Artificial stupidity

Creating machines that think like people is a great challenge, but a bad idea. In 1950 Alan Turing, a British mathematician of genius, challenged scientists to create a machine that could trick people into thinking it was one of them. By 2000, Turing predicted, computers would be able to trick most of the people most of the time - at least in conversations where neither party could see or hear the other, but instead "talk" by typing at computer terminals. Thanks to 40 years of research into artificial intelligence - a field which has adopted Turing's test as its semi-official goal - Turing's prediction may well come true. But it will be a dreadful anticlimax.

The most obvious problem with Turing's challenge is that there is no practical reason to create machine intelligences indistinguishable from human ones. People are in plentiful supply. Should a shortage arise, there are proven and popular methods for making more of them; these require no public subsidy and little or no technology. The point of using machines ought to be that they perform differently from people, and preferably better. If that potential is to be exploited, machines will need to be given new forms of intelligence all their own.

Gradually, this is happening. Many human capabilities remain well beyond the reach of machines. No computer can understand a fairy tale, recognise faces or navigate across a crowded room. But machines have learnt a lot. Computer chess-players can beat all but the very best humans. Machines can solve logical puzzles, apply bureaucratic rules and perform passable translations from one language to another. Computers' new skills are winning them jobs alongside decision-makers in a variety of companies, complementing human weaknesses with computer strengths.