Nathan Green

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About

Nathan Green is a researcher at the forefront of human-robot interaction, specializing in how robots can ethically and effectively influence human behavior. His work centers on the intersection of persuasive technology, social robotics, and user psychology, exploring how robotic systems can go beyond simple assistance to actively shape user attitudes and actions. Green’s major contribution lies in systematically measuring the nuanced differences between what users say they feel (attitudinal responses) and what they actually do (behavioral responses) when faced with persuasive communication from robots. His most cited paper, "Measuring Users' Attitudinal and Behavioral Responses to Persuasive Communication Techniques in Human Robot Interaction" (2022, 5 citations), provides a foundational framework for evaluating the real-world impact of robotic persuasion. This work is critical for designing robots that can serve as effective tour guides, sales assistants, or health coaches without being manipulative. By bridging the gap between user perception and actual compliance, Green’s research offers essential guidelines for creating socially intelligent robots that are both persuasive and trustworthy—a key step toward integrating robots into daily human environments.