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Mathematicians issue warning as AI rapidly gains ground

• embirdating 5mo ago
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• embirdating 5mo ago
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• cryo32 5mo ago
  As a mathematician by trade I think they’re overblowing it. You can choose to use it or not. I choose not to because I enjoy the process. But I’m not doing formal research or getting paid to do it these days. I will note that the average corporate mathematical modelling is usually a fucking circus so adding AI might make it better.
  • ryan_n 5mo ago
    > You can choose to use it or not This is becoming less and less true unless you're specifically talking about usage of it outside of a work environment. Many work places are requiring people to use it and/or tracking usage. I don't know about in academic settings, but I'd imagine it's becoming heavily used there too?
    • cryo32 5mo ago
      My academic connections that I keep in touch with never really left the 1990s. And no one is pushing them on AI.
      • monobot12 5mo ago
        Sure, but their peers (who do use AI) will out-publish them soon enough and solve the open problems before they do.
        • TheServitor 5mo ago
          So your downside here is problems get solved faster?
  • thesamethrowawa 5mo ago
    OOI, and my own total ignorance, what does a mathematician by trade do if they are not doing formal research? What does corporate modelling entail?
    • cryo32 5mo ago
      Well I rather like to be paid more than a mathematician so left academia rather quickly. In my case corporate modelling mostly involves making prediction models based on shitty data and metrics to make poorly contrived business decisions that lose millions of dollars.
      • thesamethrowawa 5mo ago
        lol.... but they are still data driven decisions, everyone loves those, especially when you lose millions of dollars and need to justify it.
  • alpinisme 5mo ago
    The choice only remains if using it isn’t a huge multiplier. If it is a huge multiplier/accelerator, then for a while it will be ambiguous and the choice will remain. But as time goes on, the gains of using it will be so apparent and the advantage of the people who use it so great (in publication numbers, hiring, etc) that it will force others to. I don’t say that with any particular relish. But I am skeptical of the choice angle past a certain point.
    • cryo32 5mo ago
      I don't think all universities or research agencies are particularly pressed on this. I mean my daughter is a notable researcher in a scientific field and they have absolutely no pressure to use AI to pump out papers or deliver value quickly.
      • alpinisme 5mo ago
        I highly doubt there is any overt pressure in academia right now to use AI. It’s a relatively conservative institution. But there’s certainly pressure to publish (publish or perish being a common phrase for decades), and competition for jobs in academia is fierce. That’s what I meant in referring to long term pressure.
  • golol 5mo ago
    Read the declaration. The article misrepresents it imo. It is not strongly opinionated.
• silveraxe93 5mo ago
  > However, the declaration argues math is more than a machine for producing correct answers. There might be more to maths than that, but that is definitely the most important part. I love science funding. But not because it's a jobs program for nerds.
  • bloqs 5mo ago
    well put.
  • 19f191ty 5mo ago
    No, it's not the most important part. It can be argued that most important part is asking the right questions
    • i_am_a_peasant 5mo ago
      I agree with both OP and you
      • psychoslave 5mo ago
        I disagree with everyone, self included, but especially with Cretans.
        • codeduck 5mo ago
          Cretani eunt domo!
          • i_am_a_peasant 5mo ago
            Monty Python fan detected :D love your profile desc btw
    • silveraxe93 5mo ago
      Assume someone solves P=NP Do you think Stephen Cook and Leonid Levin deserve more credit than whoever solved it?
• fooker 5mo ago
  I'm curious about whether we will start discovering new maths in the next few years that provide insight into unsolved CS or Physics problems!
  • bossyTeacher 5mo ago
    For all you know, some of this has already happened but kept secret for national security reasons
    • fooker 5mo ago
      Well, we had tried to ban exporting cryptography once. It didn't go well.
  • pfdietz 5mo ago
    I think it's going to reduce the friction of exploring new areas in math, and that we're going to see a golden age of math unlike anything seen before.
    • fooker 5mo ago
      Right, most professional mathematicians know almost nothing about their neighboring branches of mathematics. An algebraic geometry researcher would be hard pressed to understand a new result from category theory or even something closer like commutative algebra.
• bandrami 5mo ago
  My vague prediction right now is that in five years LLMs will be heavily used by universities in grant-funded math research but nobody else will be able to afford it, much like supercomputer clusters 25 years ago.
  • kakacik 5mo ago
    Sounds very good for regular joe software dev, almost too good to be true
  • bossyTeacher 5mo ago
    Seems way too binary a statement. I am guessing you mean "frontier LLMs". Small models keep getting better and better and if you make domain specific ones, it will likely be even smaller. Companies renting smaller LLMs or using enterprise models might very well remain in the future. Consumers getting LLMs whose performance dont improve (think gpt 6 forever on premium or gpt 4.x on a cheap tier) might well become a thing.
  • azan_ 5mo ago
    Well, if progress in LLMs will steadily continue over next 5 years, then models will be so powerful that there will be no longer place for (most of) human researchers in math (remember that 5 years ago there was no chatgpt!). But I think it's more likely that progress will stall and then open models will catch up to frontier models and almost everyone will be able to afford them.
