{"type":"ScholarlyArticle","title":"Transforming Recommender Systems: Balancing Personalization, Fairness, and Human Values","authors":[{"name":"Julia Neidhardt","slug":"julia-neidhardt","given":"Julia","family":"Neidhardt","affiliation":"CD Lab for Recommender Systems , TU Wien , Austria"}],"abstract":"Recent advancements in recommender systems highlight the importance of metrics beyond accuracy, including diversity, serendipity, and fairness. This paper discusses various aspects of modern recommender systems, focusing on challenges such as preference elicitation, the complexity of human decision-making, and multi-domain applicability. The integration of Generative AI and Large Language Models offers enhanced personalization capabilities but also raises concerns regarding transparency and fairness. This work examines ongoing research efforts aimed at developing transparent, fair, and contextually aware systems. Our approach seeks to prioritize user wellbeing and responsibility, contributing to a more equitable and functional digital environment through advanced technologies and interdisciplinary insights.","doi":"10.24963/ijcai.2024/982","url":"https://ijcai.org/proceedings/2024/982","pdf":"https://ijcai.org/proceedings/2024/0982.pdf","markdown":"https://ijcai.org/proceedings/2024/982.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/982","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Early Career","track":"Early Career","number":982,"pages":{"first":8559,"last":8564},"keywords":["Data Mining: DM: Recommender systems","AI Ethics, Trust, Fairness: ETF: Societal impact of AI","Humans and AI: HAI: Personalization and user modeling","AI Ethics, Trust, Fairness: ETF: Fairness and diversity"],"videos":[],"references":[{"position":1,"raw":"[Aayesha et al., 2024] Aayesha Aayesha, Muhammad Afzaal, and Julia Neidhardt. 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