Story of Psychology - Morton Hunt [364]
—AI programs have no sense of self or of their place in the world around them. This severely limits their ability to do much real-world thinking.
—They are not conscious. Even though consciousness is still proving extremely difficult to define, we experience it and they do not. They cannot, therefore, examine their own thoughts and change their minds as a result. They make choices, but these are determined by their built-in data and their programming. Computers thus have nothing that resembles free will (or, if you prefer, free choice).
—They cannot—at least not yet—think creatively except within the purely abstract realm of chess. Some programs do generate new solutions to technical problems, but these are recombinations of existing data. Others have written poetry and music and created paintings, but their products have made little dent in artistic worlds; as in Doctor Johnson’s classic remark, they are “like a dog’s walking on his hinder legs. It is not done well; but you are surprised to find it done at all.”
—Finally, they have no emotions or bodily sensations, although in human beings these profoundly influence, guide, and not infrequently misguide, thinking and deciding.
Nonetheless, both the IP metaphor and the computer have been of immense value in the investigation of human reasoning. The IP model has spawned a profusion of experiments, discoveries, and insights about those cognitive processes which take place in serial fashion. And the computer, on which IP theories can be modeled and either validated or invalidated, has been an invaluable laboratory tool.
But the shortcomings of the IP model and the limitations of AI simulations led, by the 1980s, to a second stage of the cognitive revolution: the emergence of a radically revised IP paradigm. Its central concept is that while the serial model of information processing fits some aspects of cognition, most—especially the more complex mental processes—are the result of a very different model, parallel processing.
By astonishing coincidence—or perhaps through a cross-fertilization of ideas—this accorded with then-new findings of brain research showing that in mental activities, nerve impulses do not travel a single route from one neuron to another; they proceed by the simultaneous activation of multitudes of intercommunicating circuits. The brain is not a serial processor but a massively parallel processor.
Matching these developments, computer scientists got busy devising a new kind of computer architecture in which interlocking and intercommunicating processors work in parallel, affecting one another’s operations in immensely complex ways that are more nearly analogous to those of the brain and mind than are serial computers.102 The new computer architecture is not patterned on the neuron networks of the brain, most of which are still unmapped and too complex by an astronomical degree to be copied, but it does, in its own way, perform parallel processing.
The technical details of these three developments lie beyond the scope of this book. But their meaning and significance do not; let us see what we can make of them.
New Model
In 1908, Henri Poincaré, a French mathematician, labored for fifteen days to develop a theory of Fuchsian functions but without success. He then left to go on a geological expedition. Just as he boarded a bus, talking to a fellow traveler, the solution popped into his mind so clearly and unequivocally that he did not even interrupt his conversation to check it out. When he did so later, it proved correct.
The annals of creativity are full of such stories; they suggest that two (or possibly more) thoughts can be pursued simultaneously by the mind, one consciously, the other or others unconsciously. Anecdotes are not scientific evidence, but in the early years of the cognitive revolution several experiments on