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About

Joshua Zonca investigates the cognitive and social mechanisms that underpin human interaction, with a particular focus on how these dynamics extend to our relationships with robots and artificial agents. His research centers on the role of reciprocity in shaping trust and social influence, demonstrating that humans are more likely to follow the advice of a robot that has previously taken their own opinions into account. This key finding, published in his most-cited work (26 citations), reveals that reciprocal dynamics—long understood in human-human contexts—are also critical for effective human-robot collaboration. Zonca’s work also explores how uncertainty affects our reliance on others, showing that when information about competence is unavailable, social influence from peers, robots, and computers follows similar patterns. He has developed novel experimental setups to study perceptual and motor adaptation in joint action, and has shown that collaborative physical interaction can bias human attention toward a robot’s hand, mirroring the near-hand effect observed in human dyads. Through these contributions, Zonca is advancing our understanding of how to design more intuitive and trustworthy autonomous systems.