What's the future for pure math research in the age of AI?
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What's the future for pure math research in the age of AI?
Unofficial Hacker News client; not affiliated with Y Combinator.
jaykru · · focus · HN ↗
1. An essential goal of mathematics is human understanding. The computation of proof terms doesn't necessarily enrich human understanding. The proof of the four color theorem result is a good example, and formal verification/SAT solving gives many more: these are results that can be trusted up to our trust in the system used to produce them, and they can be used in practice, but they don't necessarily enrich our understanding. Imagine a computer with near infinite proof search powers set loose with the current human definitions, theorems, and understanding of mathematics. Suppose it constructs a proof for a new theorem at our mathematical frontier. The shortest such proof in terms of currently understood definitions and concepts could be so long and mechanical that the entire lineage of humans until the end of the universe could not finish reading it. So though it overlaps with the activity of mathematicians, this type of computational proof search is not mathematics as such. This is an important distinction that many people do not seem to grasp and some dismiss as cope.
2. The human activity of theory building, rendering otherwise monstrous proofs like the one I discussed above into light conceptual arguments a person can understand, appears at this time out of reach of models. Maybe they will do this in the future, but it is not yet the case. Human theory building drastically compresses the spaces of theorems and their proofs: this is why great theory builders like Groethendieck are so important to the field; grinding has its value too, but runs up against computational limits in both humans and computers. These limits are collapsed by the conceptual shortcuts created by theory builders.
Gowers has a nice and arguably better-grounded article on the mathematical capabilities of recent LLMs that I think is enlightening to read alongside Wolfram's bird's eye view of the implications of those capabilities: <a href="https://gowers.wordpress.com/2026/08/12/what-sort-of-maths-are-llms-good-at/" rel="nofollow">https://gowers.wordpress.com/2026/08/12/what-sort-of-maths-a...
btilly · · focus · HN ↗
But it begs the question. What is the value to the rest of humanity that a small group of people possesses something that can be called human understanding? Particularly when that group of people is historically terrible at communication (as is routinely demonstrated in Calculus classes), and most humans are not capable of learning that understanding (though more are capable than think they are capable - that is another story).
I am speaking as someone who nearly finished a PhD in mathematics. I understand why mathematicians would wish to continue in the age of AI. But, barring something like universal basic income, it isn't obvious why the rest of humanity would support them in this endeavor.
jaykru · · focus · HN ↗
[0] <a href="https://www.anthropic.com/research/claude-shaped-science" rel="nofollow">https://www.anthropic.com/research/claude-shaped-science
btilly · · focus · HN ↗
You are simply giving a different argument than the one I'm giving a counter to. Yes, of course, if including human understanding results in strictly better results than AI, then there is an argument for the value supplied by human mathematicians.
But that's an argument that human understanding is on the path to better outcomes. It's not an argument that the intrinsic worth of human understanding is a reason to support mathematicians.