'Human-AI Teaming: Review of the NAS Report
Open Access
Article
Conference Proceedings
Authors: Ryan Quandt
Abstract
Human-machine teams offer possibilities for conceptualization and action that could be achieved by neither alone. “Human-AI Teaming,” a recent report by the National Academies of Sciences observed that teams are not reducible to their aggregation: their individual performance does not entail successful team performance. The present paper selectively reviews the report and argues that their observation supports the development of a mathematical, behavioural, and physical model of human-machine teaming as a first, essential step toward integrating AI. Joint trade-offs between structural fitness and performance underlies such a model.
Keywords: Human, Machine Systems, Models, Teams, Uncertainty, Bias
DOI: 10.54941/ahfe1003758
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