Data & AI Ethics

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.

At a glance

Where Munich, Germany (in person)

What Series of talks (each circa 20 minutes + 10 minutes discussion).

When Friday, November 14, 2025, circa 9:00 - 17:15.

Themes, Contributions, and Program

A detailed program is now available here. You can find a list of abstracts here.
The workshop will feature the following confirmed contributions. 

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): Ethical Software Development and Data Ethics
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 & Louis Longin (University of Mannheim & LMU Munich): 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.

Location

The workshop will take place in Schellingstraße 3, Munich, Germany, near the main buildings of LMU Munich and the Technical University of Munich (TUM). Directions and information on local food options are now available here.

Registration and Workshop Fees

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.

Acknowledgments

The organizers are grateful to the Munich Center for Machine Learning (MCML), the research project "Green Data, Indicators, Algorithms: Connecting Green Finance and Smart Cities" (GreenDIA), the LMU Open Science Center (OSC), as well as LMU Munich and TU Munich for their support.

Contact

If you have any questions, please do not hesitate to contact epix.workshop@stat.uni-muenchen.de.