What I predicted 9 months ago came to pass:

> "a scenario in which a large automated proof is achieved but there would be no practical means of getting any understanding of what it means"

https://news.ycombinator.com/item?id=46284897#46286785

That is precisely the concern of mathematicians (getting proof without getting the knowledge to humanity):

> But solving problems is only a tool and proxy for achieving the primary goal of conceptual understanding and insight. Forgetting this in the world of AI may turn the tool against the primary goal. Indeed, the mass production at faster and faster pace of "true/false" statements could destroy fertile ground instead of breathing life into new ideas.

I predict it's only going to get worse. So far, in software, all AI companies push for results that you don't necessarily need to understand (don't look at the code). I don't see any reason why they would change that posture for math.

"Your advice for making AI-obtained proof are sensible, but AI has progressed too much and I'm afraid you're obsolete and all math is now a compiler target and not an actual craft", is what I predict based on the exact same thing happening to software recently.