Human Factors, Decision Support, and Algorithmic Fairness

In this talk, we present ongoing research on human factors of decision support systems that has consequences from the perspective of algorithmic fairness. We study various settings: a game, face matching, criminal recidivism prediction, and recruitment. In all cases, a decision support system helps a human make a decision. Through a series of user studies, we observe that users must thread a fine line between algorithmic aversion (completely disregarding the algorithmic support) and automation bias (completely disregarding their own judgment), and that this is impacted by interface design choices, onboarding, fairness interventions, and task-level factors. The talk presents joint work with Asia Biega, Marina Estevez-Almenzar, Alessandro Fabbris, Anna Gatzioura, Manuel Portela, Clara Rus, Jorge Saldivar, and David Solans within various research collaborations including Horizon Europe project FINDHR.