ARTAI: an evaluation platform to assess societal risk of recommender algorithms
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Published Version
Date
2024
Authors
Ruan, Qin
Xu, Jin
Dong, Ruihai
Younus, Arjumand
Mai, Tai Tan
O’Sullivan, Barry
Leavy, Susan
Journal Title
Journal ISSN
Volume Title
Publisher
arXiv
Published Version
Abstract
Societal risk emanating from how recommender algorithms disseminate content online is now well documented. Emergent regulation aims to mitigate this risk through ethical audits and enabling new research on the social impact of algorithms. However, there is currently a need for tools and methods that enable such evaluation. This paper presents ARTAI, an evaluation environment that enables large-scale assessments of recommender algorithms to identify harmful patterns in how content is distributed online and enables the implementation of new regulatory requirements for increased transparency in recommender systems.
Description
Keywords
Recommender algorithms , Societal risk evaluation , Simulation system
Citation
Ruan, Q., Xu, J., Dong, R., Younus, A., Mai, T.T., O’Sullivan, B. and Leavy, S. (2024) ‘Artai: an evaluation platform to assess societal risk of recommender algorithms’. arXiv. https://doi.org/10.48550/ARXIV.2409.12396