20 citations · 32 across the 4 of their papers we have counts for
4 papers
Adaptive Sampling Strategies to Construct Equitable Training Datasets
William Cai, Ro Encarnacion, Bobbie Chern +4
In domains ranging from computer vision to natural language processing, machine learning models have been shown to exhibit stark disparities, often performing worse for members of…
Two-sided fairness in rankings via Lorenz dominance
Virginie Do, Sam Corbett-Davies, Jamal Atif +1
We consider the problem of generating rankings that are fair towards both users and item producers in recommender systems. We address both usual recommendation (e.g., of music or m…
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems
Chloé Bakalar, Renata Barreto, Stevie Bergman +13
Many technical approaches have been proposed for ensuring that decisions made by machine learning systems are fair, but few of these proposals have been stress-tested in real-world…
A large-scale analysis of racial disparities in police stops across the United States
Emma Pierson, Camelia Simoiu, Jan Overgoor +4
To assess racial disparities in police interactions with the public, we compiled and analyzed a dataset detailing over 60 million state patrol stops conducted in 20 U.S. states bet…