Distinct brain mechanisms support trust violations, belief integration, and bias in human-AI teams

Abstract

This study provides an integrated electrophysiological and behavioral account of the neuro-cognitive markers underlying trust evolution during human interaction with artificial intelligence (AI). Trust is essential for effective collaboration and plays a key role in realizing the benefits of human–AI teaming in information-rich and decision-critical contexts. Using electroencephalography (EEG), we identified neural signatures of dynamic shifts in human trust during a face classification task involving an AI agent. Viewing the AI’s classification elicited an N2–P3a–P3b event-related potential (ERP) complex that was sensitive to agreement with the participant’s own judgment and modulated by individual response biases. In addition, we observed a centro-parietal positivity (CPP) prior to participants’ responses, and found that ongoing EEG activity in this time window co-varied with subsequent changes in AI trust ratings. These neural effects showed substantial individual variability, indicating the use of diverse metacognitive strategies. Together, these findings suggest that trust in AI is shaped by internal confidence signals and evaluative processing of feedback.