory of a computational device and that this grammar could govern the device's use of a language. This paper urges, however, that the claim that humans are such (...) a device is unsupported and that it seems unlikely that linguists and psychologists really want to claim any such thing. Evidence for the linguists' original claim is drawn from three main sources: the explanation of language comprehension and other linguistic abilities; evidence for formal properties of the rules of the grammar; and the explanation of language acquisition. It is argued in this paper that none of these sources provides support for the view that the grammar governs language processing in something like the way a program governs the operation of a programmed machine. The computational approach, on the contrary, suggests ways in which linguistic abilities can be explained without the attribution of any explicit representation of rules governing linguistic behavior. (shrink)

Cognitive science typically postulates unconscious mental phenomena, computational or otherwise, to explain cognitive capacities. The mental phenomena in question are supposed to be inaccessible in principle to consciousness. I try to show that this is a mistake, because all unconscious intentionality must be accessible in principle to consciousness; we have no notion of intrinsic intentionality except in terms of its accessibility to consciousness. I call this claim the The argument for it proceeds in six steps. The essential point is that (...) intrinsic intentionality has aspectual shape: Our mental representations represent the world under specific aspects, and these aspectual features are essential to a mental state's being the state that it is. (shrink)

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...) described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity. Key Words: categorization; cognitive explanation; language; learning; reasoning; rules; similarity. (shrink)

There is a common-sense view of language, which is held by Wittgenstein, Strawson Dummett, Searle, Putnam, Lewis, Wiggins, and others. According to this view a language consists of conventions, it is rule-governed, rules are conventionalised, a language is learnt, there are general learning mechanisms in the brain, and so on. I shall call this view the ‘ ordinary language ’ view of language. Chomsky’s attitude towards this view of language has been rather negative, and his rejection of it is a (...) major motivation for the development of his own theory. In this paper I shall review Chomsky’s long-standing criticisms. I shall show that Chomsky’s argument does not constitute a dismissal of the ‘ordinarylanguage’ view of language, Chomsky’s conclusions about language do not follow from his argument, and the ‘ ordinary language ’ view actually points to a promising way for us to understand the true nature of language and mind. (shrink)

My purpose in this essay is to clarify the notion of explanation by computer simulation in artificial intelligence and cognitive science. My contention is that computer simulation may be understood as providing two different kinds of explanation, which makes the notion of explanation by computer simulation ambiguous. In order to show this, I shall draw a distinction between two possible ways of understanding the notion of simulation, depending on how one views the relation in which a computing system that performs (...) a cognitive task stands to the program that the system runs while performing that task. Next, I shall suggest that the kind of explanation that results from simulation is radically different in each case. In order to illustrate the difference, I will point out some prima facie methodological difficulties that need to be addressed in order to ensure that simulation plays a legitimate explanatory role in cognitive science, and I shall emphasize how those difficulties are very different depending on the notion of explanation involved. (shrink)