Harm Matthias Harms

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About

Harm Matthias Harms is a leading researcher in human-robot interaction (HRI), with a primary focus on explainable artificial intelligence (XAI) and its impact on user trust and perception. His most-cited work, "Explain yourself! Effects of Explanations in Human-Robot Interaction" (2022, 23 citations), is a pivotal contribution that explores how robot-generated explanations influence human attitudes, reliability judgments, and trust dynamics. By systematically analyzing the interplay between transparency and user experience, Harms has advanced our understanding of how to design robots that communicate their decision-making processes effectively. His research bridges the gap between technical AI explainability and human-centered robotics, offering practical insights for developing more trustworthy and socially acceptable autonomous systems. Though early in his career, Harms’ work has already shaped discussions on ethical HRI and is frequently referenced in studies on robot transparency and user acceptance. His contributions are particularly notable for their interdisciplinary approach, combining insights from psychology, computer science, and robotics to address fundamental questions about how robots can earn human confidence through explanation.