Trustworthy Algorithmic Ranking Systems

Abstract

This tutorial aims at providing its audience an interdisciplinary overview about the topics of fairness and non-discrimination, diversity, and transparency as relevant dimensions of trustworthy AI systems, tailored to algorithmic ranking systems such as search engines and recommender systems. We will equip the mostly technical audience of WSDM with the necessary understanding of the social and ethical implications of their research and development on the one hand, and of recent ethical guidelines and regulatory frameworks addressing the aforementioned dimensions on the other hand. While the tutorial foremost takes a European perspective, starting from the concept of trustworthy AI and discussing EU regulation in this area currently in the implementation stages, we also consider related initiatives worldwide. Since ensuring non-discrimination, diversity, and transparency in retrieval and recommendation systems is an endeavor in which academic institutions and companies in different parts of the world should collaborate, this tutorial is relevant for researchers and practitioners interested in the ethical, social, and legal impact of their work. The tutorial, therefore, targets both academic scholars and practitioners around the globe, by reviewing recent research and providing practical examples addressing these particular trustworthiness aspects, and showcasing how new regulations affect the audience's daily work.