Blame games: Who is to blame when things go wrong, human or AI?

Understanding responses to AI versus human errors is crucial, as they shape trust, acceptance, and interaction outcomes. This study investigates the emotional dynamics of human-AI interactions by examining how agent identity (human vs. AI) and error severity (low vs. high) influence negative emotional reactions. Using a 2×2 factorial design with 250 participants, the findings reveal that human agents consistently elicit stronger negative emotions than AI agents, regardless of error severity. Moreover, perceived experience moderates this relationship under specific conditions: individuals who view AI less experienced than humans exhibit stronger negative emotions toward human errors, while this effect diminishes when AI is perceived as having higher experience. However, perceived agency does not significantly influence emotional responses. These findings highlight the critical role of agent identity and perceived experience in shaping emotional reactions to errors, providing new insights into the psychological dynamics of human-AI interactions.