| ▲ | chubot 2 days ago | ||||||||||||||||
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.” https://www.youtube.com/watch?v=2HMPRXstSvQ This article has some good perspective: https://newrepublic.com/article/187203/ai-radiology-geoffrey... 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: https://money.usnews.com/careers/best-jobs/rankings/best-pay... https://radiologybusiness.com/topics/healthcare-management/h... I asked AI about radiologists in 2025, and it came up with this article: https://medicushcs.com/resources/the-radiologist-shortage-ad... 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 the behavior of respected scientist (now with a Nobel Prize) ... It's almost like Twitter-speak that made its way into real life, and he's obviously not from the generation that grew up with Twitter | |||||||||||||||||
| ▲ | gobdovan 2 days ago | parent | next [-] | ||||||||||||||||
Yeah, even forgot about that... I suppose that the same kind of confidence made him stick with neural nets for so long too, despite mainstream AI thinking it's a dead end. But that's the thing in academia, bold claims get encouraged, as ideas still get you the credit, even if they prove useful decades later and not in the way you imagined. | |||||||||||||||||
| ▲ | giardini 2 days ago | parent | prev | next [-] | ||||||||||||||||
I wouldn't be too hard on Hinton. Researchers in image processing, geophysics and medicine have been saying the same thing since at least the early 1980's. There was always something coming that was just over the next hill that would take the human out of the loop. That special something always evaporated with time. I suppose it did keep funding coming in. | |||||||||||||||||
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| ▲ | dinfinity 2 days ago | parent | prev | next [-] | ||||||||||||||||
I think the key insight is that AI is (undoubtedly going to be) better at analysis and diagnosis than radiologists, but isn't yet widely deployed because: 1. The medical world doesn't accept new technologies easily. Humans get a much higher pass on bad performance than technology and especially than new technology. Things need to be extensively tested and certified, so adoption is slow. 2. AI is legally very different than a radiologist. The liability structure is completely different, which matters a lot in an environment that deals with life or death decisions. 3. Image analysis is not language analysis and generation. This specific machine learning part is not the bit of machine learning that has advanced enormously in the past two years. General knowledge of the world doesn't help that much when the task is to look at pixels and determine whether it's cancer or not. Now this can be improved by integrating the image analysis with all the other possibly relevant information (case history etc.) and diagnosing the case via that route. | |||||||||||||||||
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| ▲ | meowface 2 days ago | parent | prev | next [-] | ||||||||||||||||
To be fair we haven't hit 2026 yet so his prediction might still turn out to be somewhat accurate. But yeah, probably not. | |||||||||||||||||
| ▲ | ionwake 2 days ago | parent | prev [-] | ||||||||||||||||
the guy invented AI who cares if he is a couple years wrong with a prediction that will come to fruition, jeez. I would call the geezer confident not arrogant. Who is this? Some burned post doc? No offence but you are randomly laying into the guy as if this is Oprah | |||||||||||||||||