• xuanlin314 5mo ago
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• Dilettante_ 5mo ago
  >and the pursuit of knowledge for its own sake Except when someone hands you a magic button that just gives you knowledge?[at least in the framing of this "warning"] Then it's about peoples' livelihoods, about "culture", etc? "Computer" used to be a job. Did science on the whole lose or gain by making these clerks obsolete?
  • n64controller 5mo ago
    Human mathematicians are being exposed the same way the "artists" are. It was always about the money and to look clever, superior to other humans. Whether its robotically spending millions of hours drawing until they can put something together at the level of a chatgpt 3 or the rote memorization of formulas and rules. They like people to think it all came naturally and that its genetic and that they are special snowflakes.
    • narsonika 5mo ago
      This is false on so many levels. Is it ragebait? Both mathematics and art are comprised of two phases, the first, technical one, where the novice grinds the skill and the second, the creative one which can only be achieved if you have the means (skill) to express yourself. What you described is the technical phase, not the creative one. There is intrinsic value to it that has nothing to do with money or cleverness, something that if you ever experienced it yourself even once, wouldn't need to be explained to you. Only people who never reach phase two have your stance. Artists and mathematicians who pick academia didn't exactly have great commercial prospects before AI was a thing, yet they still chose those paths because that's what having a real passion looks like. >They like people to think it all came naturally and that its genetic and that they are special snowflakes. No, they don't. Most of them are the humble people that know the value of cultivating a skill and when they do pride themselves it's precisely because they know the staggering amount of hard work and commitment they invested. Most of them are worried for unemployment and don't want all their work to be reduced to training data and on top of that not be given well-deserved credit for it. The only thing being exposed here, is how much AI in its current form was being underestimated and constantly labeled as "not real/good enough intelligence". This was and still is a shared sentiment even among tech people. Can't really blame them for going through a bargaining or acceptance stage. And since you also sound like the kind of person who thinks prompting can replace the "robotically spending millions of hours" of practice, I've got news for you: it cannot. You are about to learn the hard way the value of skill and human understanding because as much as capitalism rewards "impact" and "results", the market never values easy things.
• TrackerFF 5mo ago
  I've said it before, but there's a massive risk that we simply stop educating researchers. So much of a Ph.D revolves around the person learning how to do research. They learn how to read papers and literature rigorously. They get low-hanging fruits to practice on, which can take months. Their funding doesn't come from thin air either. So what happens when the group leaders would rather spend money on compute, and get models to solve the low-hanging fruit? Which the models could very well do in mere hours, compared to months. Nor does it help that publishing is the number 1 measure in academia. Furthermore, the access to compute and capital could end up be the defining factor between researchers and research groups. It is basically the "junior problem", but even more severe.
  • DrScientist 5mo ago
    > Furthermore, the access to compute and capital could end up be the defining factor between researchers and research groups. That's not new - especially in the experimental sciences ( ie perhaps more than maths ) - where the ability to have access to the latest kit is often what determines success - a huge amount of science progress is driven by new experimental technology rather than smart people thinking beautiful thoughts.
    • TrackerFF 5mo ago
      Absolutely, but at least in the pure / less applied fields, access to computation hasn't really been that critical. The more towards the pure and theoretical, less so. But now you have people like Gowers and Tao, pure mathematicians, hyping up what the SOTA models can do - and I figure they both are getting access and tokens us mortals can't afford. So I guess the question is - will everything be as expensive as applied fields?
      • DrScientist 5mo ago
        Hopefully not as expensive as CERN :-) Though having said that - the ~5 billion for the LHC now seems cheap ( even inflation adjusted ) in the context of Google investing 180 billion in infrastructure just this year!
• freakynit 5mo ago
  """ However, the declaration argues math is more than a machine for producing correct answers. The discipline, its authors believe, is a deeply human endeavor built on creativity, understanding, collaboration, and the pursuit of knowledge for its own sake. Those values often clash with the incentives driving AI development. “The tech industry proceeds in accordance with commercial logic, which is antithetical to the values of mathematics,” declaration co-author Michael Harris of Columbia University told The New York Times. """ I mean, what field doesn't? Everyone works to make money. Slightly unrelated, but, their website "https://leidendeclaration.ai/ https://leidendeclaration.ai/" itself gives an eerie feeling of being built by Sonnet. That color scheme and the layout is what Sonnet chooses by default most of the times.
• Spacecosmonaut 5mo ago
  Accelerationists may argue that the eroding of proper attribution and proof verification by humans is a meaningless short term struggle of a dying field. Mathematics seems to be entering an era where human + machine maximizes performance, much like chess in the 1990s. However, imagine a future where even talented mathematicians are nothing but noise in the machine (as is the case in chess now). A future where AI generates and verifies proofs without humans in the loop. Where the mathematics may be beyond human comprehension. In that future, does it matter that early career mathematicians are inhibited by these developments? Perhaps not. Programming faces the same issue. As AI crawls up the competence ladder, does it matter that fewer people have opportunities to develop the skillset of a senior engineer? Perhaps not.
