Speaker: Dr. Josephine Moritz

Abstract: This paper focuses on the development of the fairness-by-perception paradigm to explain how individuals evaluate the fairness of algorithmic decision-making (ADM). While prior research has emphasized fairness-by-design, focusing on mathematical criteria, we argue that fairness emerges from subjective perceptions impacted by system design, contextual conditions, and individual characteristics. However, existing findings on ADM fairness perceptions remain highly fragmented, with inconsistent results, isolated boundary conditions, and limited conceptual integration, hindering cumulative theory development. To address these gaps, we draw on fairness heuristic theory and conceptualize fairness as a process in which individuals form initial fairness judgments that subsequently guide behavior. We establish an empirical foundation through a meta-analysis comprising two studies: Study I compares ADM against human decision-making with decision context, human involvement, and country as boundary conditions, and Study II examines variation in design choices (transparency, anthropomorphism, task type). In doing so, we advance theory by integrating fragmented findings into the fairness-by-perception paradigm.

Short Bio: Josephine Moritz is a PostDoc at the Chair of Information Systems and Business Process Management, University of Münster. Her research focuses on reactions to algorithmic decision-making in organizations and algorithmic management in both gig- and non-gig organizations. Prior to her current role, Josephine completed her PhD at the Heinrich Heine University in Düsseldorf, where she researched boundary conditions of reactions to AI implementation in organizational contexts.