Title: Understanding and Modeling Team Coordination Dynamics Across Varying Levels of Complexity

Presenter: Associate Professor, Department of Psychology, Georgia Institute of Technology
drupal.psychology.gatech.edu/jamie-gorman

Abstract: Rapid expansion and specialization of knowledge and skills increasingly demands teamwork in domains such as problem solving, command-and-control, and healthcare. Because teamwork is coordinated not just within people (individual cognitive, physiological, and motor systems), understanding and modeling teamwork requires an understanding of how patterns develop between people through interaction (team cognition, team coordination dynamics). This talk will focus on how we can understand and model team coordination dynamics under increasing levels of cognitive and behavioral complexity. A central feature of this approach is the claim that although team coordination dynamics are constrained by the knowledge, skills, and structure of the interacting agents, they are not reducible to these parts, and they are not materialistic (rather, they are dynamic). The organizing principle of increasing dynamic complexity will serve as a guideline for understanding and modeling teamwork ranging from simple rhythmic tasks (e.g., team rowing) to complex team tasks with more requisite variety (e.g., interplanetary exploration). Models and metrics will be presented in the context of research on all-human and human-AI teams, with emphasis on the need for real-time methods to analyze and visualize these dynamics. Limitations will also be discussed.

Bio: Jamie C. Gorman is an associate professor of Engineering Psychology at Georgia Tech. Jamie’s research on human performance in complex sociotechnical settings, including medical, sports, and military teams, focuses on understanding and modeling teamwork and human-technology interaction using dynamical systems theory, computational modeling, and real-time methods. His research incorporates communication analysis, perceptual-motor coordination, neurophysiology, and dynamical systems modeling for understanding coordination and complexity in all-human and human-AI teaming. This research has been funded by AFOSR, AFRL, ARL, DARPA, ONR, and NSF. Jamie is a member of the Human Factors and Ergonomics Society, serves on the HFES Evaluation subcommittee, and coordinates the HFES Student Chapter at Georgia Tech. He serves on the editorial boards of Human Factors and the Journal of Experimental Psychology: Applied. Since 2020, Jamie has been a member of the Institute for Student-AI Teaming at CU Boulder.