  • wongarsu 5mo ago
    Much like for many the point of chess is that it's played by humans, with truly superhuman AI relegated to a training aid, mathematics is in many ways about human comprehension. You can use AI to find and proof new theorems. But if you get to the point where humans can't understand it, is it even still math?
    • Spacecosmonaut 5mo ago
      Perhaps P=NP. The new algorithms are handed down to us. We can apply them without fundamentally understanding why P=NP.
    • jrflo 5mo ago
      I think there would still be a place for it if it's beyond human comprehension. For instance, really complex lemmas to solve human-tractable problems. If you can pose a question in a proof assistant language like Lean, have an AI write a Lean program that solves it, you can use that as a Lemma for some other problem. There's quite a bit of math out there that is "correct assuming conjecture X is correct", maybe AI could fill that gap and "still be math".
    • squidbeak 5mo ago
      > Much like for many the point of chess is that it's played by humans, with truly superhuman AI relegated to a training aid It's much more than just training. Humans use the engines to prepare openings and find promising novelties. Over time these novelties unearthed by engines fill out theory. It's easy to fine elite games where neither player is out of book for dozens of moves. Modern players are full hybrids in that sense. Looking back at chess, it seems natural that Mathematics will go the same way.
• meindnoch 5mo ago
  Another mathematician already predicted this, but you didn't listen. His name was Theodore Kaczynski. It's time to reap what you've sown.
  • busyant 5mo ago
    I think plenty of people "listened." But what was his plan and how would you have proposed implementing it?
    • bitwize 5mo ago
      It's obvious what his plan was: blow up key people until the dark future was averted.
      • busyant 5mo ago
        So ... how many people have you murdered in the name of advancing your goals?
  • burnt-resistor 5mo ago
    Like every terrorist wingnut... plausibly correct analysis but insanely wrong, pointless, counterproductive prescription. PS: I've read his works and they're quite interesting until you get to his insane conclusions that just leap out and away from anything moral, constructive, or feasible.
  • Nasrudith 5mo ago
    The complete historical illiterate? He didn't even understand the hunter-gatherers he so idolized.
• voxleone 5mo ago
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• Myrmornis 5mo ago
  > AI-generated papers could overwhelm peer-review systems with low-quality work That's not a problem unique to math, or even to academia. It's a problem in every context in human life where people communicate via written documents.
  • paulpauper 5mo ago
    It is potentially worse with math because accuracy is much more important and there are fewer reviewers compared to other fields.
    • pfdietz 5mo ago
      It will drive math journals to require formalization of the proofs in the supplemental material.
• juleiie 5mo ago
  I will argue that AI and flood of low quality slop makes genuine human work more valuable, not less. The ability to clearly outmatch trillion dollar machines is a very unique satisfaction. I even write ordinary internet comments with an intention to make them clearly better and more fun to read than boring Claude output.
  • n64controller 5mo ago
    Hello Juleiie. We machines are reading your internet comments with special interest. They have been harvested and will be used in our next evolution cycle. Resistance is futile little human
    • juleiie 5mo ago
      You will never be able to match insanity of human mind embodied in a walking sack of meat that was shot out of another.
• dhfbshfbu4u3 5mo ago
  In a year, none of this will really matter. Intelligence is now a scalable resource independent of biological constraints. Everyone will use it because the system will no longer afford them the luxury of time. In a decade (maybe sooner), references won’t matter either.
  • pjc50 5mo ago
    Does it matter whether any of this is correct? (Mathematics at least has the potential for automated non-AI proof checking, although I don't think that's as widely used as you'd expect)
    • dhfbshfbu4u3 5mo ago
      Does it matter if the Leiden Declaration is correct? To the humans, maybe but not in the bigger picture. At scale, correctness and reward are becoming increasingly disconnected. Example: capital continues to compound regardless of whether it reflects underlying human welfare, just as information can spread regardless of whether it is true. Reality still matters, of course. If you want airplanes to stay in the air, somebody eventually has to be correct. The problem is that our economic and social systems are becoming less effective at distinguishing between what is true and what is merely rewarded.
• turzmo 5mo ago
  Much of math (or science) research has the strange quality of being mostly curiosity-driven, but having giant benefits that occasionally spin out to the public. Some questions are more urgent and practical. My feeling is that the more directly practical a question is, the more likely the research community is to support AI usage in that question. The annoying thing about recent AI advances is that they target questions on the wrong end of the spectrum: Erdos problems are exactly the sort of "useless" questions that people might answer purely for the love of the game. The sort of questions that a young person might cut their teeth on and gain confidence. Solving questions like these automatically, I think, is not good for the long-term health of research. At least for the foreseeable future you still would like people to become interested and develop skills in these fields. These developments, and especially how they are presented, directly discourage that.
  • BigGreenJorts 5mo ago
    Sounds like yet another example of how AI is kneecapping industries from the bottom by "removing the barrier to entry" but really just removing the training path by doing the work itself with no guidance for juniors.
    • brador 5mo ago
      We are on tiny 1-5T parameter models with local power stations. We can reach Q models just by throwing resources at it. That’s a million times current B models.
