Two former quant traders and current MTS's raising kids in the age of AI Harvard '17 and Princeton '16
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We've written about the importance of rigorous foundational skills and learning how to learn in the age of AI. But consider a world where AI performs all economically valuable labor, and our children no longer need to work for a living. What will make them happy? 🧵
This is a preview of what could happen across scientific and creative fields. The third category is creation and community participation. Open-source developers have historically contributed substantial work without commensurate financial compensation.
Aaronson, "The Mathocalypse": scottaaronson.blog/?p=10169
Lozano-Robledo: nitter.cf/mathandcobb/status/210…
Alpöge: nitter.cf/__alpoge__/status/2107…
Tao: mathstodon.xyz/@tao/11739526…
Big, big, big, big props for quasiriemann and no Siegel zeroes (with many other beauties in there), I’m kicking myself for talking all over about it being within reach but not actually having pushed.
There are some sad stories related to their users getting scooped / conflicts of interest (kakeya maximal comes to mind), and obviously we had some of the problems (without commenting on precise rumours).
We should put that aside for today though. It’s obviously the most significant moment in mathematical history.
Open-source contributors study: papers.ssrn.com/sol3/papers.…
Self-determination theory: selfdeterminationtheory.org/…
We're already seeing this tension in mathematics. Following OpenAI's release of hundreds of claimed mathematical breakthroughs, Scott Aaronson called the moment "The Mathocalypse."
Terence Tao raised a more fundamental concern: mathematical discoveries historically generated seminars, collaborations, new research directions, and entire communities. AI can produce the discoveries without generating the corresponding human activity.
Among the results was a claimed proof of the Unique Games Conjecture, which his wife Dana Moshkovitz had spent much of her career working toward.
If AI produces most new mathematical discoveries, the marginal value of a human mathematician's discoveries will decline dramatically, even as human math Olympiad medals remain prestigious.
The second is outcome-dependent achievement, including scientific discovery, mathematical research, and art. Here, AI poses a much greater threat to human prestige.
The prestige of these accomplishments comes from relative human performance, and is largely independent of machine capabilities. Chess, sports, math Olympiads, and other competitive games can continue providing an infinitely increasing bar for achievement.
Chess engines have been vastly superior to human players for decades, but Magnus Carlsen is still enormously respected. Cars are faster than Usain Bolt, but we still care about who is the fastest human runner.
Even if economic productivity becomes irrelevant, humans will continue to seek achievement and respect from one another. The first is repeated, human-skill-based competition.