Report on the CyCAT winter school on fairness, accountability, transparency and ethics (FATE) in AI

Styliani Kleanthous, Jahna Otterbacher, Jo Bates, Fausto Giunchiglia, Frank Hopfgartner, Tsvi Kuflik, Kalia Orphanou, Monica L. Paramita, Michael Rovatsos, Avital Shulner-Tal

Research output: Contribution to journalArticlepeer-review

Abstract

The first FATE Winter School, organized by the Cyprus Center for Algorithmic Transparency (CyCAT) provided a forum for both students as well as senior researchers to examine the complex topic of Fairness, Accountability, Transparency and Ethics (FATE). Through a program that included two invited keynotes, as well as sessions led by CyCAT partners across Europe and Israel, participants were exposed to a range of approaches on FATE, in a holistic manner. During the Winter School, the team also organized a hands-on activity to evaluate a tool-based intervention where participants interacted with eight prototypes of bias-aware search engines. Finally, participants were invited to join one of four collaborative projects coordinated by CyCAT, thus furthering common understanding and interdisciplinary collaboration on this emerging topic.
Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalSIGIR Forum (ACM Special Interest Group on Information Retrieval)
Volume55
Issue number1
DOIs
StatePublished - 2021

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