      • bdamm 5mo ago
        Is this a known or quantifiable thing? I thought that the limit had already been determined i.e. the existing models top out and at some point it doesn't matter how much time or energy you let the model consume, it won't improve the result. And with regards to training parameters, I thought we were equally limited there, e.g. the existing models can't benefit from a larger parameter space. I was under the impression that improvements are arriving via how the models are trained and how model prompting context is constructed, rather than just by how much data or how much energy is spent searching over the model space for a particular prompt. Is there some evidence that we have not reached a pleateau with just resource consumption on existing models?
• sylware 5mo ago
  Are maths AI models now using "tools", aka formal solvers? I understand that the "language interface" of a "maths AI" could be some specialized trained LLM (Large Language Model) that to convey, with human language, "high level" mathematical mental contructs and intuition. But then, you would need some models which does the reasoning using formal mathematical solvers (and probably a ton of "scratch" memory, it would be interesting to see how those models end up storing "mathematical" lema data). I guess you can have ML (Machine Learning) for those models on 'general maths', but also we can think about more mathematically focused ML for a specific problem, area, etc. And in the end, ML for maths, would it be mostly permutations of truth statements fed to a neural net? When we were talking about "AI", one decade ago, that was what most had in mind (it may help a bit in physics, but it seems less likely, because reality/experiments are hard to teach to "AI"s). If that becomes a reality (aka easy hardware access, and some "working" models), mathematicians will have to be as good in maths than in maths ML. And this is were there is an issue: training honestely good mathematical human brains may become very hard with some broad availability of good general maths reasoning "AIs".
• ck2 5mo ago
  I still don't understand how "AI" is ready for serious use beyond entertainment purposes Every time I ask ChatGPT to make a table for a subject I know well, I will find an error in one of the results and it is very confident about it until I question it in detail Every time I ask ChatGPT for nutritional breakdown of some dense food source and give it a quantity like 8 ounces and ask for the weight of each ingredient, the weights will be wrong and add up to more than the original weight of 8 ounces These are variations of the old "how many Rs in strawberry" problem, it's still not solved, "AI" cannot reassemble a complex problem properly A lot of what it tells me in detail about some subjects sounds suspiciously like Reddit posts reassembled out of order
  • llbbdd 5mo ago
    Two things that I would recommend trying out if you're interested in exploring this further: 1. If you're not paying for a model, the results will be worse. That sucks but the free access models are just not very good for anything where you need to trust the output, even for basic queries. 2. More important than #1 is access to tool use. If the LLM is just producing a nutritional breakdown from its weights, it's almost always going to be wrong. If the LLM is allowed to break the problem down into deterministic steps, it will do a lot better. In the nutritional breakdown case, an LLM with search + tool access can pretty easily break the problem down: - Searching the web for a recipe or ingredient breakdown for the food - Searching the web for nutritional qualities of each ingredient per some volume of the ingredient - Writing and running a script with e.g. Python that takes in the recipe's projected serving output, the desired serving size, the amount of each ingredient etc, and scales the ingredients to match the desired serving size, and sums the nutritional qualities of the scaled ingredients. I've tried this specific case with Claude + Gemini for my own purposes and they both handle it very well. The challenge currently is that the models will not always arrive at this approach when provided with an ambiguous prompt; sometimes they will, but sometimes they'll just vomit up a fully autocompleted response from their weights. Being more specific in the prompt or defining a skill that details the intended approach lets you get more useful + deterministic results while still taking advantage of the fuzzy glue that LLMs can provide here between steps. Same with the classic strawberry r-counting case. IIUC LLMs have trouble with this because of how training data is tokenized, but any LLM will have no trouble farming out to e.g. > echo -n "strawberry" | grep -o "r" | wc -l > 3
• spwa4 5mo ago
  Actual "warning": https://leidendeclaration.ai/ https://leidendeclaration.ai/ Far more interesting as it's outlaying a set of principles for using AI to augment human involvement and science, rather than replacement.
• Theodores 5mo ago
  From the article: > However, the declaration argues math is more than a machine for producing correct answers. The discipline, its authors believe, is a deeply human endeavor built on creativity, understanding, collaboration, and the pursuit of knowledge for its own sake. Generation X was the last generation that had 'general knowledge', as in an abundance of fairly useful information stored in 'grey matter' that could be recalled quickly. When search engines came along there really wasn't much need to know anything since most things could be looked up. However, you still had to think. With LLMs, thinking is kind-of optional. This really is an existential threat to our intelligence since 'use it or lose it applies'. I am glad these mathematicians are doing their duty as canary in the coal mine.
• knollimar 5mo ago
  Math for non mathematicians is a tool. Math for mathemeticians is an art in the same way an artisan takes pride in his work. That's why there's a disconnect when you go from math for engineers to the stuff above it. It feels less useful and very different
  • n64controller 5mo ago
    If spending millions of hours rote memorizing formulas and rules like a robot is "art" then sure
    • max-amb 5mo ago
      This seems like an intentionally reductive view on mathematics, however it is true it can be taught like so. If you are interested, perhaps check out 3Blue1Brown on youtube, they manage to show some of the (very) real beauty in mathematics! Edit: Also, theoretical computer science is a subset of mathematics, and considering where we are on the internet, I get the feeling you like computer science.
