this post was submitted on 21 Aug 2026
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GenZedong
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I was always under the impression that the cognitive outsourcing is worse the earlier it starts. I am in academia, and a lot of really bright researchers, professors etc are using generative AI tools, but they have spent a good 20-30 years already reading, researching and producing high-quality output already, they are not using it to get away from thinking about hard problems, simply to speed up the process of tackling them.
It is way worse for students. I can only speak for mathematics, but the field is trying to come to gripes with what this whole ordeal will mean, and even then we are at least quite shielded from some of the problems with education (quite easy to expand and assess in-person exams, for instance).
You generally NEED a minimum of 10-20k hours working and thinking about this stuff to understand it at a high level, there are no shortcuts. Now the barrier to be able to put some slop together and pretend you've come up with a result is a lot lower, which is the shortcut many students are going for sadly.
If anyone is interested in the discussion I'll just put some good starters:
https://nitter.net/aaswaminathan01/status/2025418710198960388
https://davidbessis.substack.com/p/the-fall-of-the-theorem-economy
I hold the belief that LLMs are the final nail in the coffin of an results-oriented education model that has become outmoded. I have personally experienced cognitive dissonance between my idealised notion of education and knowledge acquisition on one hand, and on the other the reality of stress, lack of reward for going beyond "good enough" and fear of my perfectionism yet slowness making me unable to catch up.
One way I keep myself from collapsing from all the things to worry about is that I try to focus on a few things I feel passionate about: the future of education is one of them.