Predictions about the economic effects of artificial intelligence (AI) range widely, with some analysts expecting rapid productivity growth and wider prosperity, while others foresee significant job displacement and increased inequality. The future remains uncertain, yet the scale of potential disruptions should not be underestimated.
AI could profoundly alter the labor market and income distribution, prompting calls for major fiscal policy changes. However, fiscal institutions cannot be developed overnight. Gathering and analyzing evidence takes time, and crafting, enacting, and implementing new policies requires even more. The delayed policy response to the ‘China shock’ highlights the need for proactive measures to address AI’s challenges.
“Policymakers should begin developing forms of ‘fiscal insurance’ against AI’s most significant risks,”
Two key risks warrant attention. First, large-scale worker displacement could arise as AI creates new jobs while eliminating existing ones. Displaced workers might struggle to find jobs matching their skills or location, facing prolonged unemployment and loss of income. This situation can affect not only wages but also workers’ health, families, and communities. The U.S. has some policy frameworks, like Trade Adjustment Assistance, but they remain narrow and cumbersome. Policymakers must design a modern system to help workers without needing to prove specific causes for job loss. It should include temporary income support, training, job-search assistance, and wage insurance.
Second, AI might increase the percentage of national income going to capital rather than labor, further concentrating wealth and political influence. Raising taxes on capital income, wealth, inheritances, or consumption could help finance policies to cushion worker displacement and promote prosperity. Alternatively, broadening ownership of financial assets could offer a more sustainable approach. This might involve a sovereign wealth fund or placing equity stakes in individual accounts, each with unique challenges regarding management and political issues.
These policy options need development and evaluation before implementation on a national scale. Starting this work now prepares for potential economic shifts that AI may introduce.
Douglas Elmendorf and Louise Sheiner, the authors, have extensive experience in fiscal policy. Elmendorf was the director of the Congressional Budget Office and served as the dean of Harvard’s Kennedy School of Government. Sheiner formerly worked at the Federal Reserve Board and is the policy director at Brookings’ Hutchins Center on Fiscal and Monetary Policy.
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