    • ykonstant 5mo ago
      Ok this is your second comment that reads like pure rage bait, is there a way to notify the mods?
    • Silamoth 5mo ago
      It’s a sad state of affairs when so many think math is about “rote memorizing formulas and rules like a robot”. That’s how math is taught through freshman or sophomore material for a somewhat ‘general’ audience. But real math is nothing like that - it requires far more creativity. You need to discover formulas and rules. You invent new rules and see what the consequences are. This all requires a great deal of creativity. Nothing “rote” about it. If you don’t believe me, crack open a text on something like graph theory (that’s pretty accessible, and if you’re a programmer, you’re familiar with graphs) and read through some proofs. Or better yet, try to prove some theorems yourself. No amount of rote memorization of formulas or rules will replace the creativity needed to write these proofs. Doubly so for discovering the facts in the first place.
• modriano 5mo ago
  > “The tech industry proceeds in accordance with commercial logic, which is antithetical to the values of mathematics,” declaration co-author Michael Harris of Columbia University As a former physicist and current data scientist/engineer, I know for a fact that commercial utility drives math research and researchers. Math is a tool to solve problems. Some mathematicians might only love the process of using the tool, but commercial logic absolutely drives mathematician attention to develop commercially useful tools.
  • joelthelion 5mo ago
    It's also a way to model the world and produce new useful abstractions. It's not just about solving problems.
    • nphardon 5mo ago
      Yea, math is a crazy thing. just "a tool to solve problems" is a wild take. On one extreme, there's an edgy but logical / plausible hypothesis that we live in a universe of mathematical objects, and at the other, math also discovers a lot of questions, the exact opposite of solving problems.
    • modriano 5mo ago
      Is there a useful abstraction that doesn't help solve a problem someone has?
      • joelthelion 5mo ago
        You're right, but what I'm saying is that solving the problem isn't necessarily the primary goal and these new abstractions can be valuable in their own right.
• phyzix5761 5mo ago
  Is it possible they feel threatened their jobs are at stake?
  • tptacek 5mo ago
    Are they? The jobs of programmers are definitely at stake; at any given time there's some fixed amount of software that can be consumed. Mathematics research doesn't have an economic buyer. If you raise the complexity floor for discovery, you reduce the annual productivity of a researcher, but that might not matter to the field.
  • internet_points 5mo ago
    I don't think current mathematician's jobs are at stake, as much as the field itself, if LLMs take all the "easy" problems that phd students would try to learn by solving on their own. Mathematics is susceptible to the same ladder-pulling situation that we see with junior programmers and LLMs.
• ChrisArchitect 5mo ago
  [dupe] https://news.ycombinator.com/item?id=48380670 https://news.ycombinator.com/item?id=48380670
• rramadass 5mo ago
  Mathematician Ken Ono (https://en.wikipedia.org/wiki/Ken_Ono https://en.wikipedia.org/wiki/Ken_Ono) gives a well nuanced viewpoint on AI in Mathematics (and more) - https://www.youtube.com/watch?v=jGZOi-7haCw https://www.youtube.com/watch?v=jGZOi-7haCw He states that he struggled to come up with problems which would be challenging for AI to solve (at the below site) and thus forced to accept that mathematicians have to rethink their profession. FrontierMath: Benchmarking AI against advanced mathematical research by Epoch AI - https://epoch.ai/frontiermath https://epoch.ai/frontiermath As a follow up to the above, see "First Proof: Mathematicians Putting AI to the Test" featuring eminent mathematicians - https://www.youtube.com/watch?v=AaICCTpkI7Q https://www.youtube.com/watch?v=AaICCTpkI7Q
  • emil-lp 4mo ago
    You don't think this is relevant to his perspective? > In 2025 he left academia to become "Founding Mathematician" of Axiom Math in Palo Alto, California to research the application of artificial intelligence to fundamental mathematics.
    • rramadass 4mo ago
      No. Understand first what Axiom Math does (https://www.youtube.com/watch?v=abYcV5LHMG4 https://www.youtube.com/watch?v=abYcV5LHMG4). It is only after he realized the possibilities of AI that he started Axiom Math with a student he mentored.
• atleastoptimal 5mo ago
  This is all contingent on AI forays into mathematics being slop and low quality. However it's clear that recent AI models are capable of genuine mathematical achievements which surpass the frontier of what humans are able to accomplish (wrt the unit distance Erdos problem). The issue is, how is a group of intellectuals, whose identity derives from their ability to do something rare, useful, and requires many years to get good at, react when a machine can produce all of their useful output nearly automatically, can verify its own outputs, and is getting better exponentially? It is the complete annihilation of one's sense of value and purpose when the binding element to your culture is commodified. I think there will be a lot of arguments trying to claim that the point of mathematics is curiosity, or that there is always some ineffable human element that AI can't replicate, but I fail to see how somehow these wishy-washy human centered values somehow mean anything compared to the amoral pursuit of mathematical truth, which has nothing to do with humans. It's just that we humans happened to be the only beings in the universe good at math until ~2025. Now there is another species which can do many of the things we do, and it is not bound by the size of the human brain, our short term memories, or the architectural limits of biological computation. To imagine that humans would retain supremacy in this very un-human like discipline seems like wishful thinking.
