Associated with the Linz Institute of Technology and the Institute of Computational Perception @ JKU Linz, Austria

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 the main 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 ethical implications of their research and development on the one hand, and of recent political and legal regulations that address the aforementioned dimensions on the other hand. While the tutorial foremost takes a European perspective, because EU regulation is at the forefront of elaborating guidelines for ethical and trustworthy AI, we also review initiatives outside of Europe, in particular in the US and China. Since ensuring non-discrimination, diversity, and transparency in retrieval and recommendation systems is a global endeavor in which academic institutions and companies in different parts of the world collaborate, this tutorial is relevant also to researchers and practitioners in countries that do not regulate AI technologies yet, in particular since we are experiencing more and more of such regulations recently. The tutorial, therefore, targets both academic scholars as well as practitioners around the globe, by reviewing recent research and providing practical examples addressing one or more of the trustworthiness aspects, and showcasing how new regulations affect the audience's daily work.


Citation

Markus Schedl, Emilia Gómez, Elisabeth Lex
Trustworthy Algorithmic Ranking Systems
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), 2023.

BibTeX

@inproceedings{Schedl2023Tutorial_WSDM_2023,
    title = {Trustworthy Algorithmic Ranking Systems},
    author = {Schedl, Markus and Gómez, Emilia and Lex, Elisabeth},
    booktitle = {Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023)},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    location = {Singapore, Singapore},
    month = {February-March},
    year = {2023}
}

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