This is a Brookings Center on Regulation and Markets working paper.
Korinek holds an unpaid position on the Economic Advisory Council of Anthropic, an AI company. Anthropic did not have any input into this analysis or right to review the authors’ recommendations. The views represented here are those of the authors.
Abstract
Transformative artificial intelligence (TAI)—machines capable of performing virtually all economically valuable work—may gradually erode the two main tax bases that underpin modern tax systems: labor income and human consumption. We examine optimal taxation across two stages of artificial intelligence (AI)-driven transformation. First, if AI displaces human labor, we find that consumption taxation may serve as a primary revenue instrument, with differential commodity taxation gaining renewed relevance as labor distortions lose their constraining role. In the second stage, as autonomous artificial general intelligence (AGI) systems both produce most economic value and absorb a growing share of resources, taxing human consumption may become an inadequate means of raising revenue. We show that the taxation of autonomous AGI systems can be framed as an optimal harvesting problem and find that the resulting tax rate on AGI depends on the rate at which humans discount the future. Our analysis provides a theoretically grounded approach to balancing efficiency and equity in the Age of AI. We also apply our insights to evaluate specific proposals such as taxes on robots, compute, and tokens, as well as sovereign wealth funds and windfall clauses.
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Acknowledgements and disclosures
This paper was prepared for the Brookings Center on Regulation and Markets (CRM) and presented at a Brookings CRM Authors’ Conference. We are grateful to Bill Gale and Matthew Weinzierl for their insightful reviews, and to Era Dabla-Norris, Anh Nguyen, Phil Trammell, and participants at a Brookings CRM Authors’ Conference and the NBER Economics of Transformative AI Workshop for helpful comments. Korinek created part of this work as a Visiting Fellow at the Brookings Institution. The views expressed in this work do not necessarily reflect the views
of the Brookings Institution.
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