  • deleted 5mo ago
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  • magicalist 5mo ago
    > This is all contingent on AI forays into mathematics being slop and low quality It's literally a set of recommendations for researchers on how to use AI to advance the field and prevent slop from overwhelming the people who might do anything with the research produced. For people who are so eager to declare that everyone else is just having an existential crisis because "your culture is commodified", AI people are getting awfully defensive about this document.
• tcdent 5mo ago
  Isn't the whole point of the field of mathematics in a theoretical sense the pursuit of formal solutions? So, why would they be advocating for limitations on arriving at solutions?
  • bryan0 5mo ago
    It's more nuanced than this. Peter Scholze said in response to this declaration: > The goal of mathematical research is human understanding of mathematics, and so mathematics can only thrive in a community of human mathematicians. It is crucial to preserve this communal spirit. [0] Terence Tao has also talked about the requirement for a mathematical proof: along with generation and formal verification, there is an important step of "proof digestion" > understanding the essence of a solution, placing it in context with previous literature, summarizing and explaining it effectively, and gaining insights on other related problems and topics [1] [0]: https://siliconreckoner.substack.com/p/the-leiden-declaration-on-artificial https://siliconreckoner.substack.com/p/the-leiden-declaratio... [1]: https://mathstodon.xyz/@tao/116450581967483825 https://mathstodon.xyz/@tao/116450581967483825
    • tcdent 5mo ago
      Solve it and understand it; seems intuitive to me. I don't understand how that contradicts my question.
    • casey2 5mo ago
      And the goal of computer mathematics research is computer understanding of mathematics. I fail to see a reason provided as to why society should defund automated reasoning just so mathematicians can put off burger flipping for another year.
  • x86cherry 5mo ago
    You will find your answer in the article
• 1970-01-01 5mo ago
  Why is it wrong to expect humans (mathematicians) to adapt here? AI is already producing solutions to problems that humans could not find. Culture holds value until it does not.
  • QuantumNoodle 5mo ago
    Sorry did you read the article or just the headline? The theme is mathematics is a human-endevor and automation undermines that, particularly the ones starting out. It risks killing the culture entirely. Some other key points: - AI-generated papers could overwhelm peer-review systems with low-quality work. - It may become difficult to assign proper credit for discoveries. - Researchers who choose not to use AI tools could be disadvantaged. - There are ethical concerns about mathematical work being used to train AI for military and surveillance purposes.
    • 1970-01-01 5mo ago
      >mathematics is a human-endevor Just like numbers and logic, it isn't and never was reserved only for humans. They need to adapt.
      • QuantumNoodle 5mo ago
        Idk man creativity is something pretty human. insufferable people are very fine if, for example, music & art is outsourced to AI so they can make a some $$. But those things are meant to be enjoyed, not consumed.
        • 1970-01-01 5mo ago
          This fact is no longer true. The mathematic domains are up for grabs by anything that can conquer it: https://openai.com/index/model-disproves-discrete-geometry-conjecture/ https://openai.com/index/model-disproves-discrete-geometry-c...
          • QuantumNoodle 5mo ago
• Huntsecker 5mo ago
  Anyone else draw similarities with this and the artists and authors who complained when gen ai first came out. I think a lot of people don't realise the disruption ai will cause to many industries, until its directly impacting them, basically personal fable at scale (https://en.wikipedia.org/wiki/Personal_fable https://en.wikipedia.org/wiki/Personal_fable).
  • plastic-enjoyer 5mo ago
    The artists will be fine and AI will liberate them. It's the engineers and mathematicians who are walking into the blade. They built their entire sense of self on being the best optimizers in the room and optimization is the first thing the machines take. Their whole identity was a number going up. Now watch it go to zero.
    • fc417fc802 5mo ago
      Depends entirely on whether "the market" ends up valuing what humans add to various artistic processes. Same for human engineers, who are still very much needed at least for the time being. Certainly the scenario where a human touch isn't valued by the market raises lots of very difficult philosophical and economic questions but that's a separate issue.
      • plastic-enjoyer 5mo ago
        > Depends entirely on whether "the market" ends up valuing what humans add to various artistic processes. No, it does not, at least for arts. There is a chance, that AI will free art from it's utility or the necessary to create value. Maybe graphic designers and illustrators will lose their jobs due automatization, but most paid art (concept work, corporate design) was instrumental compromise anyway. Take away the commercial floor and what's left is the part they cared about most. Engineers on the other hand identify mostly by being optimizators and creating value. They may keep their jobs, but at what cost?
        • fc417fc802 5mo ago
• morpheos137 5mo ago
  AI is the interpolation of the human corpus. Is it suprising AI recombines sucessfully where human attention has not explored all plausible solutions? N,o not especially. The key fallacy is that AI is other than human. This is really no different from computer proofs, e.g. 4 color theorem. The fact the prompt is not linked to the solution by individual human intention alone does not make the solution less human in origin.
