Papers
1
Total Citations
13
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1
About
Carlie See is a rising scholar in human–robot teaming (HRT), with a focused interest in how individual differences shape trust in autonomous systems. Her most-cited work, "Trust in the Danger Zone: Individual Differences in Confidence in Robot Threat Assessments" (2022, 13 citations), explores the psychological dynamics that influence human reliance on intelligent machines in high-stakes environments. By examining how traits like social agency perception and system incomprehensibility affect operator trust, See has contributed critical insights to the design of safer, more effective human–robot collaborations. Her research bridges cognitive psychology and robotics, addressing the urgent need for trust calibration in threat-assessment scenarios. Though early in her career, See’s work has already drawn attention for its practical implications in defense and emergency response contexts. Her findings challenge assumptions about uniform trust in automation, highlighting the variability in human confidence that can make or break team performance. For students and researchers, See’s research offers a compelling lens into the human factors that will define the next generation of autonomous systems.
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