Stephanie Sturgeon

Papers

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About

Stephanie Sturgeon is a leading voice in human-robot interaction, with a focused expertise in how humans perceive social intelligence in machines. Her most-cited work, "Perception of Social Intelligence in Robots Performing False-Belief Tasks" (2019), is a landmark study that bridges developmental psychology and robotics. In this work, Sturgeon demonstrated that a robot’s ability to pass a classic Theory of Mind (ToM) test—the Sally-Anne false-belief task—significantly enhances human perceptions of its social intelligence and animacy. By using a NAO robot and gathering data through an online survey, she provided empirical evidence that even subtle cognitive cues can shape our social rapport with machines. This contribution is foundational for designing more intuitive and trusted robotic companions. With 19 citations, her research is a key reference for scholars exploring social cognition in artificial agents. Sturgeon’s work not only advances our understanding of human-robot trust but also opens new pathways for robots in education, therapy, and collaborative settings, making her a vital researcher in the evolving dialogue between humans and intelligent systems.