Abstract
We provide a transdisciplinary viewpoint on creating artificial social intelligence for human-agent teaming. We discuss theoretical, methodological, and technological insights, drawn from different disciplines, to more fully illuminate how cross-disciplinary research can inform research design and development. We unite ideas spanning human factors, cognitive and computer science, and organizational behavior. Grounding our ideas in real world challenges for human-AI teaming, and via a series of questions designed to facilitate synthesis across disciplines, we illustrate how transdisciplinary team science more effectively asks and answers complex questions on human-agent teaming. Our objective is to contribute to research and development in the field of human-AI and human-robot teaming by emphasizing a more human-centered perspective on AI.
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