ARTAI: An Evaluation Platform to Assess Societal Risk of Recommender Algorithms
Qin Ruan, Jin Xu, Ruihai Dong, Arjumand Younus, Tai Tan Mai, Barry O'Sullivan, Susan Leavy
TL;DR
ARTAI is presented, 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.
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.