  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
