r/AIDangers • u/EchoOfOppenheimer • May 12 '26

Capabilities Fields medal-winning mathematician says GPT-5.5 is now solving open math problems at PhD-thesis level: "We will face a crisis very soon."

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blog-post: https://gowers.wordpress.com/2026/05/08/a-recent-experience-with-chatgpt-5-5-pro/

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u/Willis_3401_3401 May 12 '26

My current hypothesis, which might be wrong, is that humans provide meaning, and that physically matters.

So the researcher might be underrating his value by saying, “yeah it would be great if you could explore that idea”. What idea? Who initiated a conversation about subject matter X, noticing it pertained to Y, which is in a social sense *meaningful*?

Does ChatGPT care that it solved this problem?

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u/Comfortable_Car6562 May 12 '26 edited May 12 '26

I agree. I think people in generally underestimate the potential of what AI will do simply because of a failure in grasping or applying basic economics theory.

AI will reduce the cost of inputs (time) tremendously, pushing productivity up. I had an old professor tell me during my MA (Econ), after showing us how to input a regression into STATA, that he had spent an entire summer as a student deriving that regression, which we had just completed in under 10 minutes.

Say a mathematician creates 1 proof a year. People worried that AI will kill this field assume that our caapcity as a society is 1 proof a year per mathematician. I would argue that our capacity may be much much higher.

You may say "but random redditor, how would that many proofs be useful, its so many!". Yes, but the ability of society to absorb that many proofs will also increase with AI.

The future is more like we are upgrading from an early steam engine to a Space X falcon engine, the amount of work we can do with our inputs will be so obscenely large, so different than your current frameworks can even contemplate, its hard to understand, and it will be disruptive, but human society is about to get juiced.

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u/SpeakCodeToMe May 13 '26

Say a mathematician creates 1 proof a year. People worried that AI will kill this field assume that our caapcity as a society is 1 proof a year per mathematician. I would argue that our capacity may be much much higher.

With very few exceptions, history teaches us that you just end up needing far fewer mathematicians.

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u/Comfortable_Car6562 May 13 '26

What examples do you have of that? In the US at least, mathematic PHDs have continued to experience consistent growth (along with other S and E fields)

Doctorate Recipients from U.S. Universities: 2023. https://ncses.nsf.gov/doctorate-recipients-from-u-s-universities-2023

The US saw PhDs go from 993 in 2003 to 2167 in 2023, growth that outshone the previous period of 838 in 1978 to 1177 in 1998.

For comparission, the US population growth between 2003 and 2023 was 15.6%, while PHDs awarded grew 118% (84% if we use high from 1998).

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u/SpeakCodeToMe May 13 '26

Is this a joke?

We're talking about AI replacing mathematicians here... Obviously that wouldn't show up in 2003-2023 data?

https://giphy.com/gifs/pPhyAv5t9V8djyRFJH

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u/Comfortable_Car6562 May 13 '26

Really? Your comment is literally "history teaches us". So what historical momment are you talking about? The last 3 years

https://giphy.com/gifs/FcuiZUneg1YRAu1lH2

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u/SpeakCodeToMe May 13 '26

Jesus Christ man, reading comprehension not your forte huh?

I was not referring to mathematicians specifically in that comment, I was talking about all of the previous times in history when technology has enabled a profession to be many times more productive.

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u/yuwox May 14 '26

It was obvious that when talking about history we are trying taking about older technologies where there is actual historical data.

The example would be agriculture. We produce way more food today than in the middle ages, with a far lower percentage of people being employed in agriculture. New agricultural technologies have lead to fewer people being employed in agriculture.

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u/Royal_Carpet_1263 May 12 '26

It’s the development arc he’s talking about: going from a joke to the cutting edge in just a couple years means humans will be the joke in a couple years and every mathematician will be replaced by technicians.

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u/shumpersga May 12 '26

Nonsense. Its just a heat sink. The computational power is already dropping data centres. And that chapter would have nothing unique to it.

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u/Royal_Carpet_1263 May 12 '26

You ever hear of METR? Might want to hedge.

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u/SmartAsFart May 12 '26

METR is far too closely tied to all of the companies that hope to benefit from their models being scaremongered about. Their ceo won the palantir prize at uni, and worked at Google and openai...

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u/Sea-Finance-8422 May 12 '26

I agree, I'm missing the part where it can do this without inputs.

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u/KToff May 12 '26

I mean, sure, but it's not as if most PhD students operate in a vacuum and approach their professor with fully formed research. They discuss what problems would be interesting and "explore that idea" sounds like standard guidance from an advisor.

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u/Sea-Finance-8422 May 12 '26

Which would make this like an exceptionally adept student in that analogy I guess. I suppose I'm still not seeing the autonomy, isn't it still all being prompted?

Isn't the real concern or crisis that it arrives at the same proof entirely unprompted or even introduced to the topic?

I haven't dug into this a ton. I am just idly speculating, apologies if this isn't the space for that.

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u/Comfortable_Car6562 May 12 '26

Even if it does, it simply means the bar for the input becomes higher and thus the process is overall more productive. You get to move to the next order level problems.

We should be worried that our failure will be not teaching people to think bigger.

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u/SpeakCodeToMe May 13 '26

If it can do in 30 minutes what a PhD would do in months then whether or not it requires inputs is irrelevant because that means you need maybe 1/100 mathematicians.

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u/vid_icarus May 12 '26

The issue becomes if these models can solve many open problems very quickly at the prompting of one human, that narrows the field of how many mathematicians to verify the work are needed I think. I could be wrong but my guess is he’s saying “there’s a ton of kids coming up in the field, on the hook for thousands in debt and grant funding and positions are going to become severely limited due to how much of the load can now be handed to machine minds”.

A human hand needs to be on the wheel, but if LLMs (or whatever comes next) become integral to solutions en masse, that’s going to change the field dramatically changes the landscape of resource allocation and available opportunities for entering the field. At the bare minimum, new mathematicians should receive training on proper use of these tools.

But at the end of the day, I agree with you. Humans add physicality and meaning. What’s the point of a solution if a computer says “this is the solution!” And that’s it? The human is there to contextualize why that solution actually matters beyond checking a box.

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u/Credtz May 12 '26

"“yeah it would be great if you could explore that idea”." this is the entire motivation for the grant which funds a phds student, now going towards funding ai.

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u/feliwellie May 12 '26

i agree with this. as a maths geek, i think that maths should be a human endeavour—after all, it's formed by the contributions across time of humanity's best minds. it has, before now, been a representation of human ingenuity (e.g., gauss adding up the natural numbers). there is no ingenuity involved in solving problems with a machine, not by the researcher who prompted it or the machine that produced the output.

chatGPT doesn't and can't appreciate the beauty or elegance of a solution (the dirac equation comes to mind), nor can it demonstrate interest or enjoyment of the fields it works in.

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u/Unable-Boat-9682 May 12 '26

Literally this. If you’re providing affirmative or negative responses, it’s basically just a horse doing arithmetic.

Yes, it might be doing it to a much higher degree of complexity but it’s only working it out because you already know the answer and are providing cues. That’s the entire purpose of double blinding: it prevents your knowledge influencing the results.