Niels Diekmann
Papers
2
Total Citations
19
H-Index
2
About
Niels Diekmann is a leading researcher at the intersection of human-robot interaction (HRI) and data privacy, whose work critically examines the privacy risks posed by increasingly autonomous social robots in domestic settings. His research focuses on the fundamental tension between a robot’s utility and a user’s privacy, exploring how design choices—such as default privacy settings—shape user trust and self-disclosure. In his highly cited 2023 paper, "Never Trust Anything That Can Think for Itself," Diekmann demonstrates that users are significantly less willing to share personal information with robots that have lenient, always-on privacy configurations, even when those settings offer greater functionality. This work, with 13 citations, provides empirical evidence for a critical design dilemma. His earlier 2020 paper, "Towards Designing Privacy-Compliant Social Robots," lays the legal and technical groundwork for mitigating privacy implications in private households, earning 6 citations for its systematic analysis. By bridging legal scholarship, technical design, and behavioral science, Diekmann is shaping how next-generation social robots can be built to respect user autonomy and privacy without sacrificing their potential for meaningful interaction.
Research Focus
Key Achievements
Top Papers
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