Thomas is an interdisciplinary Ph.D. candidate in Machine Ethics and Epistemology at UC Berkeley. With prior training in philosophy, sociology, and political theory, he investigates the ethical and political predicaments that emerge when artificial intelligence reshapes the context of organizational decision-making.
His recent work investigates how specific algorithmic learning procedures (such as reinforcement learning) reframe classical ethical questions and recall the foundations of democratic political philosophy, namely the significance of popular sovereignty and dissent for resolving normative uncertainty and modeling human preferences. Thomas is serving as the inaugural Law and Society Fellow at the Simons Institute for the Theory of Computing
, research affiliate with the Center for Human-Compatible AI
, and cofounder of GEESE