And yes, fun counts. Nobody said this had to be only a hardship.
I'm well aware that if at some point AI is good enough to replace me as a software engineer then I won't have a job. I don't expect a company to continue to pay me simply because I enjoy it if there are cheaper options out there.
Math is no different.
Total compensation includes fun.
Perhaps that won't matter if we enter an era where AI participants are the main participants who matter for discovery-level mathematics. But it would likely be what economists would see as a market failure if only a small oligopoly of AI participants, closely held behind closed doors, is able to fill that intellectual role.
New theories and insights are typically created while working out proofs. If proofs now suddenly fall out of the sky (cause LLMs create them) then that work is not done which means the substrate on which new theories and questions and conjectures used to be grown disappears. It's in that sense that the math community (and thereby society as a whole) will lose something.
It's similar to how software engineering will need to find a solution to train their next generation. Current generations have all been through manual steps of designing things from scratch and writing them by hand. That's what allows your 10x engineers to understand whether what their LLM tools are doing is good and how to massage those tools to do the right thing. A junior engineer who has only ever used LLMs to write code and create architectures does not just not have that experience but also won't acquire it. You can't just say "we don't pay them to have fun and learn, we pay them to produce results". In the short term that is the case, but in the long term you as a company and we as a community will lose out.
I'm not saying don't use AI tooling. I'm saying that this is a hard problem which we yet to have to find solutions and approaches to. As a software community as well as as society in general.
My ego tends to agree, that how can they be ever competent, if they have not endured the same hardships as I had crunching trough problems and getting allmost lost in the details.
But I rather suspect, they will turn out fine. I know LLMs are great for me to learn and I think the young generation will learn what they need to learn to get the job done.
Most people have trouble not peeking at the answers. Look at Stack Exchange's long success.
The increasing pervasiveness of technology in US education has not produced more capable graduates.
But your argument is nonsensical because even if Gauss and von Neumann appeared, they wouldn't go into random fields and just prove things mechanically. They'd have to attend seminars, teach others, collaborate with others, and generally inspire others with their brilliance. It's the precise lack of this activity that makes AI in math so reprehensible.
Your argument encapsulates a contradiction because human mathematicians wouldn't be dropping proofs arbitrarily like AI is doing. They would do something completely different. Even the best of them.
Give it six months and models might be able to explain things better than any human. They can already collaborate perfectly well if you ask them to. e.g. there was a post here a couple months ago where Tao shared his ChatGPT logs[0].
If you're not inspired by the ability to talk to a superintelligent machine, and can't find what you'd want to know, that's a you problem.
Ah, the "six months till AGI" meme, but unironically :)
Also, before citing Terence Tao on LLMs maybe you should read what he has to say about it...
Not sure what your definition of AGI is, but it clearly has superhuman performance on most knowledge work already. Do you think after already having demonstrated that it can solve top problems, that the final frontier it won't be able to cross is explaining its solutions to the experts that were researching those problems, and eventually to e.g. grad student or postdoc level practitioners as a lecture course/set of notes?
I have to assume OpenAI is only prompting to solve problems, presumably they could also prompt to not interesting new theories or paths of research found along the way as well.
Largely I thought that this is what you do once you're established in math (or any field) anyway. You have some ideas, but the details are kind of too tedious for you to work out, so you give it to grad students/postdocs. Senior engineers have some ideas, but the details are tedious to work out, so you give them to junior engineers.
Now, obviously in the meantime, there's the question of how do we train the next generation? Or do we need to train the next generation? And maybe while we work that out the answer becomes more shadowing/apprenticeship instead of farming out easy tasks.
Yours is more likely in my opinion though, mainly because universal high income is completely infeasible and shaky even at the level of definition.
If someone can solve open problems in mathematics then they should do so, isn't it as simple as that?
They should let the public use the models as well, but I guess they have no real moral imperative to do so.
But asking them to stop solving problems is just weird.
It’s not a human focused civilization, which is where the issue comes up.
