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Cognitive scientists often say that the mind is the software of the brain. This chapter is about what this claim means. The last part of the section will discuss the relation between the mental and the biological.
This approach has been popular among thinkers who fear that acknowledging mental states that do not reduce to behavior would make psychology unscientific, because unreduced mental states are not intersubjectively accessible in the manner of the entities of the hard sciences.
Behaviorists don't define the mental in terms of just plain behavior, since after all something can be intelligent even if it has never had the chance to exhibit its intelligence. Behaviorists define the mental not in terms of behavior, but rather behavioral dispositions, the tendency to emit certain behaviors given certain stimuli.
It is important that the stimuli and the behavior be specified non-mentalistically.
Thus, intelligence could not be defined in terms of the disposition to give sensible responses to questions, since that would be to define a mental notion in terms of another mental notion indeed, a closely related one.
To see the difficulty of behavioristic analyses, one has to appreciate how mentalistic our ordinary behavioral descriptions are.
Consider, for example, throwing. A series of motions that constitute throwing if produced by one mental cause might be a dance to get the ants off if produced by another. An especially influential behaviorist definition of intelligence was put forward by A. Turing, one of the mathematicians who cracked the German code during World War II, formulated the idea of the universal Turing machine, which contains, in mathematical form, the essence of the programmable digital computer.
Turing wanted to define intelligence in a way that applied to both men and machines, and indeed, to anything that is intelligent.
His version of behaviorism formulates the issue of whether machines could think or be intelligent in terms of whether they could pass the following test: Let's say an hour. The computer is intelligent if and only if the judge cannot tell the difference between the computer and the person.
Turing's definition finessed the difficult problem of specifying non-mentalistically the behavioral dispositions that are characteristic of intelligence by bringing in the discrimination behavior of a human judge.
And the definition generalizes. Anything is intelligent just in case it can pass the Turing test. Turing suggested that we replace the concept of intelligence with the concept of passing the Turing test.
But what is the replacement for? If the purpose of the replacement is practical, the Turing test is not enormously useful. If one wants to know if a machine does well at playing chess or diagnosing pneumonia or planning football strategy, it is better to see how the machine performs in action than to make it take a Turing test.
For one thing, what we care about is that it do well at detecting pneumonia, not that it do it in a way indistinguishable from the way a person would do it. So if it does the job, who cares if it doesn't pass the Turing test? A second purpose might be utility for theoretical purposes.
But machines that can pass the Turing test such as Weizenbaum's ELIZA see below have been dead ends in artificial intelligence research, not exciting beginnings.
See "Mimicry versus Exploration" in Marrand Shieber, A third purpose, the one that comes closest to Turing's intentions, is the purpose of conceptual clarification. Turing was famous for having formulated a precise mathematical concept that he offered as a replacement for the vague idea of mechanical computability.
The precise concept computability by a Turing machine did everything one would want a precise concept of mechanical computability to do. No doubt, Turing hoped that the Turing test conception of intelligence would yield everything one would want from a definition of intelligence without the vagueness of the ordinary concept.
Construed as a proposal about how to make the concept of intelligence precise, there is a gap in Turing's proposal: A judge who was a leading authority on genuinely intelligent machines might know how to tell them apart from people.
For example, the expert may know that current intelligent machines get certain problems right that people get wrong.BBB's Business Profile For Paper Source Cambridge that includes background information, consumer experience, BBB Accreditation status, BBB Rating, customer reviews, complaints, business photos Location: Massachusetts Ave, Cambridge, MA IBM Research is the innovation engine of the IBM corporation.
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