Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems,...

Fairness in machine learning is often conceptualized narrowly in comparative, distributional terms. In studying stakeholders' concepts of fairness, we find that this framing is insufficient to capture...

Simulator for MOdular Recommendation EcoSystems. Contribute to that-recsys-lab/smores development by creating an account on GitHub.

Simulator for MOdular Recommendation EcoSystems. Contribute to that-recsys-lab/smores development by creating an account on GitHub.

Optimizing outcomes for multiple stakeholders in recommender systems has historically focused on algorithmic interventions, such as developing multi-objective models or re-ranking results from existin...

YouTube video by Casey Fiesler