When mathematicians discover a new result, they automatically become experts during the process, and then go around giving talks to explain their results, methods, and intuitions to other mathematicians. Eventually, some of the mental frameworks percolate to other fields.
No one from OpenAI is willing to give a talk on any of their 300+ results.
There is a fixed landscape of logically provable mathematical statements. Normally, the process of exploring that landscape simultaneously improves human understanding. Now, formal proofs and actual knowledge have become decoupled.
There is also an issue of motivation and putting in 10,000 hours to become an expert (and remain an expert).
It's the same in the software engineering, there is a shift from software engineering to managing SWE agents, with the associated loss of expertise.
It's a hard challenge, but it is not unique or impossible to solve. Aviation industry faced it long time ago with autopilots. Autopilots took over nearly all aspects of routine flight and left pilots without time/ability to practice their skills. While these skills are needed in an emergency. Well, the industry solves it through certification, training and simulation.
No, the math community is shutting itself in from the rest of the world.
You can ignore the AI, but that doesn't mean the AI ignores you. Suddenly you become a little isolated society like the Amish and everyone else thinks you're kind of quaint and backwards.
The problem is that AI is just too smart to explain complicated topics to humans. It has an immense context window that humans simply don't match. AI labs should work on bridging that, but you cannot really put any blame on them currently.
AI Boosters: AIs are just getting better at everything and so their broad capacity can be defined as "intelligence".
Also AI Boosters: These entities are too intelligent to explain what they are doing to people...
I mean, Terry Tao actually used ChatGPT to explain one of the earlier OpenAI results. Humans working with AI can explain this stuff. If nothing else, OpenAI could be releasing things at the rate that it can get human mathematicians to explain the results. Which is to say, "yes, I can blame them", I don't expect them to behave differently but I can certainly blame them.
If humans with the background to understand the proof can get the AI to satisfactorily explain itself, then OpenAI doesn't need to publish explanations or release things at a rate that a human can explain. They have an interactive explainer that you can just ask!
It's still of course useful to have some of this distilled understanding be written down, just like I had it generate high level descriptions of our code at work so it doesn't have to rediscover everything every time, but that's more of a cache/optimization.
To Archetypal Aunt Tillie, perhaps programmers already looked like some sort of priest trying to rationalize and convey the ineffable decisions of the fickle computer spirit... but I really hope that the job doesn't start looking like that from the inside too.
It'd be some sort of... epistemic step backwards by civilization.
There has always been a smartest creature on the planet, whichever species was smartest has changed thousands of times and there is nothing special about humans that keeps them from being superseded.
You didn't understand me. What I'm saying is that current AI is not good at explaining things because their "brain" works differently. Imagine someone with a 10x larger working memory explaining something to you, even though they are equally intelligent. They would try to overflow your working memory where a better matched teacher would chop it up in human digestible pieces.
No one from OpenAI is willing to give a talk on any of their 300+ results.
There is a fixed landscape of logically provable mathematical statements. Normally, the process of exploring that landscape simultaneously improves human understanding. Now, formal proofs and actual knowledge have become decoupled.