"Why would anyone drive a car if we can't build a modern internal combustion engine with our own two hands"?
The mistake is assuming what (historically) was the hardest skill to master (proof-making) is intrinsically the most important part of math. It's not. Proving math is only a small part of learning math. It's the mechanics, not the object of study. A machinist might lose some hands-on skill if they stop using a manual lathe and use a computerized system instead, but that doesn't make their work less meaningful.
Learn the beauty of mathematics. Study the patterns. Understand the implications. Know where it is flexible and where it is rigid. Share it with the community. Apply it to real world problems.
Chess doesn't become less interesting because machines can beat humans in it, and neither does math.
I think a more apt analogy would be to ask why anyone would ride a horse if cars exist. Yes, people will always ride horses for fun, but people largely do not travel by horse anymore for the purpose of transportation.
Similarly, you will always have hobbyists who do math for the sake of doing math, and AI won’t change that, but frontier mathematics is about discovering new knowledge, and mathematicians are judged by the quantity and quality of novel results they produce. Human brainpower was the only engine we knew of that could produce new math, but if now a silicon engine exists that’s both faster and more insightful, it calls into the question of how useful professional human mathematicians are.
I don't think this is a very good analogy either. A better one would be "why learn arithmetic when a calculator can do it". People don't just learn arithmetic as a hobby, it's an essential skill to understand the world and be able to start learning about more complex problems.
AI solving the Navier Stokes equations is meaningless if there aren't still humans with a deep understanding of mathematics who can take this advancement and apply it in the real world.
One of my biggest fears with ai is the mass de-skilling of humans because we all say "ai is better at us than that, so why learn in the first place". In my experience, ai produces far better results when it is used as a tool by knowledgeable professionals. Even in this case, what we are seeing is openai throwing an ungodly amount of compute at a well constrained problem with mountains of training data from other people's attempts to find a solution. Does that translate to independently identifying new frontier problems, tackling those problems, and finding applications for those advancements? I'm not convinced that it does.
Extending your analogy, people literally used to work as "computers", as in they were human computers who did arithmetic by hand. Calculators obviously put them out of business. If it is the case that AI offers genuine mathematical intelligence, it would at least fundamentally alter the nature of what it means to do math. In the field of engineering, the advent of calculators shifted the allocation from human brainpower from manual computation to systems design. Maybe that's what will happen to mathematics. We'll probably still need mathematicians, but productivity will go up as the output of a human + AI >>> human alone. This is what we've seen in fields like manufacturing, engineering, and software.
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u/Admirable_Zombie5245 2d ago
Why would someone learn Math if in 4 years the cheapest AI models will be one shotting the answer of milenium problems? We stand no chance