NORMalize 2025: The Third Workshop on Normative Design and Evaluation of Recommender Systems

  • Lien Michiels
  • , Sanne Vrijenhoek
  • , Alain D. Starke
  • , Johannes Kruse
  • , Savvina Daniil

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Recommender systems are one of the most widely used applications of artificial intelligence. Their use can have far-reaching consequences for stakeholders, users, and society at large. In this third edition of the NORMalize workshop, we once again seek to advance the research agenda of normative thinking, considering the norms and values that underpin recommender systems, as well as to introduce the concept to a broader audience. We aim to bring together a growing community of researchers and practitioners across disciplines who want to think about the norms and values that should be considered in the design and evaluation of recommender systems, and to further educate them on how to reflect on, prioritise, and operationalise such norms and values. NORMalize 2025 is a half-day workshop focusing on discussion and interdisciplinary collaboration, building upon its two successful runs at previous RecSys conferences in 2023 and 2024.
Original languageEnglish
Title of host publicationProceedings of the Nineteenth ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery
Publication date2025
Pages1386-1388
ISBN (Print)979-8-4007-1364-4
DOIs
Publication statusPublished - 2025
EventNineteenth ACM Conference on Recommender Systems - Universum Convention Center, Prague , Czech Republic
Duration: 22 Sept 202526 Sept 2025

Conference

ConferenceNineteenth ACM Conference on Recommender Systems
LocationUniversum Convention Center
Country/TerritoryCzech Republic
CityPrague
Period22/09/202526/09/2025

Keywords

  • Normative design
  • Normative thinking
  • Norms
  • Value-sensitive design
  • Values

Fingerprint

Dive into the research topics of 'NORMalize 2025: The Third Workshop on Normative Design and Evaluation of Recommender Systems'. Together they form a unique fingerprint.

Cite this