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Lorna Mills and Sally McKay
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blingee by L.M.
The limitations of the Computational Theory of Mind might seem kind of obvious — while the syntactical structure of language may be formally discrete, context, memory and shifting paradigms are inherently necessary to the construction of meaning. A computer may be programmed with an extensive vocabulary of terms, but the meanings of each unit would have to be computed against a background environment of infinitely variable conditions. This framing problem has proven to be a serious set-back. As computational cognitive scientist Jerry Fodor points out...
The failure of AI is, in effect, the failure of the Classical Computational Theory of the Mind to perform well in practice. Failures of a theory to perform well in practice are much like failures to predict the right experimental outcomes (arguably, indeed, the latter is a special case of the former). For well-known Duhemian reasons, neither shows straight off that the theory in question is false. But neither, on the other hand, do they bode the theory in question an awful lot of good. If having such failures doesn’t keep you awake at night, you’re a lot more sanguine about your theories than I am about mine.Computational Theory is to neuroscience what String Theory is to theoretical physics — a compelling idea that has lost significant scientific credibility due to its failure, over time, to produce empirical results.
Jerry Fodor, The Mind Doesn't Work That Way: The Scope and Limits of Computational Psychology, 2001. pg. 38