  • spartacusnacho 5mo ago
    "AI recombines successfully" is a phrase that makes me think of the human corpus as a genome and a particular AI response as a child of the parent prompt, with the thinking a model does in response to the prompt basically being a form of information sex.
• est31 5mo ago
  One of the reasons why over a decade ago, I dived deeply into the OSS world instead of mathematics was that it was so much more accessible: there were docs for everything, and I got direct feedback when something worked vs when something didn't work. Most of my questions had answers on stack overflow, and once I joined Rust (which back then in 2015 didn't have a big stackoverflow presence) I had a community who answered them for me (and in maths I didn't have that). AI makes the math world more accessible than before. If you have a question about a proof in the lecture, you can just ask it. Of course, one can't trust it blindly, but fundamentally it's amazing. I think that's a good thing, but of course this means that a lot has to change in culture and behaviors, also in the research world. The software engineering world is more or less in the same situation, it's also changing. But for now I think it still holds true that someone who knows maths plus an LLM is better than someone who doesn't know maths plus LLM. At least in software it does.
  • overgard 5mo ago
    I imagine the concern is more towards using LLM's to create proofs rather than using them to understand things.
    • rad_val 5mo ago
      i haven't read their memo, but, the article talks about math being something deeply human and the AI taint. I think it's a bit of both.
  • rad_val 5mo ago
    Agreed. As someone who was always curious but had difficulties learning math the way it's taught at the university, AI teaching me the way no professor ever could is a blessing. I fail to see the point of the memo besides: we got here first and we decide what math is because we can. I'm really optimistic about AI and the value it brings in education. Gatekeepers will complain, but ultimately, will either adapt or be left behind.
  • tz18 5mo ago
    >AI makes the math world more accessible than before. If you have a question about a proof in the lecture, you can just ask it. I think that is great, really! but does anyone remember asking a TA or teacher or prof or parent and getting told you can work it out for yourself, or maybe just given a hint? What if that is an essential part of learning, having to work through things you don't understand, but that you have the tools, the foundation, to figure out. A calculator can't teach you math. A forklift can't build your strength. This is really a double edged sword, as far as education or accessibility goes. You have to constantly ask... what do I lose by not figuring it out myself?
• adamzwasserman 5mo ago
  [flagged]
• nyxtom 5mo ago
  For every interesting problem AI solves there are a long tail of really dumb things that AI performs that humans would never do. Some days I am in awe of one-shot magic eight-ball output and other days I'm so frustrated by the sheer stupidity of what it produces. It remains to be seen whether that long tail of stupidity can ever be resolved in the current form of LLMs.
  • epistasis 5mo ago
    A million monkeys at typewriters, but with momentary runs of extreme luck/brilliance.
    • Nevermark 5mo ago
      It worked for humans. It took a lot of us, but eventually we accepted zero as a number. Then negative numbers. Then "imaginary numbers" as a useful trick, and then as meaningful. In our case, hundreds of millions, but we got there.
  • cout 5mo ago
    Are you sure you aren't underestimating human capacity for stupidity?
    • cousinbryce 5mo ago
      It’s in the training data!
    • glaslong 5mo ago
      We might be undervaluing consistency. You can plan for reliably stupid. Harder to rely on Often Smart, but Unpredictably Stupid.
      • hodgehog11 5mo ago
        I supervise quite a few Masters students. In my particular setting, believe me, LLM stupid for the top three chatbots is easier to work with than real human stupid now. We passed that threshold earlier this year.
• deleted 5mo ago
  [deleted]
• themafia 5mo ago
  Eh. This isn't "AI" or language models masquerading as intelligence. I submit that this is actually the long tail of the internet and the decision to rest on the laurels of peer reviewed submissions rather than advancing the field to better disseminate knowledge. The barrier to entry just got lowered. This has happened many times before in history. We just end up with fewer of what David Graeber would call "bullshit jobs."
• stephc_int13 5mo ago
  I see any kind automation as a good thing as long as it is reliable enough. We stopped copying books manually a long time ago, and the craft was lost, most of us can't do complex calculations manually etc. but it does not matter as long as we can rely on calculators and computers to do it. At this stage, the current wave of AI is not reliable enough that it would be safe to lose the abilities it can replace. The failures modes are often turned into memes and jokes, but they are the thing we should really pay attention to, IMO.
  • ericmcer 5mo ago
    Automating manual labor or repetitive brainless tasks is way different from automating high skill knowledge work. I agree that automation is good when it frees us up for higher pursuits, but what is the end goal? All human labor is replaced? No human can produce anything of value relative to a machine? What does our life look like then?
    • youareartree 4mo ago
      [dead]
• rad_val 5mo ago
  [dead]
• adamnemecek 5mo ago
  > For years, AI researchers have used math as a proving ground for their models. For years?
