Thomas MacGillivray

Papers

Total Citations

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About

Thomas MacGillivray is a leading researcher in human-robot interaction (HRI), with a particular focus on the psychological and experiential factors that shape how people trust and collaborate with robotic agents. His most-cited work, "Trust and Prior Experience in Human-Robot Interaction" (2017, 54 citations), experimentally demonstrates that users with prior interaction experience exhibit higher trust scores and more nuanced trust calibration when observing a robot perform tasks. This foundational contribution has helped shift the field toward understanding trust as a dynamic, experience-driven process rather than a static attitude. MacGillivray’s research bridges cognitive science and robotics, offering practical insights for designing robots that earn and maintain user trust over time. His work is widely referenced in studies on human-robot teamwork, assistive robotics, and autonomous systems. By illuminating how past encounters shape future cooperation, MacGillivray has provided a critical framework for developing more intuitive and socially aware robotic technologies, making his contributions essential reading for students and researchers exploring the human side of intelligent machines.