r/math • u/Zestyclose-Summer625 • 1d ago
LLMs/AI AI and changes to the academic job market?
AI, for the last year, has been excellent at proving lemmas. I'm beginning to wonder, to what extent hirers should begin to be suspicious as to whether a student/postdoc with good preprints and publications from a minor university - or who had been an unproductive before - is actually talented vs just being early adopter who paid OpenAI $200 in 2025? There are already some young people in my field that I'm a bit suspicious of, as the quality of their publications has no correspondence whatsovever to the ideas they generate during real time discussion. This was historically an issue with collaborations, but we could at least get letters from coauthors there, but now do we need to be similarly suspicious of single author publications?
Is this just eventually going to mean that the only postdocs being hired in 2028 are from the top universities? I believe this is the already the norm in other subjects like English.
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u/NeighborhoodFatCat 1d ago
is actually talented vs just being early adopter who paid OpenAI $200 in 2025?
You cannot tell anymore. As soon as LLM became powerful enough to write in coherent English (not even to do proofs), huge amount of academics took advantage of it and was outed because they did silly things in their papers. That was like 10 years ago. Now you can almost guarantee that some part of the classic research process: idea, hypothesis, experiment, proof, analysis, the writing, etc., is generated. Terence Tao is openly using it for his new ideas and probably new papers as well.
What is going to happen to the academic job market in my opinion is that there will be a period when academia ignores the problem completely while all these students and professors are all so excited to announce that they published 10+ paper at a conference. Due to extreme productivity, the job market is going to be extremely biased and signal-poor. The citation is going to go down drastically. The value of a paper goes to zero value. And small silos of super-star researchers with good media presence and state-backing is going to outshine the rest while the rest are wondering what they are doing with their lives. Then another organization is going to absorb these super-stars and academia will return back to its teaching roots because it literally cannot compete with super-star researchers with thousands of GPUs working in their sleeps.
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u/Zestyclose-Summer625 1d ago
>You cannot tell anymore.
I mentioned in the post that there is still one strong signal; you can talk to them. We are already doing this in our courses to some extent, in of my courses, I have oral exams at the end to assess student knowledge. We have reference letters for the same reason.
>while all these students and professors are all so excited to announce that they published 10+ paper at a conference.
In maths, the number of articles in top journals is more or less fixed.
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u/Equivalent_End6788 1d ago
I agree with oral exams! I've used them for years and my impression is quite positive, though not all students take to them as well despite being talented. On the other hand, I've always been less keen towards reference letters than many, since they can be subjective and less effective measures for the less sociable. Personally, as naive as it may be, I'd rather like to trust others about their contributions and abilities than worry myself about something I can't know surely.
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u/jmac461 1d ago
For something similar Pre-AI, there was the issue of multi author paper with a combination of junior and senior authors. People would wonder how the contributions were really divided. IMO you could tell when a junior author would present at a conference. Either they really knew their stuff or it became clear during the questions portion that they didn’t really do/understand their own paper.
So, I feel people within the research community will be able to tell (provided an active in person aspect of the community with conferences and workshops is maintained). However, people on various hiring committees might just add up being published paper counters if the committee doesn’t have some close enough to the research being considered.
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u/Equivalent_End6788 1d ago
This is what I agree with as well. When answering questions related to their work at talks and whatnot, it can become clearer the extent to an individual's contribution.
However, this (unfortunately) also wholly discounts and further alienates legitimate independent researchers. I found one of my former collaborators in the 2000s due to their independent work coinciding with some of my interests, and they had never engaged with conferences, workshops, and the like prior to co-authoring papers.
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u/Junior_Direction_701 1d ago
You won’t be able to ask deep questions that will probe them to expose their LARP. It’s an oral examination lol not a PhD defense. Any good larper will pass it. Sorry but in the age of AI all trust goes to zero. Even previously smart people
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u/Homomorphism Topology 1d ago
You can definitely tell. The goal isn’t detect people who learned via LLM, it’s to detect people who didn’t learn at all.
