EDGE: NATURAL BORN CYBORGS? - Page 3

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In fact, the true power and beauty of the brain's role is that it acts as a mediating factor in a variety of complex and iterated processes which continually loop between brain, body and technological environment. And it is this larger system which solves the problem. We thus confront the cognitive equivalent of Dawkins' vision of the extended phenotype. The intelligent process just is the spatially and temporally extended one which zigzags between brain, body and world.

One useful way to understand the cognitive role of many of our self-created cognitive technologies is as affording complementary operations to those that come most naturally to biological brains. Thus consider the connectionist image of biological brains as pattern-completing engines. Such devices are adept at linking patterns of current sensory input with associated information: you hear the first bars of the song and recall the rest, you see the rat's tail and conjure the image of the rat.

Computational engines of that broad class prove extremely good at tasks such as sensorimotor coordination, face recognition, voice recognition, etc. But they are not well-suited to deductive logic, planning, and the typical tasks of sequential reason. They are, roughly speaking, "Good at Frisbee, Bad at Logic:" a cognitive profile that is at once familiar and alien. Familiar, because human intelligence clearly has something of that flavor. Yet alien, because we repeatedly transcend these limits, planning family vacations, running economies, solving complex sequential problems, etc., etc.

A powerful hypothesis, which I first encountered in work by David Rumelhart, Paul Smolensky, John McClelland and Geoffrey Hinton, is that we transcend these limits, in large part, by combining the internal operation of a connectionist, pattern-completing device with a variety of external operations and tools which serve to reduce various complex, sequential problems to an ordered set of simpler pattern-completing operations of the kind our brains are most comfortable with.

Thus, to borrow their illustration, we may tackle the problem of long multiplication — e.g. 667X999— by using pen, paper and numerical symbols. We then engage in a process of external symbol manipulations and storage so as to reduce the complex problem to a sequence of simple pattern-completing steps that we already command, first multiplying 9 by 7 and storing the result on paper, then 9 by 6, and so on.


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