Disgusted by AI?

Marcus Zibrowius, Professor at Heinrich Heine University Düsseldorf

AI models are making mathematical progress at an unimaginable scale. There’s now a reasonable expectation that soon, we will be able to prove a theorem, or find a counterexample, at the touch of a button.

But the overall reaction of our mathematical community is closer to panic than it is to enthusiasm. AI is perceived as a threat, not just to humanity as a whole (which is a different story) but to mathematics specifically. We are collectively appalled by formally-verified but fully inexplicable proofs, and even more disgusted by companies that churn out one AI-generated (and equally verified) paper after the other without even having a single person on the team able to explain them.

We talk about the good old days when mathematics was about building a community of common understanding, facilitating personal growth, celebrating beauty.

What a feel-good fairy-tale that is!

In fact, our values have always been about who got there first. Collectively speaking, the one thing we, as a mathematical community, have always valued most has been a proof of a hitherto unproven theorem. It was not a nicer proof of a known result, and certainly not a beautiful exposition of a known proof.

You think I’m being cynical? Allow me to argue my point.

Follow the money.

Explaining a proof may have earned you an applause or a compliment. Completing a proof –\text{\textendash} and doing so faster than anyone else –\text{\textendash} is what has always had the potential of getting you a job. Also, when did you last write a grant proposal promising to deepen the communal understanding of an existing proof, or to find a more digestible proof to a proven theorem? How does the amount of funding you have acquired for promising new results compare to the funding you got for explaining existing ones?

Reflect on common behaviour.

What is more likely to keep you up at night? A fellow mathematician threatening to arrive at “your” result ahead of you, or a fellow mathematician having trouble understanding your arguments?

The other day, an eminent mathematician confessed to me over lunch that they worked through their summer holidays to get out a paper with a new construction that they got out of an AI model. Anyone asking the model the same question would get the same ingenious answer, so the logic went, hence they needed to publish this immediately.

On the flip side, I’ve sat through talks where the speaker afterwards, privately, declared “Today I have given a talk that was utterly incomprehensible. I’ve always wanted to give a talk like this.” To be fair, this was a singular, extreme case. But we would not tolerate this kind of behaviour if we really cared so much about a community of common understanding.

Acknowledge past grievances.

Personally, I vividly remember how, at a panel discussion on “Future Directions of Algebraic Topology” at Stanford in 2012, one of the younger members of the audience raised the question: What can we do to make mathematical culture more like music culture, where presenters are valued as much as composers? At that time, the idea of AI was still very much hypothetical. The question was about our very own, human culture.

Read the Leiden declaration.

The Leiden declaration, which has been widely endorsed by the mathematical community, lists the following as one of our five mathematical “values”:

Results are attributable to specific authors who take credit for their discovery and assume responsibility for their correctness. These principles ground the merit-based standards to which we aspire in mathematical research.

That is just another way of saying that the one thing that really matters for your standing within the community is that you arrive at a new result first.

So why am I saying this? Because I completely disagree with the notion that AI companies have hijacked our mathematical culture and turned it into something new and unrecognizable. They have not. Quite the opposite. They are playing to our rules. They are even solving our problems, problems that no one else cares about! They have just taken our existing culture to its extreme.

And now, we are disgusted!?

I would argue that what we’re really disgusted by is a key aspect of our own culture, now that we see it more clearly than ever before. We’re disgusted by the idea that getting there first is all that matters.

Let’s be honest about what was and what is. We defined our priorities. AI serves them better than we can. Perhaps, the priorities were off.


Received 25 September 2026.

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15 responses to “Disgusted by AI?”

  1. J Avatar
    J

    Exactly, this is why many of us outside the formal mathematics community feel schadenfreude more than sadness at the predicament that community finds itself in. Collectively and institutionally succumbing to Goodhart’s law and then complaining you got out optimized for the metric sounds like a concert of very small violins.

    1. M Avatar
      M

      Nah, I don’t think thats the reason. Its just a characteristic of being a certain type of person. It’s like when large parts of computer science got crashed. There was no legitimate schadenfreude, except you enjoy seeing others who never tried to harm you (and who express feelings of loss because they cared for something that got crashed) in bad situations.

      The reward system in math has not been much different from other sciences and other activities of humans, its the one naturally given by nature, which is why its hard to come up with an alternative that naturally works well.

      Maybe mathematicians will figure out a new way of rewarding contributions, I am quite optimistic. All the debates you can see right now, and mathematicians confessing their feelings, you should take it as a sign that the old system might not have produced extremely many bad people. Most (but of course not all) detrimental voices I can hear in these debates seem to be from math external.

