Research and application have used human-AI teaming (HAT) as a new paradigm to develop AI systems. HAT recognizes that AI will function as a teammate instead of simply a tool in collaboration with humans. Effective human-AI teams need to be capable of taking advantage of the unique abilities of both humans and AI while overcoming the known challenges and limitations of each member, augmenting human capabilities, and raising joint performance beyond that of either entity. The National AI Research and Strategic Plan 2023 update has recognized that research programs focusing primarily on the independent performance of AI systems generally fail to consider the functionality that AI must provide within the context of dynamic, adaptive, and collaborative teams and calls for further research on human-AI teaming and collaboration. However, there has been debate about whether AI can work as a teammate with humans. The primary concern is that adopting the "teaming" paradigm contradicts the human-centered AI (HCAI) approach, resulting in humans losing control of AI systems. This article further analyzes the HAT paradigm and the debates. Specifically, we elaborate on our proposed conceptual framework of human-AI joint cognitive systems (HAIJCS) and apply it to represent HAT under the HCAI umbrella. We believe that HAIJCS may help adopt HAI while enabling HCAI. The implications and future work for HAIJCS are also discussed. Insights: AI has led to the emergence of a new form of human-machine relationship: human-AI teaming (HAT), a paradigmatic shift in human-AI systems; We must follow a human-centered AI (HCAI) approach when applying HAT as a new design paradigm; We propose a conceptual framework of human-AI joint cognitive systems (HAIJCS) to represent and implement HAT for developing effective human-AI teaming

翻译：研究与应用已将人机协作（HAT）作为开发AI系统的新范式。HAT认为AI将作为团队成员而非简单工具与人类协作。高效的人机团队需能充分利用人类与AI的独特能力，同时克服双方已知的挑战与局限性，增强人类能力，并提升联合绩效至超越任何单一实体。2023年《国家人工智能研究与发展战略规划》更新指出，主要关注AI系统独立性能的研究项目通常未能考虑AI在动态、自适应及协作团队中需提供的功能，并呼吁进一步研究人机协作。然而，关于AI能否作为团队成员与人类协作仍存在争议。主要担忧在于采用"团队协作"范式与以人为中心的AI（HCAI）方法相悖，可能导致人类失去对AI系统的控制。本文进一步分析了HAT范式及上述争议，具体阐述了所提出的人机联合认知系统（HAIJCS）概念框架，并将其应用于HCAI框架下对HAT的表征。我们认为HAIJCS有助于在采纳人机协作的同时实现HCAI。此外，本文还讨论了HAIJCS的启示及未来研究方向。洞见：AI催生了新型人机关系——人机协作（HAT），这是人机系统的范式变革；在将HAT作为新设计范式时，必须遵循以人为中心的AI（HCAI）方法；我们提出人机联合认知系统（HAIJCS）概念框架，以表征并实现HAT，从而开发高效的人机协作。