Publications-ppc
Trustworthy Algorithmic Ranking Systems
Authors
Schedl M, Gómez E, Lex E.
UPF authors
Type
Conference proceedings
Book Authors
ACM SIGIR
Book title
WSDM 2023 - Proceedings of the 16th ACM International Conference on Web Search and Data Mining
Publisher
Association for Computing Machinery, Inc
Publication year
2023
Pages
1240-1243
ISBN
9781450394079
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. © 2023 Owner/Author.
Complete citation
Schedl M, Gómez E, Lex E.. Trustworthy Algorithmic Ranking Systems. In: ACM SIGIR. WSDM 2023 - Proceedings of the 16th ACM International Conference on Web Search and Data Mining. 1 ed. Association for Computing Machinery, Inc; 2023. p. 1240-1243.