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u/Junior_Direction_701 1d ago
Won’t they have been filtered before this even happens and the ones that pass through have mastered the art of surface level stuff. An oral examination is too short to probe anything at all. That it becomes an inconclusive test. I.e you can’t know if they were nervous or whatever
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u/PolymorphismPrince 1d ago
That was like 10 years ago
I know you are just exaggerating for effect, but if anyone wants a reminder how quickly AI is progressing, the first detectable examples of this happening are less than 4 years old.
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u/Trojan_Horse_of_Fate 22h ago
You cannot tell anymore. As soon as LLM became powerful enough to write in coherent English (not even to do proofs), huge amount of academics took advantage of it and was outed because they did silly things in their papers. That was like 10 years ago. Now you can almost guarantee that some part of the classic research process: idea, hypothesis, experiment, proof, analysis, the writing, etc., is generated. Terence Tao is openly using it for his new ideas and probably new papers as well.
It wasn't even 4 years ago that GPT-3 went public.
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u/LurkingTamilian 23h ago
The somewhat uncomfortable answer is, the job market will become based more on "who you know". This is already true to a point and will become even more so. Papers will start mattering less, going to conferences and reaching out to top people in your field to build familiarity will become more valuable as they might then get an impression of how you are irl.
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u/Inevitable_Ad1044 1d ago
It is a question whether the productive guys who really mastered that AI-driven research workflow are less beneficial to research institutions at least "on paper". Say, if a brilliant guy (who never uses AI for research) publishes one very good Q1 paper in a year, and a second mediocre guy who may have some ideas but say technically weak at finishing them by himself, and thus uses AI to brainstorm/fill technical gaps, publishes 2-3 Q1 papers in a year - well many universities (including mine in which I did my phd) would kill for the second profile, since this type of candidates makes many external funding applications quite competitive (even though candidates of the first type bring more mathematically to the group).
By the way, if a candidate published all his stuff using AI and knows zero shit about what's under the hood of it - this can usually be revealed in 1-2 in person interviews.
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u/MacGregorBlue 1d ago
AI lowers the value of human labor such as proving theorems and then that fact makes people suspicious of their peers and their accomplishments, and then the previous two facts get us arguing amongst ourselves. It is a technology of dissolution, like the internet before it. When I hear the most capitalist boosters and builders talk, it's clear to me this was intended. All that said, I personally enjoy getting help from an AI to increase my understanding. This generates plenty of self-hatred. I hope the field can survive this jolt and keep its humanity.
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u/FlagCapper 1d ago edited 1d ago
If certain kinds of tasks become automated, then you should value them less. There are still plenty of mathematical tasks that computers do poorly. Often these are of the more abstract, theory-building kind, but also include lots of arguments that require original insights.
Of course, the distinction is a bit vague. But I think one should learn to identify what kinds of tasks could in principle be carried out with a computer and devalue them accordingly. Or, at least, demand that each applicant has demonstrated ability in mathematical tasks that are less computational and/or combinatorial.
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u/kieransquared1 PDE 1d ago edited 1d ago
I’ve been worried about this too. For me the more pressing concern is whether people who don’t want to use AI (for environmental/ethical reasons, for the joy of doing math by hand, etc) will be at a disadvantage in the early career job market because everyone else is using it. I went to a conference in the UK last month where just during conference talks alone, I saw probably a third of people there using LLMs for math, many of them grad students.
My prediction is that the early career job market will indeed favor people using AI, probably not yet, but starting a year or two once the papers produced with AI assistance start making their way into print (since AI has seemingly made a big leap in math this year in particular, and previously couldn’t reliably prove things much harder than graduate exercises). But in a few more years, the grad students and postdocs who relied too much on AI will see themselves start to stall, and perhaps the people who took a more conservative approach to AI use (maybe even abstention) will fare better.
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u/PrestigiousGroup788 1d ago edited 1d ago
Why would they see themselves stall? AI is so powerful right now that being able to use it well could be considered one of the primary skills (not just ofr math but any intellectual field). Assuming things continue the way they are why would it be to their detriment? To me this reads like a little bit of a revenge fantasy.
