Bridging Human–AI Interaction and Human–Robot Interaction: Shared Challenges, Converging Futures
Samuel A. Olatunji, Beau G. Schelble, Yayun Tian, Bethany Moss, Joseph B. Lyons, Wendy A. Rogers, X. Jessie Yang, Lionel P. RobertThis panel examines the growing convergence of human–AI interaction (HAI) and human–robot interaction (HRI) as intelligent systems become more autonomous, embodied, and embedded in everyday settings such as healthcare, education, homes, and workplaces. Although HAI and HRI have evolved as distinct fields, the panel argues that shared human factors concerns—such as trust, safety, autonomy, teamwork, situation awareness, evaluation, and responsible deployment—now require greater integration across both domains. Drawing on perspectives from leading researchers and doctoral students, the session explores how embodiment, motion, social cues, and system transparency shape human interaction with AI and robots. It also addresses methodological tensions, including laboratory versus field evaluation and short-term versus longitudinal study, while highlighting implications for ethics, training, and design. Overall, the panel aims to identify common challenges, foster cross-disciplinary collaboration, and outline a research roadmap for human-centered intelligent systems that improve performance, well-being, and quality of life across diverse contexts and sectors.