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FAccTRec 2025: The 8th Workshop on Responsible Recommendation
Conference proceeding   Open access

FAccTRec 2025: The 8th Workshop on Responsible Recommendation

Michael D. Ekstrand, Toshihiro Kamishima, Amifa Raj and Karlijn Dinnissen
Proceedings of the Nineteenth ACM Conference on Recommender Systems, pp 1371-1372
22 Sep 2025
DOI: https://doi.org/10.1145/3705328.3748502
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https://doi.org/10.1145/3705328.3748502View
Published, Version of Record (VoR) Open

Abstract

Human-centered computing Human-centered computing -- Collaborative and social computing Human-centered computing -- Collaborative and social computing -- Collaborative and social computing theory, concepts and paradigms Human-centered computing -- Collaborative and social computing -- Collaborative and social computing theory, concepts and paradigms -- Social recommendation Information systems Information systems -- Information retrieval Information systems -- Information retrieval -- Retrieval tasks and goals Information systems -- Information retrieval -- Retrieval tasks and goals -- Document filtering Information systems -- Information retrieval -- Retrieval tasks and goals -- Information extraction Information systems -- Information retrieval -- Retrieval tasks and goals -- Recommender systems Information systems -- Information systems applications Information systems -- Information systems applications -- Data mining Information systems -- Information systems applications -- Data mining -- Collaborative filtering Social and professional topics Social and professional topics -- Professional topics Social and professional topics -- Professional topics -- Computing profession Social and professional topics -- Professional topics -- Computing profession -- Codes of ethics
The 8th Workshop on Responsible Recommendation (FAccTRec 2025) was held in conjunction with the 19th ACM Conference on Recommender Systems in September, 2025 at Prague, Czech Republic, in a hybrid format. This workshop brought together researchers and practitioners to discuss several topics under the banner of social responsibility in recommender systems: fairness, accountability, transparency, privacy, and other ethical and social concerns. It served to advance research and discussion of these topics in the recommender systems space, and incubate ideas for future development and refinement. For 2025, we highlight (1) the increasing importance of pre-trained models in recommendation; and (2) shifting regulatory, organizational, and political landscapes.

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Collaboration types
Industry collaboration
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Web of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
Computer Science, Theory & Methods
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