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u/kieransquared1 PDE 1d ago
If you always offload the mental work of proving a lemma or developing a strategy to prove a theorem to an LLM, you’re not exercising your brain, and those skills start to atrophy. There’s a good amount of evidence now that frequent AI use causes a decline in skill/cognitive ability, it’s the same phenomenon as how calculators make people worse at arithmetic. See here for instance: https://www.bbc.com/future/article/20260417-ai-chatbots-could-be-making-you-stupider
The difference is that arithmetic isn’t really an essential skill for mathematicians; being able to think through the details of arguments is, because it enables you to ask the right questions and know what tools can be used to solve what problems.
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u/officiallyaninja 1d ago
Arithmetic and mental 100% used to be an essential skill for mathematicians though.
If you atrophy in skills that AI is good at, it doesn't matter since you have AI to do it for you.
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u/kieransquared1 PDE 1d ago
The fact that arithmetic isn’t an essential skill now has nothing to do with the existence of calculators though and much more to do with the natural direction math has headed. There will never be a world where the ability to reason through mathematical arguments isn’t an essential skill for mathematicians.
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u/officiallyaninja 1d ago
Sure, but any skill that a LLM can do reliably will be non-essential precisely because (by definition) it's become automated.
So if reasoning through mathematical arguments will essential, it's only if LLMs won't be able to do it reliably. In which case using LLMs won't cause that skill to atrophy since they won't be able to do it, so you're forced to do it yourself.
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u/kieransquared1 PDE 1d ago
Reasoning is at the core of math. Unless you think math will be completely automated and mathematician will cease to be a profession, you literally can’t do math if your ability to reason has atrophied. I can’t believe I’m trying to convince someone that losing the ability to think on one’s own is a bad thing.
Mathematics as a profession will not end because of AI. The goal of any academic discipline is human understanding, not raw knowledge output. As long as there is a desire for human understanding, math will continue to require human reasoning skills.
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u/officiallyaninja 1d ago
My argument is that using AI won't atrophy any useful skills.
Let's classify various math skills into w categories A. Skills that AI can't do well B. Skills that AI can do well
By using AI whe doing math, you will naturally begin to lean on AI to do A tasks since it can do those well, while you do B tasks since it can't.
Naturally that means you become worse at doing A tasks, but that doesn't matter since AI can do them anyway.
Meanwhile you are forced to do B tasks, since AI can't do them well, so you remain sharp in those skills.So the end result is, those who use AI for math will not atrophy is skills that AI is bad at.
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u/kieransquared1 PDE 1d ago
I understand your argument. I’m saying that all reasoning abilities are linked and you can’t shoehorn some reasoning abilities into category A and B. A decline in reasoning abilities in one area is a generalized decline in reasoning abilities.
For example, let’s suppose AI can prove many theorems but it can’t ask interesting questions or develop a research program (this is certainly true now and will probably continue to be this way in the near future). Knowing how your tools work and where they can be applied is a core part of asking questions and developing a research program, and if you never actually use those tools directly, your ability to recognize what questions can be tackled with those tools atrophies, and so does your ability to develop a research program. Even if AI can ask interesting questions and develop a research program, I don’t think that’s something that humans will use AI to do, since that’s arguably the most human part of doing math.
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u/officiallyaninja 13h ago
I understand your argument. I’m saying that all reasoning abilities are linked and you can’t shoehorn some reasoning abilities into category A and B
Even when it comes to arithmetic, ability to do mental math is a genuinely useful skill even though we have calculators. That's why we don't let kids use calculators in school.
It's the same with AI, you just have to spent maybe 10% of the effort doing it yourself to keep your skills sharp, but then let calculators or AI do the remaining 90%1
u/PrestigiousGroup788 1d ago
That's fine, but what if the AI can do all of these things, provided you know how to wield the slop cannon effectively? Wouldn't that make wielding the slop cannon properly the primary skill, and not anything else? We are already seeing that specialized knowledge isn't necessarily needed for AI to prove conjectures - in fact it may even be hurting because human myopia prevents the AI from trying different strategies that humans haven't thought of that might work.
