This workshop is a joint initiative by the Data Ethics Group at LMU's Department of Statistics and the Munich Center for Machine Learning (MCML).
The Data & AI Ethics Workshop (read: Data Ethics & AI Ethics) aims to bring together researchers from a range of disciplines who are concerned with current ethical questions surrounding data. From data science, machine learning, and statistics, to ethics and philosophy, to the social sciences and the humanities – we welcome all areas engaging with data and data ethics.
In the age of data-driven research and decision-making, questions of data ethics are as important as ever. Moreover, with the growing influence of artificial intelligence, new challenges are emerging, and some old questions take on renewed urgency. Thus, this workshop also asks: how does AI ethics intersect with, and inform, data ethics?
Through a series of talks and ample time for discussion, the workshop will offer space for dialogue about data ethics across disciplinary boundaries. We especially aim to foster exchange among communities that do not often have the opportunity to meet – and invite anyone interested in these topics to join the conversation.
Where Munich, Germany (in person)
What Series of talks (each circa 20 minutes + 10 minutes discussion).
When Friday, November 14, 2025, circa 9:00 - 17:45.
The workshop will feature the following confirmed contributions. A detailed programme will be published soon. You can find a list of abstracts here.
Embedding Ethics into Data Practice and Education
Theresa Willem (TUM): Embedding Ethics in Medical AI
Paula Hepp, Jonas Fischer & Amelia Fiske (TUM): Incorporating Graphic Art as a Translational Tool to Advance Health Data Justice
Niina Zuber & Jan Gogoll (bidt): Introduction to Ethical Software Development
Lisa Kauck & Katharina Schüller (STAT-UP GmbH): From Knowledge to Values: Ethics by Design in Data Science Education
Kim Hajek & Paul Trauttmansdorff (TUM and Ethical Data Initiative): Data Ethics in Practice: The Ethical Data Initiative and Data Clinics as a Collaborative Teaching Format
Machine Learning and Data
Helen Alber (LMU Munich): Human Perspectives in Machine Learning: Ethical and Epistemic Challenges
Timo Freiesleben (University of Tübingen): The Benchmarking Epistemology – Construct Validity for Machine Learning Evaluation
The Philosophy and Ethics of Data
Rena Alcalay (TUM): Bodily Doubt and Survivor Bias: Epistemic Harms in Medical Data Ethics
Frederic Gerdon (University of Mannheim): When Does Inference-making Violate Individuals' Privacy (Rights)?
Institutions, Governance, and Data Ownership
Thomas Meier (LMU Munich & MCML): Reclaiming the Moral Commons. A Communitarian and Technomoral Critique of Power in the Age of Trillionaires
Walter Radermacher (LMU Munich): Trustworthiness of Statistics. Threats. Countermeasures.
The workshop will take place in Schellingstraße 3, Munich, Germany, near the main buildings of LMU Munich and the Technical University of Munich (TUM).
The workshop is free of charge, but registration is required.
Please register here by November 1, 2025. As slots are limited, please let us know if you have registered but no longer plan to attend.
If you have any questions, please do not hesitate to contact epix.workshop@stat.uni-muenchen.de.
PostDoc in "Green Data, Indicators, Algorithms: Connecting Green Finance and Smart Cities",
Social Data Science and AI Lab,
LMU Munich
PostDoc, MCML Reproducibility and Open Science Transfer Coordinator,
LMU Munich
PostDoc in "Consequences of AI-Based Decision Making for Urban Societies", MZES & University of Mannheim
Department of Statistics,
LMU Munich