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This lecture explores the impact of task load on team performance in decision referrals within human-automation teams. Dr. Kesav Kaza, Research Fellow at the University of Ottawa, presents a comprehensive analysis of how human factors affect systems with humans in the loop. Learn about optimal decision referrals in human-automation teams performing binary classification tasks, with particular focus on how human performance degrades under increasing task load. The presentation introduces a stochastic optimization model for determining which tasks to refer to human operators, demonstrating that it's optimal to myopically refer tasks yielding the largest reduction in expected cost. Discover the practical applications of this framework to counter-drone surveillance through field experiment results, and explore open problems in this emerging domain. The talk combines theoretical frameworks with experimental studies involving human participants to provide insights into effective human-AI collaboration strategies.
