Fairness, Rankings, and Behavioral Biases

This course aims to explore the interaction between human behavioral biases and ranking processes in the context of fairness and equity. By building formal models of these biases, participants will learn how to identify interventions that can mitigate bias and improve performance. The course covers topics such as mental models, building mathematical models, evaluating outcomes, obstacles to diversity, and the impact of interventions like the Rooney Rule. The teaching method involves lectures, discussions, and formalization of concepts. This course is intended for individuals interested in algorithmic fairness, bias mitigation, and decision-making processes in screening and ranking scenarios.