Interview with Juba Ziani

Abstract

In his winter meeting tutorial, Juba Ziani presented an overview of recent advancements in the rapidly evolving field of algorithmic fairness. Dr. Ziani is an assistant professor at the School of Industrial and Systems Engineering at Georgia Institute of Technology. His research focuses on the design of markets for data, data privacy, fairness in machine learning and decision-making, and strategic considerations in machine learning. Dr. Ziani's recent work explores the effects that opacity of algorithmic decision-making policies may have on the ability of individuals from different sub-populations to improve. In particular, it introduces a framework which is based on individuals learning about the policy from their peer networks, and demonstrates how information gaps between different sub-populations may result in an increased level of disparity. In an interview after the winter meeting, Dr. Ziani shared some of his thoughts on research on algorithmic fairness.