Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems

no code implementations • 5 Nov 2019 • Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel

In addition to the theoretical results, we find on multiple datasets -- including a large-scale real-world recommender system -- that the overall system's end-to-end fairness is largely achievable by improving fairness in individual components.

Fairness Recommendation Systems