Many important economic and social decisions, beliefs, and attitudes arise from a learning process that
depends on the exchange of imperfect information across a potentially large and complex social network
involving heterogenous and self-interested agents. For example, an individual may seek to determine the veracity of a news story or image of consequence encountered on social media. Towards this end, they may interact with and gain information from other social media users or AI tools – search algorithms, AI-generated social media content, or large-language models.

Ela Leshem is a legal theorist who teaches and writes about the property and personhood status of human bodies, nation states, animals, fetuses, religious artifacts, venerated objects, and artificial intelligence. Her work has appeared in the Vanderbilt Law Review and Yale Law Journal. Before joining Fordham, she was a fellow at the Senate Judiciary Committee and clerked for Chief Judge David Barron on the U.S. Court of Appeals for the First Circuit.

Lily Hu is an Assistant Professor of Philosophy at Yale University. Her current projects broadly concern causal theorizing about the social world, with a particular focus on causal inference methodologies in the social sciences, how these various statistical frameworks treat and measure the “causal effect” of social categories such as race, and ultimately, how such methods are seen to back normative claims about racial discrimination and inequalities broadly.

Liane Huttner is a legal scholar with research interests in data protection law, digital law and AI. She holds a PhD from University Paris 1 Panthéon-Sorbonne. She has previously been a visiting scholar at the Institute of European and Comparative Law, University of Oxford, and at the Max Planck Institute for Comparative and International Private Law, Hamburg.