The Computational Theory Of Mind

What is it to have a concept? What is it to make an inference? What is it to be rational? On the basis of recent developments in semantics, a number of authors have embraced answers to these questions that have radically counterintuitive consequences, for example: • One can rationally accept self-contradictory propositions (e.g. Smith is a composer and Smith is not a composer).• Psychological states are causally inert: beliefs and desires do nothing. • The mind cannot be understood in terms of folk-psychological concepts (e.g. belief, desire, intention). • One can have a single concept without having any others: an otherwise conceptless creature could grasp the concept of justice or of the number seven. • Thoughts are sentence-tokens, and thought-processes are driven by the syntactic, not the semantic, properties of those tokens. In the first half of Conceptual Atomism and the Computational Theory of Mind, John-Michael Kuczynski argues that these implausible but widely held views are direct consequences of a popular doctrine known as content-externalism, this being the view that the contents of one's mental states are constitutively dependent on facts about the external world. Kuczynski shows that content-externalism involves a failure to distinguish between, on the one hand, what is literally meant by linguistic expressions and, on the other hand, the information that one must work through to compute the literal meanings of such expressions. The second half of the present work concerns the Computational Theory of Mind (CTM). Underlying CTM is an acceptance of conceptual atomism – the view that a creature can have a single concept without having any others – and also an acceptance of the view that concepts are not descriptive (i.e. that one can have a concept of a thing without knowing of any description that is satisfied by that thing). Kuczynski shows that both views are false, one reason being that they presuppose the truth of content-externalism, another being that they are incompatible with the epistemological anti-foundationalism proven correct by Wilfred Sellars and Laurence Bonjour. Kuczynski also shows that CTM involves a misunderstanding of terms such as “computation”, “syntax”, “algorithm” and “formal truth”; and he provides novel analyses of the concepts expressed by these terms. (Series A)

The Computational Theory of Mind says that the mind is a computing system. It has a long history going back to the idea that thought is a kind of computation. Its modern incarnation relies on analogies with contemporary computing technology and the use of computational models. It comes in many versions, some more plausible than others. This Element supports the theory primarily by its contribution to solving the mind-body problem, its ability to explain mental phenomena, and the success of computational modelling and artificial intelligence. To be turned into an adequate theory, it needs to be made compatible with the tractability of cognition, the situatedness and dynamical aspects of the mind, the way the brain works, intentionality, and consciousness.

A defense of the computational explanation of cognition that relies on mechanistic philosophy of science and advocates for explanatory pluralism. In this book, Marcin Milkowski argues that the mind can be explained computationally because it is itself computational—whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music. Defending the computational explanation against objections to it—from John Searle and Hilary Putnam in particular—Milkowski writes that computationalism is here to stay but is not what many have taken it to be. It does not, for example, rely on a Cartesian gulf between software and hardware, or mind and brain. Milkowski's mechanistic construal of computation allows him to show that no purely computational explanation of a physical process will ever be complete. Computationalism is only plausible, he argues, if you also accept explanatory pluralism. Milkowski sketches a mechanistic theory of implementation of computation against a background of extant conceptions, describing four dissimilar computational models of cognition. He reviews other philosophical accounts of implementation and computational explanation and defends a notion of representation that is compatible with his mechanistic account and adequate vis à vis the four models discussed earlier. Instead of arguing that there is no computation without representation, he inverts the slogan and shows that there is no representation without computation—but explains that representation goes beyond purely computational considerations. Milkowski's arguments succeed in vindicating computational explanation in a novel way by relying on mechanistic theory of science and interventionist theory of causation.

Jerry Fodor argues against the widely held view that mental processes are largely computations, that the architecture of cognition is massively modular, and that the explanation of our innate mental structure is basically Darwinian.

Computational approaches dominate contemporary cognitive science, promising a unified, scientific explanation of how the mind works. However, computational approaches raise major philosophical and scientific questions. In what sense is the mind computational? How do computational approaches explain perception, learning, and decision making? What kinds of challenges should computational approaches overcome to advance our understanding of mind, brain, and behaviour? The Routledge Handbook of the Computational Mind is an outstanding overview and exploration of these issues and the first philosophical collection of its kind. Comprising thirty-five chapters by an international team of contributors from different disciplines, the Handbook is organised into four parts: History and future prospects of computational approaches Types of computational approach Foundations and challenges of computational approaches Applications to specific parts of psychology. Essential reading for students and researchers in philosophy of mind, philosophy of psychology, and philosophy of science, The Routledge Handbook of the Computational Mind will also be of interest to those studying computational models in related subjects such as psychology, neuroscience, and computer science.

Essay from the year 2008 in the subject Psychology - General, grade: 1,7, University of Derby (Institut für Psychologie), course: Cognitive Psychology, language: English, abstract: In Psychology, many theories and models use process charts resembling circuit diagrams of technical devices. In this account, human behaviour and experience appears to be the result of processes taking place in the 'black box' named cognition. In this context, "computationalism is the view that computation [...] can offer an explanatory basis for cognition" (Davenport, 2008, p.1). The Computational Theory of Mind (CTM) has developed on this foundation, attempting to reveal what is inside this 'black box'. In contrast, human consciousness being a part of cognition (Harnad, 1994) seems to be beyond any scientific explanation. This essay will critically discuss the extent to which consciousness poses a problem for the CTM - regarding issues surrounding consciousness as an area of scientific study, the extent to which consciousness is explicable in computational terms, explanations of consciousness, and Dennett's (1991) different account to consciousness. It will be argued that consciousness does pose a major problem for the CTM, especially when it is conceptualised as subjective experience. It will conclude that Cognitive Science should presently focus only on certain aspects of consciousness, called the easy problems.

A new computationalist view of the mind that takes into account real-world issues of embodiment, interaction, physical implementation, and semantics.