Intelligent machinery
Jack G. Copeland · Oxford University Press eBooks · 2017
This chapter explains why Turing is regarded as founding father of the field of artificial intelligence (AI), and analyses his famous method for testing whether a computer is capable of thought. In the weeks before his 1948 move from the National Physical Laboratory to Manchester, Turing wrote what was, with hindsight, the first manifesto of artificial intelligence (AI). His provocative title was simply Intelligent Machinery. While the rest of the world was just beginning to wake up to the idea that computers were the new way to do high-speed arithmetic, Turing was talking very seriously about ‘programming a computer to behave like a brain’. Among other shatteringly original proposals, Intelligent Machinery contained a short outline of what we now refer to as ‘genetic’ algorithms—algorithms based on the survival-of-the-fittest principle of Darwinian evolution—as well as describing the striking idea of building a computer out of artificial human nerve cells, an approach now called ‘connectionism’. Turing’s early connectionist architecture is outlined in Chapter 29. Strangely enough, Turing’s 1940 anti-Enigma bombe was the first step on the road to modern AI. As Chapter 12 explains, the bombe worked by searching at high speed for the correct settings of the Enigma machine—and once it had found the right settings, the random-looking letters of the encrypted message turned into plain German. The bombe was a spectacularly successful example of the mechanization of thought processes: Turing’s extraordinary machine performed a job, codebreaking, that requires intelligence when human beings do it. The fundamental idea behind the bombe, and one of Turing’s key discoveries at Bletchley Park, was what modern AI researchers call ‘heuristic search’. The use of heuristics—shortcuts or rules of thumb that cut down the amount of searching required to find the answer—is still a fundamental technique in AI today. The difficulty Turing confronted in designing the bombe was that the Enigma machine had far too many possible settings for the bombe just to search blindly through them until it happened to stumble on the right answer—the war might have been over before it produced a result. Turing’s brilliant idea was to use heuristics to narrow, and so to speed up, the search. Turing’s idea of using crib-loops to narrow the search was the principal heuristic employed in the bombe (as Chapter 12 explains).