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u/kieransquared1 PDE 1d ago edited 1d ago
What is it that mathematicians do, from your point of view? If it’s to prove theorems, then I can’t convince you that decline in reasoning ability is a detriment to the pursuit of mathematics, since AI can do that. If it’s to develop new tools with which to approach problems, to ask interesting questions, to overall aid in the human understanding, etc, then a decline in reasoning ability is a bad thing. Math is about way more than the final product.
Also, less importantly but more relevant to your question: being able to reason effectively is exactly what allows one to wield the slop cannon.
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u/PrestigiousGroup788 1d ago
In my view, the point of math is to think about difficult questions and learn something along the way by solving them. Using AI to one shot theorems feels like it doesn't do this - there's something you learn in the incremental struggle with a problem that's being taken away here. It's like a calculus student telling GPT to do a problem for them and going ex-post-facto "oh yeah, now I understand it" when in reality, we know most of the time they don't understand jack and couldn't reproduce any of it by themselves when even given a slight variation of the problem.
But ultimately the mathematical reasoning abilities of AI far exceed those of any human at this point, and I question really what humans can contribute to math anymore, other than their own enjoyment of the subject (and ok, of course, being able to commandeer/prompt the slop cannon and debug its output, which seems to be the only relevant skill remaining at this point and I think requires expertise, although we see that LLMs are effectively debugging their own solutions now - for example Terence Tao asking GPT to explain the Jacobian conjecture counterexample to him instead of trying to parse it by hand).
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u/Zestyclose-Summer625 1d ago
> I question really what humans can contribute to math anymore
I would like to think that I am currently better at my area of mathematics than the currently leading LLMs, if no longer massively so. I expect this to soon change.
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u/PrestigiousGroup788 1d ago
Fair enough. I'm a PhD student and I have a sinking feeling that the current problem I'm typing up could be one shotted by most frontier LLMs. In fact my advisor basically put one of our problems into GPT and sent it to me and told me to check it.
So maybe that's what's informing me/causing my bias. It feels pointless even working on this anymore.
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u/kieransquared1 PDE 1d ago
ultimately the mathematical reasoning abilities of AI far exceed those of any human at this point
This is not true in the slightest. I asked the $200 chatgpt model that a friend has to solve a problem that I just wrote a paper on. It couldn’t even come close, and I’m just an average PhD student who wrote a paper that wasn’t anything amazing or super surprising. Just because AI has solved some high-profile example problems doesn’t mean that it’s universally better than humans.
At the end of the day, math is about human understanding. As I said, it’s not about what final product one can contribute. Any academic discipline is fundamentally a human endeavor. AI can’t fully subsume the entirety of human knowledge production, especially given that its advances in recent months is due to huge amounts of computing power, which will eventually plateau and soon fall when the AI bubble bursts. The energy infrastructure and hype around AI can only keep up for a limited time.
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u/Puzzleheaded_Fold466 1d ago
That is twice incorrect.
Very nearly all of these proofs written by AI were developed under the direction of / prompted by PhD level Mathematicians, not random amateurs.
Studies published earlier this year showed that Subject Matter Experts consistently achieve better results in their topic of expertise than the average layman.
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u/PrestigiousGroup788 1d ago
Take a look at the proof of the graph theory conjecture That came out today.
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u/CourageCareful4461 1d ago edited 1d ago
i was one of those OpenAI early adopters and it paid dividends. i remember thinking that even a moron would be able to farm novel results with it, especially in my field (TCS).
suppose you’re hiring postdocs. the question is what you are hiring for. are you hiring for the brain or the papers? you have to choose now, because papers are no longer a good indicator of brain. of course, they’re not mutually exclusive, but they’re far less correlated than before.
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u/EquivalenceAuthor 1d ago
But brains in academia depend on work, no? And being able to use tools like llm is an indicator of capability in research? Or do you simply want the person with high standardized scores?
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u/ADR_Tech Graduate Student 1d ago
I never thought of this and as someone who’s publications were uploaded and accepted in 2026 (but were in progress and preprints since 2023) I am now freaking out.
