PhilML'26 – Philosophy of Machine Learning Conference

PhilML’26, the Philosophy of Machine Learning Conference, will take place at LMU Munich from October 7 to 9, 2026, preceded by a graduate workshop on October 6. The conference brings together philosophers and machine learning researchers to explore foundational epistemological, ethical, and social questions surrounding machine learning.

The conference is organized by MCML PI Tom Sterkenburg and MCML Junior Member Timo Freiesleben, together with Thomas Grote and Kate Vredenburgh. Sterkenburg’s research focuses on the epistemological foundations of machine learning and the philosophical questions surrounding learning, reliability, and inductive bias.

The program addresses topics including learning, robustness, explainability, causality, trust, transparency, reliability, and fairness, as well as emerging questions raised by foundation models, such as agency, alignment, authorship, safety, and mechanistic interpretability. The conference also explores the intersections of machine learning with public policy and scientific methodology.

The conference will be held at the LMU main building, Geschwister-Scholl-Platz 1, Munich.