      We can come back to this in 1-2 years from now and re-evaluate 🙂

  2. Anonymous Avatar
    Anonymous

    Yeah, I can’t help rolling my eyes when I see people suddenly claiming that what really matters is human understanding, when for decades (centuries?) big shots have been publishing poorly written papers, and plenty of successful mathematicians don’t even make an effort to present their arguments clearly. Surely, if you’re smart enough, you can wade through my slop?

    1. just different Avatar
      just different

      There’s no reason to believe your slop is worth wading through, which is not the case for big shots. Which of course doesn’t excuse their badly written papers, but it explains why their tolerated.

  3. Anonymous Avatar
    Anonymous

    If you only focus on that one aspect (being first) then maybe. But there are dozens of others that are more important.

  4. markfhagen Avatar
    markfhagen

    None of the usual criticisms of many of the existing practices of the academic maths community are wrong; many of our norms and practices are entirely insane, the levels of egotism and lack of self-awareness and perspective that are often tolerated are often unreal; we certainly tell ourselves an overly-flattering collective story about who we are and what we are doing; there is certainly unreasonable and unfair gatekeeping, etc.

    Those are also problems that a community of human beings is in principle of correcting through internal struggles and growth, and this in fact has also been happening slowly in the maths community. I have not always been very optimistic about it, even while trying to contribute, but I have seen some things slowly change positively, and have hoped that larger cultural changes would keep working their way into mathematics with time.

    However, it is wholly suspect when people, previously, perhaps, not so vocal on the social and cultural problems of academic maths, suddenly celebrate the AI developments as some kind of revolutionary redress for those problems. That seems either disingenuous — using the language of justice to run cover for a predatory invader with no actual interest in improving community practices and standards and power dynamics — or just naive. The AI labs want to destabilise professional communities and strip them for parts, so that they can sell human capabilities back to the same human societies from which they stole those capabilities. That’s it, that’s the whole thing.

    Someone who thinks there is some kind of justice in, I don’t know, Obnoxious Egomaniac Prof. Fancypants being bested by vast concentrations of power and capital has, ironically, a hugely overinflated sense of the importance of Prof. Fancypants.

    (Also, I think that people who benefited from extensive training within academic mathematics and who have then been able to leverage that training into highly-paid and relatively stable professional careers in industry should be congratulated but, if they are feeling any schadenfreude right now, they probably ought to do some introspection about whether that feeling is really fair or constructive.)

    1. Sirawit Pongnakintr Avatar
      Sirawit Pongnakintr

      (This time I’m actively trying to be civil and not provoking)

      I would like to know the evidence supporting this claim:

      The AI labs want to destabilise professional communities and strip them for parts, so that they can sell human capabilities back to the same human societies from which they stole those capabilities. That’s it, that’s the whole thing.

      Is it an opinion of yours, or is it an empirically observed fact? If empirically observed, then can you explain the methodology that arrives at this conclusion?

      1. Anonymous Avatar
        Anonymous

        Sam Altman first ran the Loopt startup, an unsuccessful hookup app. Then he became YCombinator CEO through personal connections.

        Then he started WorldCoin, a sketchy startup that wants to scan everyone’s eyeballs for a beggarly UBI:

        https://www.technologyreview.com/2022/04/06/1048981/worldcoin-cryptocurrency-biometrics-web3/

        “Deception, exploited workers, and cash handouts: How World recruited its first half a million test users”

        Then he took over OpenAI, purportedly a company in the public interest and slowly converted it into a for-profit company. Dissenters like Sutskever were fired.

        OpenAI whistleblower (IP theft) Suchir Balaji committed “suicide”. The verdict is the result of a half-hour rushed investigation and Balaji’s parents highlight many contradictions.

        This is a specific example. In general, Silicon Valley bought open source developers since 2010, just like it buys mathematicians now.

        These developers advocated every corporate move, claimed that Microsoft was a reformed company and that everyone needed to use the most permissive licenses.

        In 2025 it turned out that there were no reformed companies and all Silicon Valley CEOs bowed to Trump (yes, the same CEOs who forced DEI under Biden).

        Now after they stole all the developers’ IP, they try to fire them and force an assembly line vibe coding software development style (fortunately only successful on paper).

        This is exactly the playbook they are using on mathematicians now:

        1. 1) Buy some big names directly and through foundations.
        2. 2) Have these names blog and coerce students and colleagues to use AI.
        3. 3) Flood the zone with AI news, so mathematics is inextricably linked to AI as if no math had existed before 2023.
        4. 4) Introduce assembly line mathematics where mathematicians will be working for increasingly lower salaries to babysit machine proofs and make them shorter.

