Taxing Artificial Intelligence
Abstract
While AI promises major benefits, its development and deployment can shift costs onto others, including environmental pressures on local communities, labor and creative displacement, and systemic risks from rapid frontier development. Taxation is an integral part of policy design, and recent academic, industry, and policy debates have begun to consider whether tax instruments can help address these harms. In this paper, we explore the viability of AI taxation. More broadly, AI taxation should not be understood only as Pigouvian correction. In the AI context, taxation can also correct harmful activity, redistribute unevenly borne costs and gains, and fund regulatory capacity. We discuss the main externalities associated with AI and survey possible tax instruments, including corporate income and rent-based taxes, consumption taxes on AI-related services, and excise instruments tied to specific AI activities. We further assess the benefits and pitfalls of these instruments, including feasibility, measurement problems, incidence, leakage, and innovation costs. Because AI externalities differ in nuanced ways, tax policy must be carefully designed and matched to the specific harms and policy objectives.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.