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this post was submitted on 15 Jul 2026
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It's doing some pretty awesome things in the medical field as well, where experts can review it's output and make decisions based on everything else they know and are experts in
It's weird, like if experts feed AI things they know to be true, correct it when it gets it wrong, rinse and repeat. Then only use that AI for the things they trained it on, it seems to be pretty good. Whereas AI fed the entirety of human shit and corrected by middle managers, who are only experts in inflating their own ego, tends to output a lot of self-inflating bullshit.
i think a yet unanswered question in this example is, how will the next generation of experts (doctors) be able to validate the outputs of AI when every new trainee doctor has come to rely on the AI tools so much that they no longer need to put in the work to develop the very skills necessary to validate AI output?
so far in human history, most experts in their fields have arrived there through a challenging process of many hours of effort and many repetitions. medicine is a "practice" that you should theoretically get better at over time. same as carpentry or sculpting or playing violin.
you can't become an expert carpenter by watching videos of houses getting built. you have to actually do the work of building houses. over and over again. until you know what a well made house looks like, inside and out. experience and intuition play key roles in this process.
similarly, you can't become a master sculptor by 3D printing a million different objects. or a talented pianist by clicking on a soundboard. people may appreciate and enjoy all the stuff you are producing, but is that the same as being a trusted "expert"?
a tool speeds things up and removes barriers to entry for non experts. very cool, the world needs fewer gatekeepers for sure. but the tool doesn't necessarily teach you the specialized knowledge intrinsic to being an expert. but AI is very different from most other tools because it doesn't help you like a hammer helps a carpenter or how a metronome helps a pianist. AI mostly just gives you a result. it bypasses the entire process. sure, arriving quickly at a result is wonderful if you only care about the product, but if the people entrusted to ensure the quality and validity of the results have only ever seen it done 'the easy way' I'm not sure if something important is being lost or diminished.
not trying to be clever or circular, just genuinely concerned that de-skilling is a likely consequence of long term (multi generational) AI usage. and the generation of experts (whose expertise actual trained the tools) will be retired or dead so we can't ask them anymore.
I feel like the correct use case here is in parallel, not primary or backup.