Workshop
Epistemology and Theory of Machine Learning
Limits, Interpretability, and Knowledge in Modern AI
30.05.2025 - 31.05.2025
LMU Munich, Main Building, A 120
This is the second edition of the Epistemology and Theory of Machine Learning series started in 2023.
The rapid rise and huge impact of methods in machine learning raises important philosophical questions. There is, in particular, an increasing interest in questions of epistemology: how exactly do machine learning methods contribute to the pursuit of knowledge? Issues under this header include the justification and the fundamental limitations of such methods, their interpretability, and their implications for scientific reasoning in general. Since machine learning algorithms are, in the end, formal procedures, a formally-minded philosophical approach promises to be particularly fruitful for making progress on these issues. Such a study of modern machine learning algorithms can draw from a long tradition of work in formal epistemology and philosophy of science, as well as from work in computer science and the mathematics of machine learning. The aim of this workshop is to discuss epistemological questions of machine learning in this spirit.
This edition is organized by the Emmy Noether junior research group “From Bias to Knowledge: The Epistemology of Machine Learning”, funded by the German Research Foundation (DFG) and affiliated with MCML.
Related
Workshop • 27.09.2026 • Strasbourg Convention Center, Strasbourg, France
ShapeMI 2026 - MICCAI Workshop on Shape in Medical Imaging
MCML PI Christian Wachinger co-organizes ShapeMI 2026, a MICCAI workshop on shape analysis and geometric learning in medical imaging.
Challenge • 27.09.2026 - 01.10.2026 • Strasbourg, France
REG 2026 - MICCAI Grand Challenge
MCML members Zhengyang Xu, Fabian Gülhan, and Azar Kazemi co-organize REG 2026, a MICCAI Grand Challenge advancing AI for computational pathology.
Workshop • 27.09.2026 • Strasbourg Convention Center, Strasbourg, France
GRAIL 2026 - MICCAI Workshop on Graphs in Biomedical Image Analysis
MCML Junior Member Kamilia Zaripova co-organizes GRAIL 2026, a MICCAI workshop on graphs, geometric deep learning, and biomedical image analysis.
