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3 Human-AI Teaming Processes and Effectiveness
Pages 19-24

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From page 19...
... Designing an AI system to work well as a teammate increases human-centeredness, based on the results of more than three decades of teamwork literature providing extensive guidance for effective teaming (Wojton et al., 2021)
From page 20...
... . These tasks, including planning and creative idea generation, persuasion and conflict negotiation, and competitions and physiological performances, require different types of team structures, functional roles, and allocations of tasks over the duration of team interactions.
From page 21...
... . The similarity of team mental models and task mental models among team members, as well as their accuracy, directly contributes to effective team processes, which significantly affect overall team performance (DeChurch and Mesmer-Magnus, 2010; Mathieu et al., 2000)
From page 22...
... Much progress has been made toward the creation of AI that understands natural human language; however, natural language processing remains a challenge for human-AI teaming. Moreover, natural language, with all its ambiguities, may not be the language of choice for effective teaming.
From page 23...
... Research is needed on improving team effectiveness in long-term, distributed, and agile human-AI teams, in the areas of team assembly, goal alignment, communication, coordination, social intelligence, and a new human-AI language. Note that these areas also pose challenges for all-human teams, especially in complex environments.
From page 24...
... An effective human-AI team ultimately augments human capabilities and raises performance beyond that of the component entities. Another consideration is for AI to be used to aid teaming in multi-domain systems by acting as a coordinator, orchestrator, or human resource manager (Demir et al., 2018)


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