AI has a long way to go before doctors can trust it with your life

Geoffrey Hinton is a legendary computer scientist. When Hinton, Yann LeCun, and Yoshua Bengio were given the 2018 Turing Award, considered the Nobel prize of computing, they were described as the “Godfathers of artificial intelligence” and the “Godfathers of Deep Learning.” Naturally, people paid attention when Hinton declared in 2016, “We should stop training radiologists now, it’s just completely obvious within five years deep learning is going to do better than radiologists.” The US Food and Drug Administration (FDA) approved the first AI algorithm for medical imaging that year and there are now more than 80 approved algorithms in the US and a similar number in Europe.

Yet, the number of radiologists working in the US has gone up, not down, increasing by about 7% between 2015 and 2019. Indeed, there is now a shortage of radiologists that is predicted to increase over the next decade.

What happened? The inert AI revolution in radiology is yet another example of how AI has overpromised and under delivered. In books, television shows, and movies, computers are like humans, but much smarter and less emotional. The less emotional part is right. Despite our inclination to anthropomorphize computers (who can forget R2-D2 and C-3PO?), computer algorithms do not have sentiment, feelings, or passions. They also do not have wisdom, common sense, or critical thinking skills. They are extraordinarily good at mathematical calculations, but they are not intelligent in any meaningful sense of the word.

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