I analyze Wittgenstein’s criticism of several assumptions that are crucial for a large part of cognitive science. These involve the concepts of computational processes in the brain which cause mental states and processes, the algorithmic processing of information in the brain (neural system), the brain as a machine, psycho physical parallelism, the thinking machine, as well as the confusion of rule following with behavior in accordance with the rule. In my opinion, the theorists of cognitive science have not yet seriously (...) considered Wittgenstein’s criticism so they, quite surprisingly, frequently confuse the question “how does it work?” with “what does it do?” But their most “deleterious” mistake is their confusion of the internal computational (or parallel) processes taking place in the brain (which possibly cause mental states) with socially-based, everyday criteria of recognition and classification of, and knowledge about, the content of mental states. (shrink)

In this essay I analyse Wittgenstein’s criticism of several assumptions that are crucial for a large part of cognitive science. These involve the concepts of computational processes in the brain which cause mental states and processes, the algorithmic processing of information in the brain , the brain as a machine, psychophysical parallelism, the thinking machine, as well as the confusion of rule following with behaviour in accordance with the rule. In my opinion, the theorists of cognitive science have not yet (...) seriously considered Wittgenstein’s criticism so they, quite surprisingly, frequently confuse the question “how does it work?” with “what does it do?” But their most “deleterious” mistake is their confusion of the internal computational processes taking place in the brain with socially-based, everyday criteria of recognition and classification of, and knowledge about, the content of mental states. (shrink)

It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks unorganised machines. By the application of what he described as appropriate interference, mimicking education an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of neurons is sufficient. Turing proposed simulating both the behaviour of the (...) network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)

On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of intelligence. (...) This is because the features of intelligence upon which it relies are resourcefulness and a critical attitude to one''s habitual responses; thus the test''s applicablity is not restricted to any particular species, nor does it presume any particular capacities. This is more appropriate because the question under consideration is what would count as machine intelligence. The first test realizes a possibility that philosophers have overlooked: a test that uses a human''s linguistic performance in setting an empirical test of intelligence, but does not make behavioral similarity to that performance the criterion of intelligence. Consequently, the first test is immune to many of the philosophical criticisms on the basis of which the (so-called) `Turing Test'' has been dismissed. (shrink)

It is not widely realised that Turing was probably the first person to consider building computing machines out of simple, neuron-like elements connected together into networks in a largely random manner. Turing called his networks 'unorganised machines'. By the application of what he described as 'appropriate interference, mimicking education' an unorganised machine can be trained to perform any task that a Turing machine can carry out, provided the number of 'neurons' is sufficient. Turing proposed simulating both the behaviour of the (...) network and the training process by means of a computer program. We outline Turing's connectionist project of 1948. (shrink)

Harnad''s proposed robotic upgrade of Turing''s Test (TT), from a test of linguistic capacity alone to a Total Turing Test (TTT) of linguisticand sensorimotor capacity, conflicts with his claim that no behavioral test provides even probable warrant for attributions of thought because there is no evidence of consciousness besides private experience. Intuitive, scientific, and philosophical considerations Harnad offers in favor of his proposed upgrade are unconvincing. I agree with Harnad that distinguishing real from as if thought on the basis of (...) (presence or lack of) consciousness (thus rejecting Turing (behavioral) testing as sufficient warrant for mental attribution)has the skeptical consequence Harnad accepts — there is in factno evidence for me that anyone else but me has a mind. I disagree with hisacceptance of it! It would be better to give up the neo-Cartesian faith in private conscious experience underlying Harnad''s allegiance to Searle''s controversial Chinese Room Experiment than give up all claim to know others think. It would be better to allow that (passing) Turing''s Test evidences — evenstrongly evidences — thought. (shrink)

This paper concerns Alan Turing’s ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Gödel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of a human mathematician, for (...) Turing, was not a computable sequence (i.e., one that could be generated by a Turing machine). Since computers only contained a finite number of instructions (or programs), one might argue, they could not reproduce human intelligence. Turing called this the “mathematical
objection” to his view that machines can think. Logico-mathematical reasons, stemming from his own work, helped to convince Turing that it should be possible to reproduce human intelligence, and eventually compete with it, by developing the appropriate kind of digital computer. He felt it
should be possible to program a computer so that it could learn or discover new rules, overcoming the limitations imposed by the incompleteness and undecidability results in the same way that human
mathematicians presumably do. (shrink)

This article questions social constructionists' claims to introduce Wittgenstein's philosophy to psychology. The philosophical fiction of a neonate Crusoe is introduced to cast doubt on the interpretations and use of the private language argument to support a new psychology developed by the constructionists. It is argued that a neonate Crusoe's viability in philosophy and apparent absence in psychology offends against the integrity of the philosophical contribution Wittgenstein might make to psychology. The consequences of accepting Crusoe's viability are explored as they (...) appear in both philosophy and psychology. (shrink)

Nature's experiments in isolation—the wild boy of Aveyron, Genie, their name is hardly legion—are by their nature illusive. Helen Keller, blind and deaf from her 18th month and isolated from language until well into her sixth year, presents a unique case in that every stage in her development was carefully recorded and she herself, graduate of Radcliffe College and author of 14 books, gave several careful and insightful accounts of her linguistic development and her cognitive and sensory situation. Perhaps because (...) she is masked, and enshrined, in William Gibson's mythic and false Miracle worker, cognitive scientists have yet to come to terms with this richly enlightening, albeit anecdotal, resource. (shrink)

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by (...) Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of _nonclassical_ computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a number of foundational arguments that are commonly rehearsed in cognitive science, and gesture towards a new class of cognitive models. (shrink)