Comment by zkmon
1 day ago
When Deep Blue beat Kaspaorov, it was not the end of career for human players. But since mathematics is not a sport with human players, what are the career prospects for mathematicians or mathematics-like fields?
1 day ago
When Deep Blue beat Kaspaorov, it was not the end of career for human players. But since mathematics is not a sport with human players, what are the career prospects for mathematicians or mathematics-like fields?
I think its worth saying two things:
1. This result is very far from showing something like "human mathematicians are no longer needed to advance mathematics".
2. Even if it did show that, as long as we need humans trained in understanding maths, since "professional mathematicians" are mostly educators, they probably aren't going anywhere.
I wouldn't say professional mathematicians are mostly educators. The educating that mathematicians do even at graduate level to non-future-mathematicians can mostly be done (not fully at parity due to depth of understanding that we accumulate but close) by non professional mathematicians. Most of the education is to other current/future mathematicians in my limited opinion.
> ... are mostly educators, they probably aren't going anywhere
Educator business survived so far, only because they provided in-person interactive knowledge transfer and credentials - both were not possible by static sources of knowledge such as libraries and internet. But now all that is possible without involvement of human teachers.
Tao's broad project, which he has spoken about a few times, is for mathematics to move beyond the current game of solving individual theorems to being able to make statements about broad categories of problems. So not 'X property is true for this specific magma' but 'X property is true for all possible magmas', as an example I just came up with. He has experimented with this via crowdsourcing problems in a given domain on GitHub before, and I think the implications of how to use AI here are obvious.