Trust and Anomalies in the Design of Safe Robotic Self-Adaptation

This article investigates trust and anomalies in selfadaptive robotic systems, drawing on interdisciplinary perspectives from engineering, anthropology, and philosophy. We examine how trust is conceptualized and operationalized within technical frameworks, where it is often treated as a calculable property, and contrast this with ethnographic insights that highlight trust as a situated, relational process shaped by human experience and cultural context. Through our fieldwork, we highlight that anomalies-unexpected deviations in robotic or human behavior-can both challenge and foster trust, depending on how they are interpreted and managed. We further discuss that anomalies, often treated as something negative by engineers, can also have a positive connotation. The paper argues that designing safe and trustworthy self-adaptive robots requires not only robust technical mechanisms for anomaly detection and response, but also an appreciation of the social and experiential dimensions of trust in human-robot interaction. We emphasize the value of interdisciplinary collaboration in addressing the complexities of trust and safety in real-world robotic environments.