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Research Agenda of Ethical Recommender Systems based on Explainable AI.

Authors :
Guttmann, Mike
Ge, Mouzhi
Source :
Procedia Computer Science; 2024, Vol. 238, p328-335, 8p
Publication Year :
2024

Abstract

In the digital era, recommender systems (RS) have become an integral part of our daily interactions, exerting a significant impact on users and society. However, this also raises ethical challenges related to RS that should be considered. Addressing these challenges requires the application of explainable artificial intelligence (XAI) models to make RS more understandable. Based on the current state-of-the-art literature, this paper aims to provide a comprehensive overview of XAI for RS and its ethical implications, with the aim of proposing a research agenda for ethical RS based on XAI. The findings of the literature review show that neural network-based RS have received much attention in terms of offering explanations, while there is a research gap in explaining context-based RS and in evaluating explanations. In addition, a set of ethical challenges for RS are discussed by exploring how explanations for recommendations can contribute to the ethical use of RS. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
238
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
178317961
Full Text :
https://doi.org/10.1016/j.procs.2024.06.032