The Political Theory of Algorithms
Josh Simons in conversation with Lily Hu
Artificial intelligence and machine learning are reshaping our world. Powerful prediction tools are changing how decisions are made in key legal, medical, and consumer spheres, narrowing opportunities for the exercise of judgment, empathy, and creativity. How, then, are we to put democracy at the heart of AI governance?
In this conversation with Lily Hu, political theorist Josh Simons will argue that prediction is political: human choices about how to design and use predictive tools shape their effects. By approaching predictive technologies through the lens of political theory, Simons will show why we must go beyond conventional theorizing of AI ethics to wrestle with fundamental moral and political questions about how the governance of technology can support the flourishing of democracy.
Josh Simons is a research fellow in political theory at Harvard University. His research explores the politics and ethics of machine learning. His new book, Algorithms for the People: Democracy in the Age of AI, is published by Princeton University Press.
Lily Hu is Assistant Professor of Philosophy at Yale and contributing editor at Boston Review. She works in philosophy of science and social science and political and social philosophy. Her essay, “Race, Policing, and the Limits of Social Science”, was published in 2021 in Boston Review.