Brett Hemenway Falk of the University of Pennsylvania and Gerry Tsoukalas of Boston University have a fascinating new paper, The AI Layoff Trap, which identifies what may become one of the central macroeconomic problems of the AI revolution: what happens if firms start replacing workers with AI faster than the economy can create new jobs and incomes for them? Their answer is unsettling. Workers are also consumers. By replacing them, firms may collectively erode the demand on which their own profits depend.
The mechanism is a classic negative externality with an unusual twist. A company replacing a worker with AI captures the entire cost saving, while bearing only a fraction of the resulting loss in consumer demand. The rest is imposed on its competitors. Each company therefore has a perfectly rational incentive to automate even when all companies would ultimately be better off if they automated less aggressively. In the extreme, this becomes a prisoners’ dilemma: everyone races to cut labour costs, only to discover that they have collectively destroyed part of their customer base.
Consider an industry with 20 similarly sized firms. If one company replaces workers with AI, it captures 100 per cent of the labour-cost saving but experiences only roughly one-twentieth of the resulting decline in demand through its own sales. The remaining 19/20 is dispersed among its competitors. From the perspective of the individual company, automation therefore looks overwhelmingly attractive.
But suppose all 20 firms make exactly the same calculation. What was negligible at the company level becomes substantial at the aggregate level. Employment and household incomes fall, consumption declines and all 20 companies confront a shrinking market. This is a textbook fallacy of composition: what is rational for one company becomes collectively destructive when everybody does it.
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