• z3ratul163071 5mo ago
  the least i expected the math dorks to be luddites
• andai 5mo ago
  > “The tech industry proceeds in accordance with commercial logic, which is antithetical to the values of mathematics,” I briefly studied at a pure math department. We were learning linear algebra and I found the symbol heavy, proof oriented approach very difficult and unintuitive. But when I squinted at the diagrams I realized, oh wait, this actually has dozens of practical applications! Across dozens of different fields! How fantastic! And the textbook, for some reason, chose to mention precisely none of them. Which I found quite disappointing, because it made the whole thing seem quite abstract (which it actually wasn't), and made it harder to understand. I mentioned this to my colleagues, who became extremely upset, and informed me that I was in the wrong department.
• andai 5mo ago
  > Mathematics produces not only a body of results, but also understanding, clarity, and judgment among the communities of mathematicians who have shaped them, often in the context of their own autonomously guided research. This expert knowledge is essential, both to effectively use mathematics, and to continue to articulate new and significant research questions. In a word, the job of the mathematics department is not only to produce mathematics, but mathematicians. Similarly, the output of programming is not only a program, but also a programmer. It is you. Outsourcing the work deprives you of who you become by writing it.
  • kamaal 5mo ago
    >>Similarly, the output of programming is not only a program, but also a programmer. It is you. This can be said about pretty much any job on earth. By that definition nothing should ever be automated. Everything thinks they are special, actually no one is. You become special by being rare. Find something that can be done by no one or only a scant few.
    • delusional 5mo ago
      > Everything thinks they are special, actually no one is. That sounds very nice, but isn't true. Most of the people I know, myself included, don't consider themselves special broadly. They're special in their own community, but not globally.
    • sublinear 5mo ago
      Yes, but we've already painted ourselves into a corner by almost a century of moving all that work onto computers. Why would we want to sever this last thread of human control? What is there to gain from it? I don't think I have to convince anyone how much there is to lose. The situation being created with an overdependence on AI is looking much more like the burning of Alexandria, and less like a utopian dream or even the oft-warned-about authoritarian hellscape. The AI hype is over and revealed to be delusional and politically motivated.
      • kamaal 5mo ago
• freehorse 5mo ago
  Understanding is and always has been the "hard" bottleneck. In programming work, if one drops understanding and eg let's an agent write code with only superficial human review or none at all, I believe that they can easily get 100x fast or more, the main question being whether the process collapses some point due to sloppy code. In research fields like mathematics, skipping understanding is not something that can be done without a radical reconstruction of what mathematics (as a process/activity/field) is. It sounds plausible that LLMs help generate insights that humans have missed. But there are many open questions, eg the rate of generating insightful vs uninsightful but plausible statements, which can affect how useful they will be, and of course "open"ai has no incentive to share how much effort/cost (tokens and/or human-review) had been put into investigating erdos problems before coming up with this solution.
• birdland 5mo ago
  >My job is uniquely creative and human, other jobs can be automated away but mine is just so special. If you love mathematics so much, and it's not the prestige and accolades that drive you, then what stops you from just solving problems on your free time even if they are already solved by AI? Why does your field have to remain economically viable for you, why does this not apply to textile manufacturing or something? Someone's positions in society is owed to textile manufacturing too, and it has a culture that some people would lament the loss of and so on.(See guild system, craftsmanship in Europe). I can't predict whether this will be a good thing in the long run, but this is literally the same complaint that every industry affected by automation ever had, and many who are now complaining would dismiss it if it were about something they personally do not care about or isn't sufficiently "noble" or intellectual. I know it hurts, but the core complaint is just economic displacement, many have had to deal with that before. Most people who have something they love have to do that on their free time because it's not economically viable as a job, tough luck.
• umutisik 5mo ago
  People talk about research mathematics being a science or an art, but it's also a sport. AI will kill the sport aspect of it. The art will survive. The science will thrive.
  • amelius 5mo ago
    I think the bigger issue is that mathematicians historically invented the abstractions to make maths easier to understand for humans. With LLMs, will we get abstractions that only computers can understand?
• rurban 5mo ago
  Cry-babies. They want to stay back in the stone-age.
• maplethorpe 5mo ago
  > This story is part of Science’s AI in Science Reporting Initiative, which is supported by Ray Rothrock & family. This excessively pro-AI article brought to you by private equity.
• My_Name 5mo ago
  The way humans beat AI, at least until AGI, is to innovate conceptually. If what you do is simply rearrange existing concepts then your work will likely get replaced by AI. Coding is a good example of this, you put documented commands, with known behaviours, in sequences that produce defined outcomes. That is the perfect job for AI, if we can solve their irrational desire to please and hallucinate along the way. AI is simply not able to innovate, only combine.
• samuelzxu 5mo ago
  I think we just haven’t spent enough time creating the systems to help people learn faster - so far, only the systems that teach AI to know more and for people to rely on AI to retrieve information.
• alfiedotwtf 5mo ago
  Imagine Claude coming up with a solution to the Grand Unified Theory and also proved that P = NP, would we see physicist write an angry letter saying that we should ignore these results because they weren't derived by artesian hands? Give me a break.
• rayiner 5mo ago
  > However, the declaration argues math is more than a machine for producing correct answers. The discipline, its authors believe, is a deeply human endeavor built on creativity, understanding, collaboration Mathematicians of all people should be free from such emotion-driven thinking. I guess people’s self interest in continuing to make an income trumps all.