      2. Mark Hagen Avatar
        Mark Hagen

        >If empirically observed, then can you explain the methodology that arrives at this conclusion?

        Basic understanding of capitalism. Based on the rest of your comment history here, that’s all you’re going to get.

    2. anonymous Avatar
      anonymous

      Very well said

  5. Anonymous Avatar
    Anonymous

    Did openAI spam hundreds of billions of tokens on the Navier-Stokes millennium problem to “test their model” or did they do it to beat Anthropic and show the public how powerful their product is? I don’t like the word “disgust” but I admit my feelings are rather emotional, I don’t see any benefit to having someone who doesn’t understand what they’re doing solve a problem with AI over someone working in the field just to know whether a statement is “true or false” maybe a few months earlier. If openAI truly spent only “3 hours of compute” per problem then is it really that substantial of a contribution? And using open math problems as some kind of “strength benchmark” to me comes across as wasteful and disrespectful to the field. Additionally AGMAI made certain recommendations for the release of AI results and openAI did not really act on them in good faith.

    1. just different Avatar
      just different

      It wasn’t OpenAI or the broader public who set up the Millennium Prize problems or who touted mathematicians as geniuses whose job it was to solve extremely difficult problems. We did that, either directly or by allowing it to happen, and we did it mostly out of intellectual laziness and an unwillingness to think critically about what the point of mathematics research is.

  6. just different Avatar
    just different

    Indeed. I’m neither an AI booster nor an AI ascetic, and I think what AI companies are doing is predictably exploitative, but there is absolutely no doubt that the current “crisis” is mostly chickens coming home to roost. The resulting self-reflection by the mathematical community is healthy; let’s hope it results in more thoughtful practices.

    Incidentally, those giant baby juncos at Stanford were probably cowbirds. 😉

  7. anonymous Avatar
    anonymous

    tldr; There’s two kinds of mathematicians, the first kind prioritizes understanding, the second kind prioritizes something else that’s not understanding. The complaints of these two kinds with ai are different. The former have a right to be disgusted, the latter are not even disgusted because of those reasons. This post is trying to put them all under one umbrella.

    The first kind is arguably a minority (a large one, I’d say), and I think we can agree that the people who are/were saying that understanding matters are honest about it, have always prioritized understanding. For them, the theorems, papers etc. were merely an operationalization[1] of being a mathematician.

    The culture of people in this camp is being hijacked and they have every right to be “disgusted”.

    On the other hand, you have people who say that prestige, problem solving[2], technical aspects [3] of doing mathematics has always been an important aspect of doing mathematics. Those people are not even showing disgust in the way the former camp does but they are complaining about other things.

    The catch is, that the most “successful” mathematicians do care about understanding (a coincidence?) and that it was natural for them to take the lead, since it’s easier to gather around a lot of famous and influential names. And now this post is weaponizing the coincidence that the people around which the community has gathered[4] is of the first kind that prioritizes understanding, even if many of them are of the 2nd kind.

    [1] A beginning for mathematics, D. Litt

    [2] Why I didn’t sign the Fields medallist letter, T. Gowers

    [3] Who will become the new mathematicians of math 2.0?

    [4] Endorsers of “A Severe Misalignment of AI in Mathematics”

  8. Charles Blouin Avatar
    Charles Blouin

    Let’s imagine a brilliant student who completed their PhD in 2023. They did not prove anything new, but their work which included lectures, a book and a thesis that did an amazing job at explaining in a novel and straightforward way a relatively new field of mathematics. The work from the student was exceptional: hundreds of professional mathematicians and grad students have used it to quickly gain an understanding of that field. New progress has already been made thanks to the additional exposure from this author. Now, it is 2025, and this person is applying to your university. You are on the hiring committee. The candidate is proposing to extend their work to other adjacent fields. With the help of a few students, they want to create exceptionally high quality books, lectures, workshops and conferences dedicated to improving mathematical understanding at a professional level.

    You know that the impact potential of the candidate is major. They could help tens of thousands of mathematical professionals and significantly contribute to the understanding of the field.

    Did they really have a chance of getting hired in 2025? I believe not. And a candidate half as good has no chance. Students working under this candidate would ‘hurt’ their career prospects in academia. They would have a hard time getting grants.

    The incentives have to change. Saying ‘we care about human understanding’ when the entire system assigns a value of 0$ to understanding is meaningless.

    The AMS created a prize in 2025, the Elias M. Stein Prize for Transformative Exposition. This a a step in the good direction.

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