''AI is a friend, a teammate, not a supervisor'': Understanding Human Perceptions of AI teammates' Monitoring in Human-AI Teams

Artificial Intelligence (AI)-mediated collaboration has been a core research interest in CSCW and HCI in recent decades. AI is being embedded in teams as a teammate, known as human-AI teamwork. A critical aspect to this and any type of teamwork is monitoring: the ability to track and be aware of both team- and individual-level actions. As AI continuously evolves from a passive tool into a supportive collaborator capable of playing a role in teams, more research is needed to investigate human perceptions of AI teammates' monitoring. More work is needed on when and how AI can function as a supportive collaborator rather than a surveillant (in regard to monitoring) to enhance team coordination and performance. Drawing on 22 interviews, we examined how humans perceive AI monitoring when AI behaves as a collaborative teammate for team support, focusing on perceptions of AI monitoring at both team and individual levels. Four tensions have been identified, namely: performance versus privacy, support versus control, fairness versus empathy, and team-level and individual-level trade-offs. We also propose feasible design principles for human-AI teaming designers to optimize AI monitoring for effective team support, maximizing its unique advantages while mitigating potential risks, further cultivating more effective and trustworthy human-AI collaboration.