Klaas Degkwitz

Papers

Total Citations

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About

Klaas Degkwitz is a rising researcher at the forefront of explainable artificial intelligence (XAI) and human-robot interaction (HRI). His work centers on a critical question: how do robots’ explanations shape human trust, perception, and collaboration? In his most-cited paper, “Explain yourself! Effects of Explanations in Human-Robot Interaction” (2022, 23 citations), Degkwitz investigates how transparent robot decision-making can transform user attitudes—boosting perceived reliability and trustworthiness while also revealing potential pitfalls in overly complex or anthropomorphic explanations. This contribution is foundational for designing socially intelligent robots that communicate effectively with non-expert users. Though early in his career, Degkwitz’s research bridges cognitive science, robotics, and human factors, offering practical insights for autonomous systems in healthcare, service, and manufacturing. His work has been presented at leading HRI venues and is gaining traction among engineers and ethicists alike. For students and researchers exploring the human side of AI, Degkwitz provides a compelling case for why “explainability” is not just a technical feature but a cornerstone of meaningful human-robot relationships.