That's a good point about motivated reasoning. I should distinguish arguments that the lazy approach is better for people and arguments that it's better for me. Whether it's better for people more generally depends on the reference class we're talking about. I will assume people who are interested in the foundations of mathematics as a hobby outside of AI safety should take my advise less seriously.

However, I still think that it's not exactly clear that going the foundational route is actually that useful on a per-unit time basis. The model I proposed wasn't as simple as "learn the formal math" versus "think more intuitively." It was specifically a question of whether we should learn the math on an as-needed basis. For that reason, I'm still skeptical that going out and reading textbooks on subjects that are only vaguely related to current machine learning work is valuable for the vast majority of people who want to go into AI safety as quickly as possible.

Sidenote: I think there's a failure mode of not adequately optimizing time, or being insensitive to time constraints. Learning an entire field of math from scratch takes a lot of time, even for the brightest people alive. I'm worried that, "Well, you never know if subject X might be useful" is sometimes used as a fully general counterargument. The question is not, "Might this be useful?" The question is, "Is this the most useful thing I could learn in the next time interval?"