Manual labor and trades is likely to be one of the last things to go, so the whole "dropout of school and go into trades" crowd may have been more correct than ever, though their original reasoning was not.
Yes, this is likely true. Plumber & Electrician on existing construction will likely take a long time (relatively speaking) to automate. And even if we end up being able to do it, it could be that humans will be the cheapest option when it comes to a lot of manual jobs especially given that there will be a large supply of unemployed humans in many scenarios.
Especially if the timeline is 40 years (as opposed to, say... 4.) I have no doubt AI-assisted robotics development would have solved the plumber and electrician jobs in a decade or two.
But I’m not sure it will take 40 years. I’m quite sure Astra could figure it out, it’s just too slow and robots are too weak. The speed will improve, and robots may lag shortly thereafter but by not much. I give it 1-2 years for AI, and 5-10 years for robots tops (perhaps even quicker).
Why are meta glasses such a big deal? Because they need training data for manual labor.
Realistically the outcome of highly capable advanced AI is an economic dark age more than anything else.
Robots automating everything and humans not needing to work was the stuff paradise fantasies were made of.
Sure, it would be the end of capitalism (which, I guess you could describe as "economic dark age"), but people these days have so little imagination what life outside of capitalism looks like that ideal societies sound like a horror story.
Communism was a horror for multiple reasons, but two big ones were: the planners didn't have the data or ability to actually plan (the interactions in a market economy did that much better), and not doing the work you were assigned was a crime (that is, slavery).
AGI and AGLabor solves both these problems. If you don't need workers, you don't need to coerce them into work. And planning and massive data collection (and management in general) sounds like something AGI would work very well at. The conceit that the lower classes are disempowered before the capitalists never struck me as well founded.
If it's you and me, then hey, we can all live happily ever after pursuing hobbies and art, provided for by our mechanical friends, within the limits of resource availability.
If it's an AI trillionaire, things aren't so rosy. If they don't need workers, why would they even bother allocating outputs from the robots to keep us alive?
I don't doubt at all that some group or another will enjoy the fruits of artificial labour. The question is how we are going to get there, and whether that group is most people who are live today and their descendants, or just the families and friends of trillionaires.
I guess one could make the argument that with enough control, a trillionaire could amass a private robot army. But I think regular humans still win (after an epic battle of course).
And jobs that require humans’ responsibility.
People can do people stuff, machines can do machine stuff. And market will react accordingly.
Meta glasses are a terrible example for the case you're making a point about: 90+% of whatever video they'll capture will be trash data.
It'd be much more efficient to set up dedicated sites just for producing the very same training data you're claiming they harvest.
So the obvious things that will probably increase in value will be stuff done/created in the real world, and creative work. We're also likely on the cusp of humanity having a much greater presence in the cosmos which will likely create the biggest labor boom in human history. I think the time-scale could also be far sooner than some might anticipate. We went from glorified markov chains to 'gg cognitive jobs' in a very brief period of time.
Something similar could happen in space going from 'neat we landed on Mars' to YOLO Galactic Imperia Humania, even if the earliest motivations may be as banal as 'We need to get to Europa [1] before China!' This is even more probable given the ability to defacto use this as a modern Works Progress Administration. [2] The countries left on Earth are going to see their influence shrink rapidly relative to countries that begin establishing meaningful grips on bodies outside of Earth.
[1] - https://en.wikipedia.org/wiki/Europa_(moon)
[2] - https://en.wikipedia.org/wiki/Works_Progress_Administration
It's also quite likely that the next big era for humanity will be the space era. And that stands to create the biggest labor boom in human history. It could also happen far faster than many might expect, even moreso as there will be competition between countries, especially as those left with only terrestrial claims will see their influence relatively wane. Space jobs and industry can also, in some ways, act as a more productive Works Progress Administration [1] to compensate for any temporary economic instability that LLMs might bring along.
[1] - https://en.wikipedia.org/wiki/Works_Progress_Administration
The second reason is that we often prefer humans to do it even if a machine can do it faster / cheaper. Sometimes, it's a status thing. For example, some people will buy Ikea furniture, some will have it custom made by a local craftsman. In fact, it's sort of the hallmark of the upper middle class that you can spend more for that human touch. Cupcakes from an artisanal bakery, private banker, etc.
Now, I don't think there's enough people who want to pay extra for human-made software. From the current trends in the industry, my impression is that we don't value our craft, so it would be surprising if others did. For mathematicians, I don't know; it's a bit painful to watch.
This is correct under present day thinking.
But imagine the accounting AI of twenty years hence. If it can reliably do the books, reduce and prevent fraud, significantly better than any human ever could, why would you still need the human in that loop?
In the present day it's a legal requirement, not to mention a practical requirement given present AI capabilities. That doesn't mean it still will be in the future.
To put it another way, if the human is on the hook for the agent, but the agent is proven by a decade+ of statistical evidence to be way less mistake/fraud prone than the human, what's the point of the human there?
What we're seeing so far is consistent with the training data being the upper bound for capabilities. They get better at recall / synthesis / reasoning over the corpus, but they don't, for example, acquire trans-human ethics; they're at best as ethical as we are, except not grounded by the fear of consequences. A perfectly-behaved, perfectly-moral LLM is not a given in 20 years, not unless your position is that there's room for unbounded, exponential self-improvement without any loss of fidelity. In that case, we'll probably have problems more pressing than the outlook for accounting jobs.
The honest answer is via politics not education, but this debate is often had in "apolitical" circles that try their best to ignore this.
Not needing to work is a neat future that might be ahead of us. But it could unlock some new negatives as well as positives.
https://youtube.com/shorts/CaJd88zh1h0?feature=shared
Free money and universal healthcare thanks to the abundance of Ai is where "they," say we are headed. Thanks to Ai ravaging our civil society we are use to.
