A BRIEF HISTORY OF ARTIFICIAL INTELLIGENCE <\/p>\n<\/p>\n
Stephanie Haack is director of communications for the Computer Museum in Boston. <\/p>\n
The quest for artificial intelligence is as modern as the frontiers of computer science and as old as Antiquity. The concept of a \"thinking machine\" began as early as 2500 B.C., when the Egyptians looked to talking statues for mystical advice. Sitting in the Cairo Museum is a bust of one of these gods, Re-Harmakis, whose neck reveals the secret of his genius: an opening at the nape just big enough to hold a priest. Even Socrates sought the impartial arbitration of a \"thinking machine.\" In 450 B.C. he told Euthypro, who in the name of piety was about to turn his father in for murder, \"I want to know what is characteristic of piety ... that I may have it to turn to, and to use as a standard whereby to judge your actions and those of other men.\" Automata, the predecessors of today's robots, date back to ancient Egyptian figurines with movable limbs like those found in Tutankhamen's tomb. Much later, in the fifteenth century A.D., drumming bears and dancing figures on clocks were the favorite automata, and game players such as Wolfgang von Kempelen's Maezel Chess Automaton reigned in the eighteenth century. (Kempelen's automaton proved to be a fake; a legless master chess player was hidden inside.) It took the invention of the Analytical Engine by Charles Babbage in 1833 to make artificial intelligence a real possibility. Babbage's associate, Lady Lovelace, realized the profound potential of this analyzing machine and reassured the public that it could do nothing it was not programmed to do. Artificial intelligence (AI) as both a term and a science was coined 120 years later, after the operational digital computer had made its debut. In 1956 Allen Newell, J. C. Shaw and Herbert Simon introduced the first AI program, the Logic Theorist, to find the basic equations of logic as defined in Principia Mathematica by Bertrand Russell and Alfred North Whitehead. For one of the equations, Theorem 2.85, the Logic Theorist surpassed its inventors' expectations by finding a new and better proof. Suddenly we had a true \"thinking machine\"-one that knew more than its programmers. <\/p>\n<\/p>\n
The Dartmouth Conference An eclectic array of academic and corporate scientists viewed the demonstration of the Logic Theorist at what became the Dartmouth Summer Research Project on Artificial Intelligence. The attendance list read like a present-day Who's Who in the field: John McCarthy, creator of the popular AI programming language LISP and director of Stanford University's Artificial Intelligence Laboratory; Marvin Minsky, leading AI researcher and Donner Professor of Science at M.I.T.; Claude Shannon, Nobel Prize-winning pioneer of information and AI theory, who was with Bell Laboratories. By the end of the two-month conference, artificial intelligence had found its niche. Thinking machines and automata were looked upon as antiquated technologies. Researchers' expectations were grandiose, their predictions fantastic. \"Within ten years a digital computer will be the world's chess champion,\" Allen Newell said in 1957, \"unless the rules bar it from competition.\" Isaac Asimov, writer, scholar and author of the Laws of Robotics, was among the wishful thinkers. Predicting that AI (for which he still used the term \"cybernetics\") would spark an intellectual revolution, in his foreword to Thinking by Machine by Pierre de Latil he wrote: <\/p>\n
Cybernetics is not merely another branch of science. It is an intellectual revolution that rivals in importance the earlier Industrial Revolution. Is it possible that just as a machine can take over the routine functions of human muscle, another can take over the routine uses of human mind? Cybernetics answers, yes.<\/p>\n<\/p>\n
Getting Smarter Artificial intelligence research has progressed considerably since the Dartmouth conference, but the ultimate AI system has yet to be invented. The ideal AI computer would be able to simulate every aspect of learning so that its responses would be indistinguishable from those of humans. Alan M. Turing, who as early as 1934 had theorized that machines could imitate thought, proposed a test for AI machines in his 1950 essay \"Computing Machinery and Intelligence.\" The Turing Test calls for a panel of judges to review typed answers to any question that has been addressed to both a computer and a human. If the judges can make no distinctions between the two answers, the machine may be considered intelligent. It is 1984 as this is being written. A computer has yet to pass the Turing Test, and only a few of the grandiose predictions for artificial intelligence have been realized. Did Turing and other futurists expect too much of computers? Or do AI researchers just need more time to develop their sophisticated systems? John McCarthy and Marvin Minsky remain confident that it is just a matter of time before a solution evolves, although they disagree on what that solution might be. Even the most sophisticated programs still lack common sense. McCarthy, Minsky and other Al researchers are studying how to program in that elusive quality-common sense. McCarthy, who first suggested the term \"artificial intelligence,\" says that after thirty years of research AI scholars still don't have a full picture of what knowledge and reasoning ability are involved in common sense. But according to McCarthy we don't have to know exactly how people reason in order to get machines to reason. McCarthy believes that a sophisticated programmed language of mathematical logic will eventually be capable of common-sense reasoning, whether or not it is exactly how people reason. Minsky argues that computers can't imitate the workings of the human mind through mathematical logic. He has developed the alternative approach of frame systems, in which one would record much more information than needed to solve a particular problem and then define which details are optional for each particular situation. For example, a frame for a bird could include feathers, wings, egg laying, flying and singing. In a biological context, flying and singing would be optional; feathers, wings and egg laying would not. The common-sense question remains academic. No current program based on mathematics or frame systems has common sense. What do machines think? To date, they think mostly what we ask them to. <\/p>\n
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