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Geoffrey Hinton said machine learning would outperform radiologists by now

Nobel Prize winner Geoffrey Hinton said that machine learning would outperform radiologists within five years. That was eight years ago. Now, thanks in part to doomers, we’re facing a historic labor shortage.

Hinton’s seminal contributions to neural networks are credited with ushering in the explosion in artificial intelligence today, but lately he has gained a reputation as an alarmist: After more than a decade at Google, he quit last year to focus instead on warning the public about the risks posed to humanity by AI. Medical students rotating through the reading room ask whether we residents see ourselves having a job in 10 years; engineering types praise the objectivity of computer reasoning, while senior radiologists rue the lost art, the human gestalt, in medicine. There are others who subscribe to Hinton’s view that radiologists are like “the coyote that’s already over the edge of the cliff but hasn’t yet looked down”—and who thus plan to take the highest paying job available, diligently working and saving for when the floor finally falls out.

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