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About

Annika Silvervarg is a leading researcher in human-robot interaction, exploring how people perceive, interpret, and socially engage with robots. Her work centers on folk psychology and mental state attribution, investigating whether humans apply the same intentional stance to robots as they do to other people. Her most-cited paper (143 citations) demonstrates that people rely on shared folk-psychological theories when judging robot behavior, a finding with profound implications for designing socially adept autonomous systems. Silvervarg has made major contributions by moving beyond verbal measures of belief attribution, developing implicit, non-verbal tools to capture how people truly perceive robot minds—work that reveals a persistent anthropocentric bias in human predictions of robot behavior. Her studies on robot gender and persuasiveness (showing that a robot’s voice and appearance do not significantly affect its persuasive power) challenge assumptions about social influence in human-robot interaction. Notably, she has shown that some adults even fail classic false-belief tasks when the agent is a robot, highlighting the unique uncertainties people hold about machine cognition. Her research on embodiment and the uncanny valley with the Furhat robot further clarifies how humanlikeness shapes social responses. With over 250 citations across her portfolio, Silvervarg’s work is essential reading for anyone designing robots that must navigate the complexities of human social cognition.