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Geoff Hinton: On Radiology

Creative Destruction Lab · 45.5K views · 2016-11-24 · 1:25

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Overview

A one-minute clip from a 2016 Toronto conference in which Geoff Hinton comments on deep learning and radiology. He suggests radiologists should stop being trained because machines would soon read scans better.

On Hacker News

HN uses it as a famous example of an overconfident AI prediction that turned out wrong, since radiologists remain in demand.

Discussed on HN; no positive recommendation is recorded in this export · HN mentions 2017–2026

Topics

AI safety, AGI & impactMachine learning & deep learningMedicine & infectious disease
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geoffrey hintonradiologydeep learningautomationjobs

What people said

leoc · 2026-06 · Reference

He seems pretty unequivocal in the video: [VIDEO] . He even points out that it’s something which he’s claimed previously, ruling out the idea that it was some kind of spur-of-the-moment conclusion.

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chubot · 2025-09 · Criticism

I guess it's worth reminding people that in 2016, Geoff Hinton said some pretty arrogant things that turned out to be totally wrong: Let me start by saying a few things that seem obvious. I think if you work as a radiologist, you're like the coyote that’s already over the edge of the cliff but hasn’t yet looked down It’s just completely obvious that within five years deep learning is going to do better than radiologists.… It might be 10 years, but we’ve got plenty of radiologists already.” [VIDEO] This article has some good perspective: [LINK] His words were consequential. The late 2010s were filled with articles that professed the end of radiology; I know at least a few people who chose alternative careers because of these predictions. --- According to US News, radiology is the 7th best paying job in 2025, and the demand is rising: [LINK] [LINK] I asked AI about radiologists in 2025, and it came up with this article: [LINK] The Radiologist Shortage: Rising Demand, Limited Supply, Strategic Response (Ironically, this article feels spammy to me -- AI is probably being too credulous about what's written on the web!) --- I read Cade Metz's book about Hinton and the tech transfer from universities to big tech ... I can respect him for persisting in his line of research for 20-30 years, while others saying he was barking up the wrong tree But maybe this late life vindication led to a chip on his shoulder The way he phrased this is remarkably confident and arrogant, and not like th

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carbocation · 2025-01 · Criticism

I remember when Hinton said that that we should "stop training radiologists now" in 2016[1]. Meanwhile, radiologists are in high demand and are getting paid better than ever. I believe the same will be true for programmers in the future. Sure, some of the boilerplate will be handled for you, just like segmentation is for radiologists. That's great for everyone. 1 = [VIDEO]

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Sources

Video by Creative Destruction Lab, played through YouTube.

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