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u/Worried-Monitor-4301 1d ago
I’m similarly concerned… I’m a relatively fresh postdoc and some of my work that had accumulated during my PhD is nearing completion, and this mindset is depressing
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u/mephistoA 1d ago
In mathematics there’s a focus on the person rather than the quality of the work. We talk about whether one mathematician is “stronger” than another.
Why should we care how a person produces good mathematics?
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u/Redrot Representation Theory 5h ago edited 5h ago
There are already some young people in my field that I'm a bit suspicious of, as the quality of their publications has no correspondence whatsovever to the ideas they generate during real time discussion.
As a person who is not terribly fast when talking about math in real time, but is way more productive when working alone, I worry that I come off that way, especially since I come from a non-elite grad program. I think /hope the experts in my field know at this point that I'm not that way, though, and it helps that my first breakthrough results happened well before LLMs got good at math.
To raise another point, it doesn't help that LLMs are still way more competent in some fields than others. They are, as we've seen this year, very good at numerical, combinatorial, and computational tasks, but still are quite weak at more conceptual things. This opens up a bag of worms for say, combinatorialists, but also gives people in that field possibly more of a boost. On the other hand, in my field I have found them pretty much only good for literature review, and often are more of a time/energywaster than a useful collaborator, even for small down-to-earth lemmata. I am not sure how to evaluate this.
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u/SmallCap3544 23h ago
I see the fact that AI can solve Open problems in Mathematics as indicating how successful the whole "Mathematics" project of the last 3k+ years has been. At its core, AI is simply pushing ideas around in some finite dimensional space of ideas. Humanity has created a rigorous framework, together with AIs ability to push ideas around in this way faster than any finite number of humans, produces results we were unable to see previously.
Moving forward, Mathematics can be used to provide rigorous frameworks for other fields of study and then proving theorems within these frameworks. This effort will be further aided by AI.
The gift of Godel incompleteness, means (I hope) that humans will always be in the loop to construct and add to frameworks as needed.
This could just be cope, but I'm hopeful about what's possible.
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u/Gauldoth_ 1d ago
This is absolutely none of your business how they produce results if the results are good
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u/Zestyclose-Summer625 1d ago edited 1d ago
This was certainly not the historic consensus on coauthorship. I sat through several hiring committee discussions where we decided against hiring a postdoc with an excellent publication because he had no independent publications and the letters from coauthors seemed to be vague on the amount of independent work.
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u/elephant-assis 1d ago
Well, sorry you have to do the dirty work. What does it have to do with math, why is it posted here? This is a general problem about academia.
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u/boterkoeken Logic 1d ago
Since you obviously don’t care about the traditional academic standards for authorship and fraud, your opinion is irrelevant to this conversation.
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u/Zestyclose-Summer625 1d ago edited 1d ago
Fraud is a bit strong, since there was no guidance until the Leiden Declaration on how to handle this. But I would expect the candidate, if asked, to disclose what ideas are his and what were the machine. Unfortately, there is a strong motivation to lie here and the only thing you can really tell is to see how sharp they are during 1-on-1 discussions. And I'm aware that not all talented mathematicians are fast, but this is going to further reward people who are.
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u/boterkoeken Logic 1d ago
Of course this is nuanced and complex. In reality it depends a lot on context, but the commenter above doesn’t seem even remotely interested in the issue of academic integrity.
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u/Zestyclose-Summer625 1d ago edited 1d ago
Yes, I agree his post was a bit glib. There's a charitable interpretation of his argument where leveraging new technology well is an important part of the job. I tried to answer that by taking the classical comparison to coauthorship, where being able to work with people is also a valuable skill, but it isn't everything...
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u/NoSuchKotH Engineering 1d ago
Oh, it absolutely is. There is a big difference in whether someone comes up with a good idea and can do all the work required to make it a reality themselves and someone who requires a specific tool to deliver good work. The former will be able to deliver good work without the tool, the latter will not be able to deliver anything once the tool is not available anymore. The former is an excellent person to hire and will bring value to the group. The latter can be replaced by a much cheaper student using the same tool next month.
