Creative Destruction Lab
7 HN mentions · mentioned in 6 months, 2017–2026
1:25 · 45K views · Nov 24, 2016
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.
HN uses it as a famous example of an overconfident AI prediction that turned out wrong, since radiologists remain in demand.
7 comments from Hacker News
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.” this 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
"It’s also important to be patient. College is an investment that pays dividends over your entire working life. If you’re a new graduate, you’ve just incurred the upfront costs of this investment in your human capital, but you have many decades to go to reap the economic benefits of your college degree. " I must admit, that triggered me. I say that is by far a too comfortable assertion. > It definitely seems that there's too much focus paid to the automation of transportation and the like, and even though those are going away, it's obvious a lot of white collar/office jobs are easier to automate away Curiously under examined while the cries for basic income go on, often projected as help for the working/welfare classes. Where do these cries come from? The beleaguered middle classes. Maybe we should read between the lines. I strongly suspect a lot of middle income people don't have a Plan B more sophisticated than the truck driver (fleeing into the universities is a brainless move in most scenarios) and their incomes have been stagnant for a long time, so they're afraid of falling through the cracks. A just concern in my view. People who deal with a body of information can be just as entrenched in their habits as anybody else. Some blue collar will be automated of course, but the salient point is that nearly all blue collar labour was already automated in the Industrial Revolution . That which remains will be harder to automate. The most humble of jobs are incredibly frustrati
> I can appreciate that. I haven't been listening to him for that long; having no idea what situation you're discussing, I'll take it at face value. this video We are currently facing the biggest radiologist shortage in the last 30 years. > It’s the unknowns which are dangerous. Electricity, the Industrial Revolution, the internet, gene editing/bionengineering also came with unknown existential risks. > We’re inventing something new in almost every way imaginable. > I think people assume advancements will accelerate, actually. This is highly debatable. > we're talking about the potential to build a new life form with godlike abilities. Evidence? This has been stated in sci-fi books from before I was born and I don’t see any proof that we’re building something remotely close to this.
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 = this video
> the current trajectory is clear and verifiable. 2016, Geoffrey Hinton, "People should stop training radiologists now. It’s just completely obvious that within five years deep learning is going to do better than radiologists." this video