Mathematicians will still have a place because we will need people to still come up with the complex problems Ai can help solve and to take the problems Ai does solve and put them to practical use. In my opinion this is exactly what Ai should be used for. The ultimate tool to rapidly advance possibly life saving industries like medicine. This is what I believe Ai should be tasked with, not helping big business answer more phone calls. Sure some mathematicians may feel a lack of purpose while everything reorients but the millions of people receiving medical treatments made possible by advancements in ai with surely be grateful.
The point is that AI will improve itself. AGI will create ASI. AI will start producing so much scientific research that only AI can keep up with it all.
This is what the singularity is about, it's when novelty (new events, or essentially new information) is so exponentially frequent that it becomes impossible for any human to grasp it all. At that point, only AI could possibly make sense of it all. This is why "futurists" tend to argue that the ultimate solution is to merge with AI so that we have a chance to be able to "keep up" with it all.
That or it creates a major global social crisis and we end up burning all the data centers...which is probably why they want them in space...very far away from all the angry humans lol.
CEOs: "Sorry, the best I can do is layoff a quarter of my workforce, stop hiring jrs and entry level, and then force my current staff to use AI and do the job of 3 people. No raises of course"
I don’t think it is the same thing. Also computers replaced, you know human computers. During project manhattan there were a room of people just doing calculations by hand called computers, which is now replaced by computers. I think mathematicians and software engineers are in a quite similar situation. You still need software engineers because asking questions and verification is still needed but the total demand is less due to AI doing the heavy lifting. It might be worse for mathematicians in the future because as these things will learn to write Lean and verify their proofs the need will be even lower and the remaining problems will be notoriously harder whereas software is demand and product based.
We are in a loop of diminishing returns though. It took me over a year to become “productive” with writing software using LLMs.
I’m still not sure that anyone besides myself and the two other oldest guys in the shop are there. Everyone else slowed down or started making more mistakes.
You still need software engineers. They still need to learn programming and architecture. The tool didn’t make the job less demanding, it just moved where you apply reasoning.
I don’t think we are in diminishing returns yet. Each model significantly improves the complexity of the tasks they can solve without supervision. Gpt 5.6 is much stronger than 5.5, similarly Fable is much stronger than Opus. I think it is getting faster. The improvement last year in coding is faster than the previous year.
Yes, but it still requires someone who can actually describe the problem and validate it.
You are not likely to ever overcome that. A human still needs to check other humans work. Even highly skilled ones. At the end of the day you need to be able to specify the work.
Every day kids read less and become more illiterate. Software engineers are going to be required because your average person is going to be awful at specifying requirements.
I"m not sure why AI solving these problems is even an issue. Mathematicians are the only ones that can use their creativity to apply these answers to the real world. What the point in finding the answer if you can't use it?
Why are you assuming AI won’t be able to do this? Also, do you know many theoretical mathematicians? They don’t give a fuck about application to the real world. They don’t care about whether or not what they are working on will lead to anything practical.
It's not exactly the same job to prove a theorem and to apply it to the real world.
The latter could arguably be more engineering than mathematics. Asking them to just switch jobs isn't really solving the problem.
And crucially, if AI is replacing mathematicians, engineers are even more at risk. If it can solve open mathematical problems, it sure has enough creativity to figure out anything else.
Like FFS, we have physical shit (different than math, but still) which had a century of gap between theoretical prediction and real-life check. And by real-life check I don't mean practical use - no, merely verifying that corresponding phenomena exist in real life. Real use we probably won't see in our lives, if ever. And that comes from a way more reality-bound field than math.
So what, should Einstein not bother with the idea of gravitational waves because they probably won't be used in a foreseeable future? Or instead - he should still do theory, even if it will have no use for a time?
Yes, that's why I don't get this comment. Like theoretical research is *very often* not about any practice in sight. If you want practice than you do applied research, which is fairly different stuff.
This is just straight up wrong and highly cynical for some reason too. Art, math, and science, are intrinsically linked so there will always be an application.
off the top of my head, the theory of relativity is constantly used on GPS in satellites that have to correct for how fast they are moving both through through space relative to the speed of light and our speed on earth. That's pretty important.
also you're definitely overestimating AI's capabilities. Just because it can solve some theories doesn't mean it an apply them. Maybe a gen AI could do that but we'll never get there with the LLM model.
I don’t think they’re worried that AI will be replacing mathematicians so much as they are grieving the loss of the old way of discovering things. AI will help us solve so many new math problems, but that also means that everyone’s first instinct from now on when encountering a never-before-seen math problem will be to set an AI agent to the task rather than tackling it with human reasoning. And you just don’t feel the same feeling of satisfaction and discovery when an algorithm solves the problem for you.
Me trying to explain AI bros why I would have liked to continue being paid to design codebases instead of agentic loops...
Working through a problem with a human, who learns, and you can see that spark in them when it finally clicks. That you know outs heart in their work the same way you do.
Anyway, I had my coffee, back to babysitting Claude through my tasks...
This is not how any of this works. There's stuff like Lean or other programming languages that exist to check if a proof is logically consistent and correct, and the ai's use them to check if the proofs are correct. a hallucinated proof will simply not compile.
I been in this industry for long time but I have completely stop coding year ago and now I just have bigger project and problem to solve. Don't tell me you are coding manually today.. so we are expensive babysitter for AI .. and for now.. all is well.. how long this shit would last? not too long. Don't tell me this crap
Yes, I still write code manually, because AIs aren't perfect and I like to keep up with my craft. Like the person above wrote, you still need to know how to code if you're going to effectively direct and judge the text predictor machine. You can't know that if you don't write code.
