Brookings Institution researcher Molly Kinder predicts a prolonged and painful period of AI-driven disruption that will hit knowledge workers far harder than blue-collar employees. Casey Newton reports for Platformer in an interview with Kinder, who is leaving Brookings to launch a new organization focused on solving what she calls the problems of the “AI transition.”
Kinder calls the coming period the “messy middle.” Most jobs will survive, she argues, but losses will concentrate in well-paid knowledge sectors like law, finance, consulting, and accounting. Her core argument: “If you can do your job locked in a closet with a computer, eventually you’re probably going to be in trouble.”
This marks a striking reversal. Computers boosted knowledge workers for decades, making them more productive and more valuable. Large language models like ChatGPT could now substitute for the cognitive work that once made those workers indispensable.
Targeted policy, not a universal check
Kinder rejects universal basic income as a response. If checks replace high salaries for everyone, she asks, why would anyone continue working as a nurse, police officer, or construction worker for far less? “You’ve just destroyed the labor market,” she says.
Instead, she proposes targeted interventions:
- A workforce reinvestment fund requiring companies that cut young workers to fund white-collar apprenticeships
- Wage insurance for older workers who must accept lower-paying jobs after displacement
- Government-created knowledge jobs if the private market fails to generate enough good ones
Kinder warns that inaction could repeat the failures of deindustrialization, when manufacturing job losses devastated communities and governments did little. If policymakers are not ready with a response, she says, public trust in AI will collapse further.
The messy middle, Kinder cautions, could last for decades. Even without a full jobs apocalypse, concentrated losses in coveted sectors would be, in her words, “politically explosive.”
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