Authored by Rachel Gillum with Gregory Leslie and Cara Wong, this chapter was published as part of the American Political Science Association’s Presidential Task Force on AI, Politics, and Political Science, a major disciplinary initiative examining how AI is reshaping politics, governance, research, and teaching.

This chapter examines how AI systems reshape racial and ethnic power across governance, political participation, and political science research. The chapter argues that AI bias is best understood as a structural issue rooted in data, institutions, and power. The chapter brings theories of race, identity, institutions, and power into AI governance debates that are often treated as purely technical.

The chapter also introduces the AI Measurement Statement, a practical disclosure framework for identifying group-differentiated measurement risks in AI-assisted research.