Making a Mind vs. Modeling the Brain: AI Back at a Branchpoint

In the early 1950s, as calculating machines were coming into their own, a few pioneer thinkers began to realize that digital computers could be more than number crunchers. At that point two opposed visions of what computers could be, each with its correlated research program, emerged and struggled for recognition. One faction saw computers as a system for manipulating mental symbols; the other, as a medium for modeling the brain. One sought to use computers to instantiate a formal representation of the world; the other, to simulate the interactions of neurons. One took problem solving as its paradigm of intelligence; the other, learning. One utilized logic, the other statistics. One school was the heir to the rationalist, reductionist tradition in philosophy; the other viewed itself as idealized, holistic neuro-science. The rallying cry of the first group was that both minds and digital computers were physical symbol systems. By 1955 Allen Newell and Herbert Simon, working at the RAND Corporation, had concluded that strings of bits manipulated by a digital computer could stand for anything -numbers, of course, but also features of the real world. Moreover, programs could be used as rules to represent relations between these symbols, so that the system could infer further facts about the represented objects and their relations. As Newell put it recently in his account of the history of issues in AI: