2 citations · 3 across the 2 of their papers we have counts for
5 papers
Fair ranking: a critical review, challenges, and future directions
Gourab K Patro, Lorenzo Porcaro, Laura Mitchell +3
Ranking, recommendation, and retrieval systems are widely used in online platforms and other societal systems, including e-commerce, media-streaming, admissions, gig platforms, and…
A Note on the Significance Adjustment for FA*IR with Two Protected Groups
Meike Zehlike, Tom Sühr, Carlos Castillo
In this report we provide an improvement of the significance adjustment from the FA*IR algorithm of Zehlike et al., which did not work for very short rankings in combination with a…
Towards a Flexible Framework for Algorithmic Fairness
Philip Hacker, Emil Wiedemann, Meike Zehlike
Increasingly, scholars seek to integrate legal and technological insights to combat bias in AI systems. In recent years, many different definitions for ensuring non-discrimination…
FairSearch: A Tool For Fairness in Ranked Search Results
Meike Zehlike, Tom Sühr, Carlos Castillo +1
Ranked search results and recommendations have become the main mechanism by which we find content, products, places, and people online. With hiring, selecting, purchasing, and dati…
Reducing Disparate Exposure in Ranking: A Learning To Rank Approach
Meike Zehlike, Carlos Castillo
Ranked search results have become the main mechanism by which we find content, products, places, and people online. Thus their ordering contributes not only to the satisfaction of…