In parallel with computing power having grown exponentially and become vastly cheaper, humans have also got better at programming. A high-profile piece of evidence to that effect came in 2011, with the public victory of a project called Watson, run by IBM.

The idea behind Watson was to build a computer that could understand ordinary language well enough to win a popular TV quiz show called Jeopardy!, playing against not just ordinary contestants, but record-holding champions.?1 This would be, as Brynjolfsson and McAfee say, ?a stern test of a computer?s pattern matching and complex communication abilities?, much more demanding than another IBM project, the chess computer Deep Blue, which won a match against the world champion Gary Kasparov in 1997.

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Chess is vulnerable to brute computational force; I have a program on my smartphone which can easily beat the best chess player in the world. General knowledge-based quizzes, particularly ones like Jeopardy! with a colloquial and allusive component, are much less easily solved by sheer computing power.

The outcome is already a locus classicus in the study of computing, robotics and futurism, and is discussed at length in both John Kelly and Steve Hamm?s Smart Machines and Tyler Cowen?s Average Is Over.?2 Watson won, easily.

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Its performance wasn?t perfect: it thought Toronto was in the US, and when asked about a word with the double meaning ?stylish elegance, or students who all graduated in the same year?, it answered ?chic?, not ?class?. Still, its cash score at the end of the two-day contest was more than three times higher than that of the best of its human opponents. ?Quiz-show contestant may be the first job made redundant by Watson,? one of the vanquished men said, ?but I?m sure it won?t be the last.?


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