Elias Naphausen

Papers

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About

Elias Naphausen is a pioneering researcher at the intersection of Human-Robot Interaction (HRI), interaction design, and non-verbal communication. His work fundamentally challenges how we understand and interface with autonomous systems, particularly focusing on making "black box" AI more transparent and intuitive for everyday users. Naphausen's most cited work, "Punishable AI" (2020, 9 citations), introduces a groundbreaking concept: using gradual destructive interaction as a feedback mechanism for robots. This paradigm allows users to communicate displeasure or correct behavior through intuitive, punishment-like actions—a stark departure from traditional programming interfaces. His more recent contribution, "New Design Potentials of Non-mimetic Sonification in Human–Robot Interaction" (2023, 1 citation), expands the sensory vocabulary of HRI by exploring abstract, non-mimetic soundscapes as a means of information transfer. Developed at the Hybrid Things Lab, this work opens new design possibilities for robotic feedback beyond visual or human-like auditory cues. Though early in his career, Naphausen's provocative, user-centered approach is carving a distinct niche, promising to reshape how we teach, correct, and coexist with increasingly complex robotic systems.