Track papers across labs, topics, and trends.
Search papers, labs, and topics across Lattice.
This paper investigates the potential of AI taxation as a policy tool to mitigate the externalities associated with artificial intelligence, such as environmental impacts and labor displacement. It argues that taxation can serve multiple purposes beyond mere Pigouvian correction, including redistributing costs and funding regulatory frameworks. The authors analyze various tax instruments, assessing their feasibility and implications for addressing the unique challenges posed by AI development and deployment.
Taxing AI could not only curb its negative externalities but also reshape the landscape of regulatory funding and social equity.
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.