The persistent idea that AI disruption could create a permanent underclass signals how much collateral damage AI companies will tolerate in their pursuit of AGI
Most people I know in the A.I. industry think the median person is screwed, and they have no idea what to do about it.
New York TimesJasmine Sun
Context & Ripple Effects
Earlier coverage paired an uneven AGI impact and a potential shift in power from labor to capital with warnings that society must either adapt faster or collectively constrain development. This report brings that distributional concern inside the AI industry itself.
The surrounding coverage also shows a contested picture: some research suggests people most exposed to workplace change may be relatively able to move jobs, while AI leaders have encountered more adoption resistance than expected. That makes confidence in broad-based gains an operational issue, not only a philosophical one.
First-order effects
The report sharpens scrutiny of AI companies’ responsibility for labor-market disruption, particularly where automation shifts income away from work and toward capital.
Workers and policymakers gain a clearer basis to demand transition measures and accountability, while AI firms must contend with the gap between their deployment ambitions and their stated uncertainty about social mitigation.
Second-order effects
Greater concern about unequal outcomes can reinforce adoption resistance, forcing AI vendors and deploying employers to make more concrete cases for worker benefits rather than only productivity gains.
If labor income weakens relative to capital income, governments whose revenues depend heavily on earnings could face fiscal pressure, increasing the stakes for tax and social-policy responses.
Third-order effects
If AI gains continue to accrue chiefly to a concentrated set of owners while displacement risks are broadly distributed, AI industrialization could deepen the existing capital-versus-labor imbalance rather than simply change job tasks.
The durable policy question shifts from whether AI transforms work to whether institutions can distribute its gains and absorb its losses quickly enough; the related coverage shows that answer remains contested.
The trend: This is part of the broader transition from AI’s promised productivity benefits to a political and institutional test of who captures those benefits and who bears the adjustment costs.
I think Jasmine is one of the most talented writers of her generation but this is a fantasyland where both classist obsessives & the precariat are being used to create a panic to extract resources which may well kill the emerging technologies that bring positive sum change
Most people I know in AI think the median person is screwed, and they have no idea what to do about it. I spent the last 3 months talking to dozens of researchers, economists, and policy experts about AI's impact on work; including reps from every frontier lab and several [image]
Nice work by Jasmine but...economists by and large don't expect a permanent underclass. You see that in our survey she links, but also 1) productivity high correlated w/ wages historically, 2) architectural disruption is slow (where is Waymo in *your* city?), 3) prices adjust 1/2…
“So while Anthropic employees insist that positive A.I. futures are possible — or else they wouldn't be building it — they often seem uncertain about whether that world is likely, or whether they personally are bringing it about.” www.nytimes.com/2026/04/30/o...
So much to take away from this NYT piece. Whether it happens quickly (3-5 years) or takes a decade, it's inevitable that AI will outperform humans in almost all knowledge-worker tasks. …