Comment by light_triad
1 day ago
This is the taste question applied to Mathematics in a similar way it's been applied to code. In an era of AI abundance, the question becomes what the goals are and what gets verified and digested (adopted by users). Goodhart’s law: the goal of producing code is not just about maximizing the number of tokens used, but the productivity gains and economic surplus.
This could serve as the template for any field in the age of AI: "We are not trying to meet some abstract production quota. The measure of our success is whether what we do enables people to understand and think more clearly and effectively about math (or products, or science, or hardware...)"
> but the productivity gains and economic surplus.
I think you might be missing out vast swathes of human experience here. Some things are about joy, or god help me - fun.
(For the record I think AI has a role to play here as well)
I find AI a joy to use to build software. I was never the type of engineer who loved the code itself. I was always the type who wanted to see how users would react, how metrics change based on the feature, etc. The code was the most boring part for me generally.
This is the template any field should have in the face of AI: screw AI, forget it. If you're using it, it's a disrespect to the field. Let's continue without it. I think that's the only sane approach.
William Thurston's argument (from the quote) was that the point of math isn't to produce more math but to better understand the nature of reality, just like the point of code is not to generate more code but to increase user value.
AI is a tool that reshapes knowledge work but the ultimate goal remains about value.
I posit that one cannot decouple understanding from a healthy social environment in which to practise math. And AI destroys that.