Lily Hu is a PhD candidate in Applied Mathematics at Harvard University, and a Fellow at the Berkman Klein Center for Internet and Society, where she studies algorithmic fairness, political philosophy, and philosophy of artificial intelligence and machine learning. Broadly, her academic interests include machine learning in social and economic environments, theories of distributive justice, and connections between algorithmic fairness and welfare economics. Her current time is divided between computer science-related research, where she studies theoretical properties of machine learning tools as resource distribution mechanisms, and philosophy work, where she considers the epistemological underpinnings of machine learning and the normative force of predictions issued by computational tools.