I look at public policy through the lens of computer science, bringing a computational perspective to a diverse range of contemporary social issues. My recent work has examined policing practices, including the development of new statistical tests for discrimination; fair machine learning, including guidance for designing equitable algorithms; access to education; and democratic governance, including swing voting, polling errors, voter fraud, and political polarization.I often write essays and engage in public discussions on policy issues from a statistical perspective. These include examinations of algorithms in the courts (in the New York Times and the Boston Globe); algorithmic fairness (in the Washington Post and on the Moral Science Podcast); policing (in the Washington Post, Slate, and the Huffington Post); mass incarceration (in the Washington Post); election polls (in the New York Times); claims of voter fraud (in Slate and on This American Life); and college admissions (in the Boston Globe, Boston Review, and the Washington Post).