Jeffrey T. Hancock
Papers
5
Total Citations
198
H-Index
5
About
Jeffrey T. Hancock is a leading scholar in human-robot interaction, with a focus on how people perceive and respond to social robots. His research integrates social psychology and communication theory to explore the nuanced ways humans form impressions of robotic agents. A central contribution is his application of the Stereotype Content Model to robotics, demonstrating that people judge robots along dimensions of warmth and competence, much like they judge other humans. This framework, detailed in his highly cited 2019 and 2020 works, reveals that first impressions of robots are systematic and can lead to stereotyping. Hancock’s work is particularly impactful for its attention to vulnerable populations, such as older adults in rural China, where he examines cultural and resource-specific concerns about robotic care. His 2021 study on Chinese elders’ perceptions has garnered 64 citations, underscoring its relevance to aging societies. More recently, he has identified the “presumed allo-enhancement effect,” a bias where people believe robots are more beneficial for others than themselves. With over 200 citations across his top papers, Hancock’s research is essential reading for anyone interested in the social dynamics of human-robot interaction and the ethical deployment of assistive technologies.
Research Focus
Key Achievements
Top Papers
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