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Presented By: U-M Industrial & Operations Engineering

899 Seminar Series: Jamie Gorman, Arizona State University

A Generalizable Approach for Measuring Coordination Dynamics and Performance in Human-Autonomy Teams

Seminar Seminar
 Kenny Eliason on Unsplash
Bio: Dr. Jamie C. Gorman, Ph.D. is a Professor in Human Systems Engineering and Deputy Director of the Center for Human Artificial Intelligence and Robot Teaming (CHART) at Arizona State University and Senior Research Personnel with the NSF Institute for Student-AI Teaming at the University of Colorado. Dr. Gorman’s research focuses on dynamical systems and computational models of team coordination. His research is conducted in complex sociotechnical environments, including medical, space, military, educational, and sports settings, focusing on building generalizable models, metrics, and measurement systems. Dr. Gorman’s research has been funded by DoD, NSF, and industry partners. He is a member of the Human Factors and Ergonomics Society and serves on the editorial boards of Human Factors and the Journal of Experimental Psychology: Applied.

Abstract: Human-autonomy teams operating in dynamic (“perturbed”) environments primarily interact across human and machine elements. However, most measurements are subjective, involving observer ratings and survey responses (e.g., trust; influence; autonomy), and there is a need for theoretically grounded, objective, and metrics of real-time human-machine coordination states. This talk presents generalizable objective measurement systems for measuring the dynamic spread of trust and distrust through influence, quantifying team resilience to automation and autonomy failures, and AI-supported collaborative learning in K -12 education. The practical deployment of measurement frameworks in dashboards and machine learning agents will be discussed.

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