ARTAI: An Evaluation Platform to Assess Societal Risk of Recommender Algorithms
This addresses the need for tools to evaluate societal risks in recommender systems for regulators and researchers, though it is incremental as it builds on existing regulatory and research efforts.
The paper tackles the problem of societal risk from recommender algorithms by introducing ARTAI, an evaluation platform that enables large-scale assessments to identify harmful content distribution patterns and implement regulatory transparency requirements.
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.