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About

Debora Zanatto is a prominent researcher specializing in human-robot interaction (HRI), trust, and social cognition, with a particular focus on how people perceive, relate to, and cooperate with artificial agents. Her work has made significant contributions to our understanding of the psychological mechanisms that underpin human acceptance of robots and AI systems. Zanatto's most influential contribution, "Trust in Artificial Voices" (2018, 70 citations), examined the critical role of trust in human-machine communication, establishing foundational principles for designing machines that elicit reliable and productive interactions. Complementing this, her research on Theory of Mind (ToM) in HRI — explored across multiple studies accumulating nearly 65 citations — revealed how attributing mental states to robots meaningfully shapes trust and cooperation dynamics. A recurring theme in her work is anthropomorphism: her studies on how humanlike characteristics enhance robot credibility and whether those perceptions generalize to non-humanlike robots have garnered considerable attention (57+ citations combined). Her investigations into cooperation with robotic peers further illuminate the social and situational factors governing human willingness to engage with artificial agents. With over 260 total citations, Zanatto's research offers valuable insights for roboticists, psychologists, and designers working to build more trustworthy, socially intelligent machines.