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In the 1630s Rene Descartes stated that humans would never be able to create a mind modeled on their own. While trying to map mind to brain for the first time, Freud (1895, p. 297) said that “we cannot offhand imagine an apparatus capable of such complicated functioning.” He finally shelved his project, which was published only posthumously. In the 1950s, Alan Turing, a British mathematician and computer expert, stated that it was possible to build a machine that would perform all the functions of the human mind. Such a machine would pass the test of answering questions from a person in a fashion undistinguishable from answers from another person. These changing scientific opinions reflect cultural change as much as they do scientific advancement: they portray shifts from analytic (linear) to dialectic (systemic) and finally to postmodern (chaotic) thinking. Today a psychoanalyst may ask: Could Turing's thinking computer have bad faith? Could it be biased or lie? Could it distort or give unconscious messages? Could it deal with ambiguity? Finally, could it be creative? The answer may be yes, and although segments of such a machine already exist even in simple computer programs, the holistic model is yet to be assembled.
During recent years advances in artificial intelligence (Al), and particularly in the connectionist models that will concern us here, are being used by psychiatrists in an attempt to explain brain function. This new paradigm seems to promise a revolution—some believe—in that it will allow us to further uncover the secrets of the brain. It also gives practitioners some hope that the further understanding of mental illness could be greatly enhanced by the new prototypes. In this paper we propose to explore the possibility that in these models, used already by biological psychiatry, there is an additional place for psychoanalysis and, even more importantly, for bridging the latter with behaviorism, cognitivism, and with the rest of the neurosciences. Gap