Decision making with fair ranking

Abstract and Figures

Ranking is a responsible process because it involves working with sensitive attributes that can discriminate alternatives. Due to the availability of a large amount of data for automated processing, ranking is increasingly in use in decision making. Therefore, concepts of algorithmic fairness in the field of classification in machine learning find their place in fair ranking methods. This paper provides an overview of fair ranking terms, fair ranking challenges, and fair ranking algorithms from the state-of-the-art literature.