Trustworthy User Modeling and Recommendation from Technical and Regulatory Perspectives

This tutorial provides an interdisciplinary overview of fairness, non-discrimination, transparency, privacy, and security in the context of recommender systems. According to European policies, these are essential dimensions of trustworthy AI systems but also extend to the global debate on regulating AI technology. Since the aspects mentioned earlier require more than technical considerations, we discuss these topics from ethical, legal, and regulatory perspectives. While the tutorial's primary focus is on presenting technical solutions that address the mentioned topics of trustworthiness, it also equips the primarily technical audience of UMAP with the necessary understanding of the social and ethical implications of their research and development and recent ethical guidelines and regulatory frameworks.