cesses of people doing arithmetic (Crawford, 1994). On the other hand, AI programs that simulate human vision are theoretical attempts to understand the actual processes of human beings and how they view and interpret the outside world. A great deal of the debate about artificial intelligence confuses the two views, so that sometimes success in artificial intelligence's practical application is supposed to provide structured or theoretical understanding in this branch of science known as cognitive science. Chess-playing programs are a good example. Early chess-playing programs tried to mimic the thought processes of actual chess players, but they were not successful. Ignoring the thoughts of chess masters and just using the much greater computing powers of modern hard wares have achieved more recent successes. This approach, called brute force, comes from the fact that specially designed computers can calculate hundreds of thousands or even millions of moves, which is something no human chess player can do (Matthys, 1995). The best current programs can beat all but the very best chess players, but it would be a mistake to think of them as substantial information to artificial intelligence's cognitive science field (Ptacek, 1994). They tell us almost nothing about human cognitions or thought processes, except that an electrical machine working on different principles can outdo human beings in playing chess, as it can defeat human beings in doing arithmetic.Assuming that artificial intelligence's practical applications, or AIPA, is completely successful and that society will soon have programs whose performance can equal or beat that of any human in any comprehension task at all. Assume machines existed that could not only play better chess but had equal or better comprehension of natural languages, write equal or better novels and poems, and prove equal or better math and science equations and solutions. What should society ma...