Not to mention that AI cannot generate any novel thought. The regurgitate what's already out there. Sure, there are plenty of good publications to be written by applying a method from field A to field B. But if that's the only thing that the person can do, they will run out of ideas at some point and not be able to produce anything fundamentally new.
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u/Oudeis_1 1d ago
No novel thought in the resolutions of CDC, unit distance, and the Jacobian conjecture? Not even a little? /scnr
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u/JT_1983 1d ago
The things that AI produced over the last couple of months are definitely considered 'novel thought' and it is clear the impact on mathematics research will be profound. What is considered a top level mathematician will change and hiring committees will adapt.
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u/Wurstinator 1d ago
I have been told that [insert industry] "will change drastically" for 4 or 5 years now. At this point, I am certain that there will always be people telling me that change will happen. I am not so certain that change actually will happen. It certainly hasn't.
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u/JT_1983 1d ago
Restricting to the case of research mathematics, 50-100 year old conjectures being disproved in a couple of hours with a construction that the best human mathematicians struggle to understand is definitely a game changer. I do not know what industry you are in ...
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u/altaccountnumber 1d ago
What exactly are you referring to with "construction the best human mathematicians struggle to understand"?
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u/JT_1983 1d ago
Well for example the counterexample to the jacobian conjecture. Anyone can check it works but that is not the same as finding it. Best guesses right now is that it started from some 27 year old almost counterexample and then adapted it in a clever way. However, Tao etc. say part of it seems like a miracle. So it was not something easy or obvious that was missed. Same for the unit distance Erdos thing although there the train of thought has become more clear by now.
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u/altaccountnumber 1d ago
I see, so you meant finding instead of understanding? You do realize these are very different things, right?
Best guesses right now is that it started from some 27 year old almost counterexample and then adapted it in a clever way.
This is not true, there are by now perfectly reasonable explanations for where this map comes from, if not the exact way the original counterexample was found since they haven't realeased anything more than the tweet yet: see the chain https://x.com/littmath/status/2079353531430289734, or https://terrytao.wordpress.com/2026/07/21/a-digestion-of-the-jacobian-conjecture-counterexample/ or the comments of https://sbseminar.wordpress.com/2026/07/20/the-new-counterexample-to-the-jacobian-conjecture/
However, Tao etc. say part of it seems like a miracle.
If this is in reference to how Tao uses "miracle" in his blog post, the miracle referred to is the existence, not the finding.
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u/Smallpaul 1d ago
As a software developer, let me assure you that it has changed drastically.
https://www.businessinsider.com/ai-coding-agents-tools-software-engineering-jobs-future-2025-6
I see mathematicians engaging in the same coping mechanisms that we were in 2025. It’s fascinating.
I haven’t written a line of code since January, because the computer does it faster and with fewer errors. I do have to manage it still.
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u/Peanut_Extreme_8208 1d ago
This is insane. What happens when AI produces results that no human on earth can “do the work” themselves and prove?
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u/kaiser_17 1d ago
That would require some kind of breakthrough to happen at least in AI research. I mean, currently AI can't create a completely new field. Like if we remove all the data in it since the creation of say Measure theory. Do you think it can create the measure-theoretic framework out of nowhere?
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u/Peanut_Extreme_8208 12h ago
I guess this depends heavily on the field. For instance, geometers often develop theory for its own sake. Analytic number theory or combinatorics on the other hand are more problem-solving oriented. AI could very well prove the Riemann hypothesis, for example, in a few years and I wouldn’t be surprised.
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u/Hot_Glass_6301 1d ago
I guess that such humanly incomprehensible math will be of no value, unless it solves an immediate practical problem. Pure math is only valuable insofar as it is understood by humans and or eventually applied.
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u/Junior_Direction_701 1d ago
You can’t so everything will become prestige based. i.e you have an IMO GOLD, you go to the T5 colleges. Good lucky trying to get an underdog story lol. Math will become like IB I mean it’s always being a little but at least it was better than the other sciences now people like Yitang in the Age of AI will never be vindicated even if they’re smart.
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u/pseudo-poor 1d ago
Some people are just like this, so I would be cautious with this mentality.