AI, Automation and Taxation - Spencer Bastani; Daniel Waldenström (Center for Economic Studies and ifo Institute (CESifo), 2024)
This paper examines the implications of Artificial Intelligence (AI) and automation for the taxation of labor and capital in advanced economies. It synthesizes empirical evidence on worker displacement, productivity, and income inequality, as well as theoretical frameworks for optimal taxation. Implications for tax policy are discussed, focusing on the level of capital taxes and the progressivity of labor taxes. While there may be a need to adjust the level of capital taxes and the structure of labor income taxation, there are potential drawbacks of overly progressive taxation and universal basic income schemes that could undermine work incentives, economic growth, and long-term household welfare. Some of the challenges posed by AI and automation may also be better addressed through regulatory measures rather than tax policy.
Keywords: H21; H30; O33; 330; AI; automation; inequality; labor share; optimal taxation; tax progressivity