As an example: A constant issue I am seeing with AI productivity is that the most productive use of AI is when it is paired with more experienced users, while AI also does more work for entry level workers, if not replacing them entirely. It has become a question where will the future buffer of experienced seniors come from.
This is an example of where simply chopping down trees for today, doesn’t make civilization better off tomorrow.
AI is producing more content than ever before, but our ability to understand and verify it is not keeping pace.
We don’t know if these are unsolvable problems at this stage. Society could come up with workarounds and solutions to these issues in several years.
The request to stop, is part of the process by which the issues are debated and solutions found. It doesn’t mean their position is weird or moot.
If there is a prize associated with doing a puzzle, and a machine does it, then what incentive is there to pursue it.
Again, if you are only concerned with the outcome, and you have a preferred answer that you want (in this case "just use AI to advance faster"), then any information that doesn't support that case is useless or misguided at worst.
I am not trying to dissuade you from your preference. I am flagging that there is a set of other factors that influence the behavior of others, how that behavior is critical to the creation of expertise and drive, and thus why others hold different positions.
If another human was likely to get the answer before you would you also discourage them from doing it because they would rob you of the chance to do the thing you're concerned about?
Would it be unethical to dissuade someone else from enjoying the benefits of the process you wish to enjoy ?
Vs
Would it be unethical to stop a machine from data mining all the possible questions you wish to explore/enjoy.
And on another level - I am concerned with a bit more than just the answer. I am concerned with what system is in place to ask more questions and get more answers.
There is nothing in this argument that says that we won’t find some other way to study the subject. Maybe people will become monks and do math as a hobby.
We may end up in a daemon filled world, like 40k, where any hope of understanding the tech around us is impossible. (More impossible that today)
They may very well have learned plenty of things and solved or discovered other puzzles, but if the first puzzle is worth pursuing because the solution is actually useful it seems liked we're better off with the solution than a bunch of failed attempts.
That said, I do question the value of solving many of these types of math problems. I'm no mathematician so I'm assuming I'm wrong here, but on the surface many seem mostly theoretical puzzles with little or no practical use.
I’ve made this point elsewhere but the debate here is between two different philosophical positions. Results vs process.
If all you care about is the results then the process doesn’t matter.
If a person is starving or needs medicine, then a long discussion on process is inhumane. They need results.
If the conversation is about process though, then focusing on the results is missing the point.
I’d say the question for results oriented people is what are the benefits of the process and at what point does it make sense to optimize for results vs process.
When the topic is about careers the question really has to be about results. Even if the results are made by solving different problems discovered along the way towards their original problem, it still has to be about those results.
There is absolutely a question of whether burning these resources is useful when the only outcome is a solution to a potentially obscure math problem, but that is more a question of prompting and goals rather than the use of these tools themselves.
Could you elaborate?
We spend most of our young lives (many of us our entire lives) studying physics, math, etc. that others have solved. (e.g Quantum Mechanics, Relativity, Calculus, etc.)
Biology consists, almost entirely, of studying solved problems in nature.
Aren't AI breakthroughs just more to study?
Terence Tao’s “don’t create the open problem strip miner”
Why is it a problem that the professor is now a robot, and that humans could spend arbitrarily long learning from it and even after 15 years of masters-style advanced graduate lecture courses still have deeper still levels of the topic that the AI could teach them?
And if they never do reach that level of ultra-competence, well, then we found the niche for humans to continue to exist within.
Mathematicians and academics in their ivory towers are forgetting that everything is getting automated. They want to carve out fun problem solving niches that's fine but who's going to fund that? If they want to be funded by the society/civilization their argument can't be leave advanced fun problems for their hobby.
https://proofsandprompts.com/2026/09/10/open-letter-about-th...
>Participation in an event so closely associated with Anthropic and OpenAI could plausibly negatively impact the future reputations of participants.
Given how much power advisors etc have over students in academia, interpret it as you wish.
People go to said crossword group to enjoy the process of solving the puzzles. It doesn't actually matter if they have been solved yet or not, case in point the NY Times puzzles are enjoyed by more than just the first to solve them.
