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The Scarcity Worry

Jason Furman’s counter-intuitive alarm that the largest risk of the AI transition is not having too much of the technology but too little—that the productivity gains a stagnating economy desperately needs may arrive too slowly, or not at all, while policymakers focus on the wrong dangers.
The dominant anxiety surrounding artificial intelligence concerns excess: too much disruption, too many jobs automated away, too much power concentrated in too few hands. Jason Furman does not dismiss these concerns, but he insists they are incomplete. His “scarcity worry,” stated most directly in his 2016 address “Is This Time Different?,” holds that the largest worry is that we will not get enough artificial intelligence—that the productivity it promises will arrive too slowly to lift stagnating wages and shrinking labor force participation. A technology capable of generating the kind of broad-based productivity growth that the economy has not seen since the 1990s should be welcomed and accelerated, he argues, not merely managed and mitigated. The worry connects to the productivity paradox—the stubborn gap between AI’s apparent power and its measurable economic footprint—and to the historical observation that general purpose technologies require decades of complementary investment before their gains show
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