Hard Fork

Is A.I. Eating the Labor Market? + The Latest on the Pentagon, OpenClaw and Alpha School

with Anton Korinek
27 Feb 2026 15 min read 33m
TL;DR

AI's economic impact remains largely speculative—current data shows only small productivity gains—but if capabilities continue scaling, recursive self-improvement could trigger hyperbolic growth that fundamentally disrupts labor markets. The gap between frontier AI capabilities and actual workplace deployment is real and significant, but it will eventually close, likely bringing both productivity gains and labor displacement.

Key Moments
Casey Newton
“I have a fiance. I have a fiance.”
Casey announces her engagement to her boyfriend who works at Anthropic, updating the show's disclosure
▶ 0:20
Anton Korinek
“It's still in the in the realm of expectations. So, if you look at the actual data, you can see some relatively small impacts of AI on things like the job market, things like productivity growth, but they're still, first First in the territory where they're very small, like fractions of a percent, and secondly, still contested.”
Korinek explains that despite market volatility, there is no hard economic data yet showing significant AI impacts
▶ 7:24
Anton Korinek
“I think there's a very big gap between the frontier of what's possible and what is actually used in daily use. And what the paper that you just mentioned tells us is that in the field, when it comes to how actual corporations are using these technologies, as of a couple months ago, there wasn't really that big of an impact yet.”
Korinek reconciles the contradiction between widespread AI deployment and minimal measured impact on employment and productivity
▶ 10:11
Anton Korinek
“I have studied neuroscience. I have studied computer science, and at some level, you know, once basically deep neural networks became powerful, I felt it is hard to not make the conclusion that well, it looks like eventually these systems will be able to do pretty much anything that our brains can do and they're subject to much, much more relaxed constraints.”
Korinek explains his confidence that AI will eventually match or exceed human capabilities based on the fundamental differences in scalability between artificial and biological systems
▶ 18:43
Anton Korinek
“I'm not 100% sure if there will still be jobs for economic researchers by the time that they graduate. I'm crossing my fingers for them. I hope that there will be, but I don't think we can count on it at this point.”
Korinek tells his graduate students directly about the uncertainty AI poses to their future career prospects
▶ 31:14
About Anton Korinek
›
Anton Korinek is a professor of economics at the Darden School of Business at the University of Virginia and a member of Anthropic's Economic Advisory Council since April 2024. For over a decade, he has studied the potential economic impacts of AI, including scenarios of mass job displacement and recursive self-improvement. He is known among economists for seriously considering AGI and its transformative potential—positions that were once considered fringe but are increasingly mainstream.
Takeaways
1
Current data shows AI impact remains negligible Despite 70% of companies using AI, surveys show 80% report no employment or productivity impact yet. This reflects the massive gap between frontier capabilities and actual workplace deployment—companies are still figuring out how to move from demos to productive implementation at scale.
2
Labor displacement differs fundamentally from past automation Unlike previous technological waves that created new jobs, AGI-level systems could directly substitute for human labor across most economically valuable work. This breaks the 'lump of labor fallacy' economists relied on—demand for human labor itself could shrink rather than merely shift to new sectors.
3
Hyperbolic growth becomes possible with recursive self-improvement If AI reaches the capability threshold to improve itself, feedback loops between software advances, hardware breakthroughs, robotics, and energy research could trigger super-exponential economic growth until physical resource constraints emerge. CEOs should actively assess frontier capabilities now rather than waiting for models to mature.