Trusting Security Robotic Authority: The Impact of Interactional and Distributive Fairness

The growing deployment of autonomous security robots has raised critical questions about how people trust and accept robotic systems exercising public authority. Yet fairness, a central mechanism in public responses to human authority, has received limited attention in the context of robotic authority. Drawing on fairness theory from policing research, this study examines how interactional fairness and distributive fairness influence trust and acceptance of security robots. Using a 2 × 2 between-subjects experiment with 100 U.S. participants, we found that both interactional and distributive fairness significantly increased trust, whereas only interactional fairness significantly increased acceptance. These findings suggest that fairness serves as a critical mechanism shaping public responses to robotic authority. This research extends fairness theory to human-security robot interaction and highlights the importance of clear explanations and consistent rule enforcement for building public trust and acceptance.