Student Wins Annual DWJ Award
“I am deeply honored to receive the 2026 Dieter W. Jahns Student Award, and I am very grateful to … the Directors of the Foundation … for this recognition."
Xiaoyun’s project, "Trust and Distrust Spreading in Interconnected Human–AI Teams: An Ergonomics Approach to Analyzing, Designing, and Evaluating Multi-Team Collaboration With AI Agents", investigated the mechanisms of trust and distrust spreading in a Team of Teams structure where two human–AI teams worked together on simulated reconnaissance missions. The goal was to understand how manipulating trust or distrust toward one AI agent in one team affects trust attitudes, coordination patterns and performance not just within that team but also across teams that only interact through communication channels.
The most practically important finding was the dissociation between behavioral coordination and self-reported trust. The manipulation significantly affected trust ratings but did not significantly alter patterns. Even when people reported lower trust, their actual behavioral coordination did not change. For practitioners, this means that survey-based trust monitoring alone will miss whether teams are actually changing their behavior in response to trust concerns. Even more striking: in the Distrust condition, maintaining high trust in the unreliable AI was associated with worse performance. Over-reliance on a malfunctioning AI is an active performance liability, not just a theoretical concern.