【Economist】Artificial intelligence: Peering into t...

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There is an old joke among pilots that says the ideal flight crew is a computer, a pilot and a dog. The computer’s job is to fly the plane. The pilot is there to feed the dog. And the dog’s job is to bite the pilot if he tries to touch the computer.

Handing complicated tasks to computers is not new. But a recent spurt of progress in machine learning, a subfield of artificial intelligence (AI), has enabled computers to tackle many problems which were previously beyond them. The result has been an AI boom, with computers moving into everything from medical diagnosis and insurance to self-driving cars.

There is a snag, though. Machine learning works by giving computers the ability to train themselves, which adapts their programming to the task at hand. People struggle to understand exactly how those self-written programs do what they do . When algorithms are handling trivial tasks, such as playing chess or recommending a film to watch, this “black box” problem can be safely ignored. When they are deciding who gets a loan, whether to grant parole or how to steer a car through a crowded city, it is potentially harmful. And when things go wrong—as, even with the best system, they inevitably will—then customers, regulators and the courts will want to know why.

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