A lot of people put a lot of their self-worth into their work and that’s a good thing that won’t change.
Sincerely,
An "old" person in their 30s.
Do you know where “the ball” is going? Do these math students? Do the professors? It’s easy to say a vague nothing platitude like “target where the ball is going to” but such empty vague platitudes do not help anyone and just waste time.
Human-crafted religious items and artwork may be more appealing than machine-crafted replicas.
I assumed the student ultimately wants a career that is financially viable.
> Then what?
Literally anything else?
Ironically, this very attitude could lead to AI creating one of the biggest slowdowns in progress in history.
It's this one, but different careers will diminish at different rates. Mathematics was already not financially well rewarded, and current AI is basically better than everyone in the field.
> this very attitude could lead to AI creating one of the biggest slowdowns in progress in history
I think there are enough young people with pre-AI experience that we'll probably develop superintelligence before they retire, so I don't really think a near-term lack of fresh talent will result in any significant slowdown.
Then why are frontier labs ploughing millions into racing human math researchers when they're already cash-strapped? What's the ROI for that?
> we'll probably develop superintelligence before they retire.
That ship has sailed:
https://www.whitehouse.gov/presidential-actions/2026/09/inau...
Mathematics was historically "just a hobby". Much theoretical work is still "just a hobby". But, for the past few hundred years, humans that better understood the theory could find very profitable applications.
That is no longer true. Computers have solved mathematics, like they did chess two decades ago. A human will never find a better application than a computer, just like they will never find a better chess move. Yet people still play chess, and people still make money tutoring chess.
That is the future of humans in mathematics. Mathematics will become mathematics competitions. It will be just another intellectual sport. Sure, a sport that teaches valuable life lessons, but still "just a game". If you are going into mathematics today, your future career is as a competition mathematics coach.
1. I recognized that understanding math had incredibly profitable applications.
2. It was a sport.
3. It was a hobby.
Do I think the world will look the same when math is "solved"? Absolutely not! And we're seeing it transform right before our eyes. I routinely ask Claude, "here's the general idea for a math/cs/ai problem I'm working on, can you help me figure out the maths? oh and then implement it too."
Could I figure this out myself? Of course. Having the idea is halfway to formalizing it in math. But I remember even last year working on GPU kernels by hand and having a bunch of little arithmetic or indexing errors burn me, because I'm just slower and less perfect at doing the math correctly. Now I basically just tell Claude, "go optimize a GPU kernel for this problem". I still have to tell it what to look out for (architectural, algorithmic, memory improvements), but I'm sure the next model won't even need that.
> What specific direct advice would you give then if you could talk to someone who is currently studying math?
Do it for personal satisfaction, but find another way to pay the bills.
FWIW, I did like that the article at least acknowledged that the fundamental question is whether LLM-based approaches will eventually "max out", i.e. will they be limited to the "convex hull of ideas outlined in literature" as the article out it.
If LLMs do eventually hit a wall, then great, humans will still have a role to play. If not, though, we're all completely fucked - none of this nonsense about "humans managing agents" or providing "unique human insight" and what not, as agents will be more than capable of managing themselves and providing superior insight.
Do programming, electrical engineering, control systems, robotics, ML, statistics, etc.
Eg, we're probably very far off from having factories or new devices be entirely designed and built by robots. Somebody's going to need to get their hands dirty for quite a while still.
Whoops, people stopped caring about your sport!
> Just about anyone who has played a sport has heard that they have to target where the ball is moving to, not where the ball is right now. In this regard I am consistently disappointed with the commentary that mathematicians have been producing lately.
Reading this it feels like you haven't played a sport.
But nothing is certain. I am trying to avoid overspecialization and remain flexible, just as you advise. If this path fails I might become a paramedic or physiotherapist.
Go into things expecting you might have to change careers.
The sports analogy holds; the future location of the ball may be uncertain, but that is the student's target, and not overcommitting to the present location of the ball. The commenter is expressing disappointment that the commentary seems to be reacting to the present too much.
I think the problem is the reverse. We no longer can make good predictions for four years ahead, certainly not eight.
And yet, people have to make choices - so they need advice and some kind of hope of a guess.
> you might have to change careers.
I hope this is some dust dry humor!
In the UK only about 30-40% of students end up working in an area related to their degree.
The people who have a realistic plan that works out for them are a minority.
Sure you wouldn’t predict what you would work on exactly. And there were better tools, better communication and so on sure, but no disruptive innovations or seismic shifts really.
Some of those complaining today are the ones who keep saying "LLMs are just stochastic parrots predicting the next word", "how can AI do math if they can't even count the number of 'r's in strawberry?", etc.
It doesn't take a genius to realize AI will start getting better and possibly become a "threat" even before all this mathocalypse stuff happened.
For all the arrogance the hard sciences have, in the end they are just as human as their humanities counterparts. They just thought they were above becoming worthless because science was elevated above the softer sciences.
But the ball is flying out of the court and into the abyss.
Don't go classically into that qubit night.
But the post does do this: "[...] even if their capacity becomes far superior, there will always be a need for mathematicians at all levels to guide research in paths that make sense for humans to walk (not run)."
> Of course it will get better at exposition than humans.
I'm not so sure about this, because I don't know how one would train towards better exposition as it's not easy to check for good or bad exposition at scale.
As a student, I am actively making decisions which will shape my career for the next forty or so years. At a minimum a discussion like this should acknowledge the possibility that the current rate of AI progress continues apace. I understand the desire to be encouraging, but the best preparation for students involves the consideration of possibilities that current mathematicians negligently paper over.
Of course it will get better at exposition than humans. And it will prompt itself in due time.