Bridging the Gap Between Human and AI Teams

Human and artificial intelligence teams are now stepping into real‑world, high‑stakes jobs. Yet the research on how they work together is scattered across many fields and uses different ideas, making it hard to build a clear picture. Because of this split, we struggle to link what we know about humans and AI with what we learn from human‑robot teams. Robots bring new challenges, such as needing to coordinate closely, manage their own autonomy, keep the team talking, and stay safe while interacting. This review looks at all those areas, pulling together studies from different domains to see what factors matter most for teamwork.

It asks which skills help humans and AI coordinate better, how decision control is shared, what communication styles keep the team on track, and how safety concerns are addressed. The authors suggest that learning from human‑robot interaction can improve AI teamwork, and vice versa, because both involve embodied partners that must act together in real time. They also point out that many studies still use lab‑style testbeds, which may not capture the pressures of real life. Shifting focus to applied settings can reveal new insights into trust, workload sharing, and error handling. Future research should aim for a unified framework that combines findings from both human‑AI and human‑robot teams, helping designers build systems that fit naturally into complex workplaces.

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