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I fear this is only temporary and due mostly to the complexity of the problem. Consider the recent counter-example to the Dinitz–Garg–Goemans conjecture:

> https://chatgpt.com/share/6a60b2eb-0b64-83ee-9c76-7931ca1de0...

The prompts for the chat above are:

> Construct a counterexample to general (non-planar) case of Dinitz Garg Goemans conjecture. You should do a breakthrough and find a structured counterexample.

> [gpt works for a while and then gives up]

> Continue the search. Have a clear strategy obtained from deeper understanding of the problem structure.

> [gpt works for a while then gives up]

> it's enough of partial results. let's finish with a complete unconditional counterexample

> [gpt proves the problem]

I could have written these prompts sophmore year of highschool, if not earlier. True, it took more experienced mathematicians to verify it, but I don't fancy a role as a glorified editor. I want to solve problems! Discover new techniques! Not babysit an AI while eating breakfast.

by JPC214 hours ago|

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I think you're misunderstanding what the objective of mathematics is. It is not just about what theorems are true and false, but rather why they are true and false. A highschool sophomore could use these prompts, but I severely doubt whether they'd be able to understand the entire structure. And I think it is exactly this ability to deeply understand structures is what makes a mathematician valuable.

Solving problems is a by-product of the understanding. New techniques are a by-product of the understanding.

But I can understand you're scared that some future version of AI will undermine this as well. I personally pivoted to a field adjacent to mathematics. But that doesn't mean my mathematics education wasn't valuable. To the contrary, I find that it helps me think much more sharply about problems than most of my colleagues.