"AI isn't replacing radiologists" good article Expectation: rapid progress in image recognition AI will delete radiology jobs (e.g. as famously predicted by Geoff Hinton now almost a decade ago). Reality: radiology is doing great and is growing. There are a lot of imo naive predictions out there on the imminent impact of AI on the job market. E.g. a ~year ago, I was asked by someone who should know better if I think there will be any software engineers still today. (Spoiler: I think we're going to make it). This is happening too broadly. The post goes into detail on why it's not that simple, using the example of radiology: - the benchmarks are nowhere near broad enough to reflect actual, real scenarios. - the job is a lot more multifaceted than just image recognition. - deployment realities: regulatory, insurance and liability, diffusion and institutional inertia. - Jevons paradox: if radiologists are sped up via AI as a tool, a lot more demand shows up. I will say that radiology was imo not among the best examples to pick on in 2016 - it's too multi-faceted, too high risk, too regulated. When looking for jobs that will change a lot due to AI on shorter time scales, I'd look in other places - jobs that look like repetition of one rote task, each task being relatively independent, closed (not requiring too much context), short (in time), forgiving (the cost of mistake is low), and of course automatable giving current (and digital) capability. Even then, I'd expect to see AI adopted as a tool at first, where jobs change and refactor (e.g. more monitoring or supervising than manual doing, etc). Maybe coming up, we'll find better and broader set of examples of how this is all playing out across the industry. About 6 months ago, I was also asked to vote if we will have less or more software engineers in 5 years. Exercise left for the reader. Full post (the whole The Works in Progress Newsletter is quite good): worksinprogress.news/p/why-a…