Researchers at Carnegie Mellon University's Tepper School of Business are investigating how AI can strengthen human teamwork rather than replace team members. Professor Anita Williams Woolley and her colleagues developed COHUMAIN (Collective HUman-MAchine INtelligence), a framework for understanding where AI fits within organizational social psychology. The researchers argue AI should serve as a partner under human direction — facilitating connections and nudging collaboration — rather than acting as a manager or autonomous teammate. They note that while AI excels at tasks like summarizing meetings, it still can't replicate human abilities like reading the mood of a room.

Ph.D. student Allen Brown is exploring the tension between AI's collaborative potential and concerns around psychological safety and privacy. His research found that people feel more vulnerable when they believe an AI system is evaluating them, compared to being evaluated by another human, due to the loss of "mutual assumption of risk." Meanwhile, researcher Zhaohui (Zoey) Jiang is studying how AI transparency affects trust, finding that transparent AI benefits less-skilled users by helping them learn from the system's decision-making rules, while black box AI can actually be more effective for high-ability users, who tend to penalize AI mistakes more harshly when they understand the system's inner workings. Opacity, paradoxically, inflates perceptions of sophistication. The researchers suggest future AI systems may self-adapt their level of transparency to complement individual users' decision-making weaknesses.

Jake Wintermute raises a provocative point about the implications of AI for scientific research. He argues that scientists have traditionally crafted narrative stories around their findings — most of which ultimately turn out to be false — but that the act of writing them up served as a valuable "proof of effort" filter. The fact that a human invested significant time and energy into constructing a coherent story demonstrated at least a baseline level of commitment and care.

With the rise of AI scientists, Wintermute warns that this storytelling filter is effectively gone. AI can generate plausible scientific narratives at scale without the human investment that once acted as a natural quality gate. This observation highlights a deeper concern about the erosion of trust signals in science as AI-generated content becomes indistinguishable from human-authored research.