Why were we doing math in the first place? We should be happy that math problems were being solved, since presumably they were blockers for other problems in science and the like. But it feels like math was really more about seeking enlightenment, like a form of mental yoga or something. If so, we can just ignore AI proofs and continue on maybe?

There’s a somewhat famous lecture [0] by Wigner (one of the greats of 20th century physics if you’re not familiar) on exactly this topic. One of his points is that new tools and ways of thinking developed on the way to solving mathematical problems with no apparent application often find downstream applications in science and engineering. If we’re skipping the part where we identify and understand the new math, will we still reap the unreasonable effectiveness? Tao’s position in this post suggests that the current wave of LLM successes is not conducive to this dynamic

0: https://en.wikipedia.org/wiki/The_Unreasonable_Effectiveness...

I'm a retired AI researcher and I still enjoy programming. However, I don't use any however assistance as I still want the thrill of learning new things. Unfortunately, it appears that the only way for most developers to enjoy similar activities is to be retired with enough money

You could replace "math" with "programming" in your comment for a different perspective.

If you're considering an individual, maybe this makes sense.

But if you're consdiering a community, this falls apart. The maths community has universities, has professors who are paid, has students which are getting their degrees for varying reasons, it has conferences, has publications, papers, projects etc etc, all of which will get some negative impact some AI.

You know that line "when a measurement becomes a target it ceases to be a useful measurement". This line holds up to different degrees for various measurements and targets. For maths it holds up very well. The goal is "contribute to make the world better by increasing humanity's understanding of maths" and the measurement, which by evaluating an individual on it we're turning into a target, is "how much does the individual publish new findings". Measurement turned target holds up great. It's almost impossible to publish new findings and not contribute to humanity's understanding of maths. But with AI these two are being decoupled. You can produce lots of new findings, but the community is saturated and they don't get assimilated into humanity's understanding. Why do individuals use AI then? Because you've made the target "how much does the individual publish new findings" and they have to compete or lose.

To many professional mathematicians it's a form of art. But at the end of the day, it's a profession done for money, and even if they like doing it as a day to day job, they'd probably be doing something else if they had absolute freedom over their time. This is how I personally classify things as art or chore. If people continue doing something the same way when there is no financial motive, it's art in its pure form.

If we're going to be frank about it, higher level math is:

1) Intellectually challenging, to such a degree that those wishing to enter the field need to have a certain level of intellectual prowess to do so. This creates some levels of mystique, with a sprinkle of elitism and gatekeeping.

2) Driven (among other things) by prestige. And the more pure the math is, the more prestigious it is.

3) So complex that people can spend their entire working careers chasing a handful of problems. The amount of time researchers spend on very specific problems is mind-boggling, if we think about the results.

4) Intensely captivating for the people deep in the weeds.

And the deeper you get, the longer you study, the more you start to value things like "mathematical beauty", and may start to view math as a form of art.

Like many similar fields, you end up with this ivory tower where people can dedicate their whole lives to thinking deeply about extremely niche and theoretical problems.

Where was Terence Tao where other workers were being replaced by immigrants, robots and other automation?

Academics and white collars now get to experience what blue collar workers experienced in the past.

Same as what developers in USA experienced who were and are getting replaced by Indians.