Professional mathematicians are ultimately being paid to solve the problems for a (hopefully) practical reason. Its always excellent when a person enjoys the process of the work they are paid to do, but ultimately they are still paid to do the work. I really hope your argument isn't that we should collectively be funding mathematicians to solve problems simply doe the love of the game.
They are paid for the same reasons the NEA pays artists: out of a sense of obligation to demonstrate elite culture. The track record of practicality of pure math after WWII is essentially 0.
Similarly I wouldn't expect a good argument could be made that AI tools should be prevented from creating art because we want to continue funding artists.
If the goal of said funding is just to let them spend their time doing it then it doesn't matter that AI is doing it as well.
Despite nobody at openAI thinking of themselves as an asshole; despite society urging openAI not to be an asshole; despite the fact that being an asshole is entirely unnecessary even to accomplish whatever objective they are setting out to accomplish; despite everyone at openAI loudly declaring: we are not assholes!
They are still assholes.
If you listen to them, and you don't have to listen very hard to hear it, basically everyone at these labs is telling us that this technology is extremely dangerous and should be slowed down or paused entirely. Yet, they, the only entities with the power to actually do anything about it, are not acting AT ALL as if that's the case. They are all barrelling forward as quickly as possible. RSI, THE number one risk according to these guys, is being adopted at breakneck pace up and down the stack, from designing silicon, to training, to inference.
It's ridiculous and insane and I believe can be accurately summed up as, they are being assholes, because if they are actually right about this we are all gonna die. At the very least, and far more likely, every fun creative expressive human thing that is machine legible will be replaced by a torrent of machine slop. It's not "benefiting humanity." These mathematicians are telling you it's not benefiting humanity. It sucks.
Alignment problem.
That is fine to say when it is not your field. I guarantee you feel different when it is the thing you care about, that gives you joy, that defines your status. Think about how many sheldon-equivalents insist on being called Dr. (non medical)
It is part of what people use to define themselves. Its going to hurt. There may even be a Bulterian Jihad
It is clear to me that any competent person with a little patience can now build software better than what I used to build by hand.
Why do physicians insist on calling themselves Dr. (medical)?
Whole sections of the economy are being upheaved by AI, and there is no reason to make a special case for the mathematicians anymore than for the illustrators, developers, translators, HR, etc.
Of course; but it's very hypocritical to raise these feelings only when mathematicians are affected, whereas all the above professions are just told to adapt to the new way of things.
For sure though, translators don't have the same clout and social status as mathematicians do.
Mathematicians do a terrible job here. They use inconsistent symbols they don't even explain. They often obfuscate the main idea just to make the paper longer. If you are not part of a small club you are not meant to understand it. I think this is a terrible approach and I am eagerly waiting for AI to do a better job!
It just seems that this class of mathematicians is being "disrupted".
The field is changing and a new class of mathematicians will take their place.
This happens all the time in fields as technology disrupts them.
A new class of individuals, with different motivations, take the place of the old guard.
I'm sure the motivations of individuals involved in designing and manufacturing cars changed as Henry Ford introduced the factor line.
But that old crop of humans either adapted or retired.
But, plenty of humans took their place with new motivations and automotive technology continued to progress.
I personally feel math will indeed move faster as a result of these breakthroughs. And the humans that take the place of the old guard will have different passions and motivations than the current group.
Maybe the new group will be productivity motivated rather than motivated by the love of tinkering with a single problem for years.
Sounds like salaries for mathematicians need to start going up if we stop paying them with fun.
https://proofsandprompts.com/2026/09/10/open-letter-about-th...
>Participation in an event so closely associated with Anthropic and OpenAI could plausibly negatively impact the future reputations of participants.
Given how much power advisors etc have over students in academia, interpret it as you wish.
Science isn’t some passive busywork thing where you tie your hands behind your back because it isn’t fair on others to solve all the neat problems - or at least it shouldn’t be.
If your idea of science is leather patches on tweed suits and the quiet ticking of a clock while you do crosswords, then this is an argument in favour of letting the AI do the work so you can focus on your sudoku book in your slippers.