Human-AI Teaming

Although artificial intelligence (AI) has many potential benefits, it has also been shown to suffer from a number of challenges for successful performance in complex real-world environments such as military operations, including brittleness, perceptual limitations, hidden biases, and lack of a model of causation important for understanding and predicting future events. These limitations mean that AI will remain inadequate for operating on its own in many complex and novel situations for the foreseeable future, and that AI will need to be carefully managed by humans to achieve their desired utility.Human-AI Teaming: State-of-the-Art and Research Needs examines the factors that are relevant to the design and implementation of AI systems with respect to human operations. This report provides an overview of the state of research on human-AI teaming to determine gaps and future research priorities and explores critical human-systems integration issues for achieving optimal performance.Table of ContentsFront MatterSummary1 Introduction2 Human-AI Teaming Methods and Models3 Human-AI Teaming Processes and Effectiveness4 Situation Awareness in Human-AI Teams5 AI Transparency and Explainability6 Human-AI Team Interaction7 Trusting AI Teammates8 Identification and Mitigation of Bias in Human-AI Teams9 Training Human-AI Teams10 HSI Processes and Measures of Human-AI Team Collaboration and Performance11 ConclusionsReferencesAppendixesAppendix A: Committee BiographiesAppendix B: Human-AI Teaming Workshop AgendaAppendix C: Definitions