Workshop led by Prof. Dr. Christoph Kern (LMU).
In this workshop, we will discuss how concepts of dissimilarity can inform fairness-aware data practices. This includes discussing what the fairness in machine learning (fair ML) literature has to offer for advancing responsible empirical research across academic disciplines.
Research in fair ML focuses on the social implications of prediction-based decision models and develops methods to quantify and mitigate biases that may adversely impact social groups. However, the scope of fair ML spans beyond fair prediction modeling as it invites reflection on the conceptualization of historical disadvantage and on diversity in datasets.
The workshop is part of the CAS Research Focus “Dis/Similarities – Discourses on Diversity and Uniformity”.
Registration
Registration is required for participation. If you are interested in our event, please contact us:info@cas.lmu.de.