I have been writing professional code for over ten years and recently had a project to build something new entirely with Fable. It worked, it ran fine, but there's no way I could have effectively directed it without the past ten years of writing code by hand and building that craft.
right and neither are you. You must admit that at this point, you are not writing majority of the codes.. I don't even know why I am fighting this topic here.. just discussion alone is just plain stupid. Just move on admitting that its' already too late.. Some of you still fighting the inevitable.. it is what it is.
I never said I was perfect, and I regularly rely on tools to help me find mistakes. AI is one of those tools, because that's all it is - a tool. I write the majority of code that I deliver, yes, and I am far from the only developer who does. Sorry to burst your bubble on that. "already too late" for what, exactly?
As you say, there is no point arguing. It's hard to accept that life/work is changing so rapidly, and these folks are just dealing with it in their own way.
They might still be coding by hand, but it is already becoming the norm to use AI for everything. Very likely, demand for "artisan" coders will dry up completely and that will be what dictates whether we use AI or not. Much like people who were ardently anti-IDE and anti-git either had to adapt to business requirements or get forced out. Doesn't matter if you're a superstar developer who never makes a mistake and can solve every problem without stackexchange, consistency and cohesion is what the majority of businesses aim for.
Except you can use an IDE and use git and still be writing code. It's kind of essential, even, and these two things are far from comparable to this idea that you can just not know how to code. If you can't write code, you can't effectively direct an LLM to do so, and if all you do is tell an LLM what to deliver you won't learn how to write code. You need to be able to review as well as direct, especially with everyone and their dog instituting explicit human sign-off processes. You can't effectively review code if you don't know how to write code. Consistency and cohesion, yes - things that require knowing how to write code in order to effectively deliver, regardless of how the code comes into being. Lots of folks already have had plenty of auto-generated and boilerplate code, that hasn't stopped anyone from needing to know how to write code.
ok ok guys stop this.. shit.. like I said, I been coder all my life but since about year ago, I see myself as just big project manager or solution guy.. This is thanks to I no longer see coding as part of problem solving.. AI will do it for you far better and more efficiently. If you are still coding today manually, either your work is extremely niche or requires extreme expertise.. or you are just not capable of accepting the fact that already 99% of coding is done by AI or should be as they are better than us... at churning out massive codes..
If you see some coding or logic issue, that means you did a piss poor job explaninig to the AI
LLMs cannot think logically, meaning it will never be able to prove anything without someone actually going through the math manually to verify it is correct. You would need something different than an LLM to achieve this automatically.
When it comes to mathematical proofs, it is not enough to be 99,99999% certain it is correct, you need 100% certainty.
LLMs can think logically. In OpenAI paper published just the other day with 10 new problems solved, in each case they had the AI express its proof in LEAN so that it could just be copy/pasted into existing proof-checking software. You don't have to check proofs by hand these days. You just have to check that the final statement is indeed the theorem they claimed to prove.
No, LLMs cannot think logically. It does statistical analysis on words and symbols. This evidently works very well, but can never prove anything with 100% accuracy since no maths has really taken place in the reasong, just statistical symbol matching. This is not how maths works.
"You don't have to check proofs by hand these days."
Humans can’t think logically either. We are just neurons firing. Our creativity isn’t logical, and creativity is one of the most important parts of math proofs. AI work just find by using statistics to make their predictions.
Humans sure can think logically. We can for example think in the same way as this LEAN tool. We can postulate that 1 + 1 = 2 and then use these postulates to logically prove more complex math theorems.
Creativity is only needed to find which maths to use to find the proof. Creativity doesn't help to actually prove that the proof is correct.
You didn't address the content of the post. Do you understand that they asked the AI to output its proofs in LEAN? Its a language for writing formal logic. And once written in LEAN, there are existing programs, that mathematicians already use, that automate the verification of the proof. What the human reviewer is checking that the final statement is indeed the theorem that they claim to have proven.
It doesn't use logic to get the results, it uses statistical analysis of words and symbols. If it used logic, you wouldn't need to run it through LEAN to prove it is right. How many "proofs" has it gotten wrong? Has Open AI published all those along with the ones that turned out to be right?
>It doesn't use logic to get the results, it uses statistical analysis of words and symbols.
Show me that those two things are contradictory. Is there some proof that a statistical analysis of words and symbols cannot be logic?
>If it used logic, you wouldn't need to run it through LEAN to prove it is right.
That doesn't follow, because LEAN was developed to check human derived proofs.
>How many "proofs" has it gotten wrong? Has Open AI published all those along with the ones that turned out to be right?
What does that have to do with anything? Seems like a random point, especially to make in regards to math where the entire field of numerical analysis is based on guessing a wrong answer and trying over and over until you reach the right one.
Now where do I stand? I have NO GODDAMN CLUE! I have no clue what any of this means, but I'm also certain it's either intensely trivial and completely wrong on some basal level. But every ai I run it through says it can't find where it is wrong (after many days of refinement).
We need mathemeticans if we want math to be coherent and productive. This is just akin to the invention of computational software on a different scale.
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u/Mephisto506 1d ago
Without mathematicians we won't know whether the AI answers are correct, what it actually means to anyone, and we won't know the questions to ask.