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.

▲

chubot 2 days ago | parent [-]

Well maybe, but none of that implies that there will be fewer radiologists will be employed, or that people studying radiology now are fools.

The overwhelming likely thing is that radiologist jobs will change, just like programming jobs will change.

e.g. see my comment on: Did Google and Stack Overflow "replace" programmers?

https://news.ycombinator.com/item?id=43013363

That is, I do not think programmers will be "replaced". The job will just be different; people will come to rely on LLMs for their jobs, like they rely on search engines.

Likewise, you can probably hire fewer doctors now because Google appeared in ~2000, but nobody talked about them being "replaced". There is NOT less demand for doctors.

---

It also reminds me of the prediction around self-driving cars, which is 13+ years ago at this point:

https://news.ycombinator.com/item?id=45149270

I believe Hacker News mostly fell for the hype in ~2012-2016. And even though the predictions turned out to be comically wrong, many people are still attached to them

https://en.wikipedia.org/wiki/List_of_predictions_for_autono...

i.e. I don't think Hinton will be proven "right" with ANY amount of time. The whole framing is just off.

It's not humans xor AI, it's humans + AI. And the world is not static

	▲	dinfinity 20 hours ago \| parent [-]
		The world is indeed not static. That it hasn't happened yet doesn't mean it won't. Predictions about self driving were off, but far from "comically wrong". Waymo's operations are proof of that. And to conclude things based on the state of the replacement of programmers after only 2-3 years of ChatGPT being a thing is folly. The reality is that AI has far fewer limitations and legacy cruft than humans to deal with. Don't get me wrong, I like humans, but our performance is very close to the peak of what it could ever be. That of AI not so much. Remember that AI has been evolving for less than 100 years and it is already where it is today. That took us/biology orders of magnitude more time. The only real question is how fast it will replace (which) human labor.