Losing the hand on the wheel: AI trust, decision delegation, and displacement of responsibility in financial decision-making

PURPOSE: As artificial intelligence (AI) becomes increasingly integrated into financial decision-making, concerns about responsibility attribution in human-AI collaboration have intensified. This study examines how AI trust relates to the displacement of responsibility. METHODS: Drawing on automation trust theory and moral disengagement theory, we propose a mediation model in which decision delegation links AI trust to displacement of responsibility, with perceived anthropomorphism and perceived accountability as contextual moderators. Two scenario-based experiments were conducted to test the proposed framework. RESULTS: The findings show that AI trust has no direct effect on the displacement of responsibility. Instead, it exerts an indirect effect by increasing users' willingness to delegate decision authority to AI systems. Furthermore, perceived anthropomorphism strengthens this indirect effect, whereas perceived accountability weakens it. CONCLUSION: These results suggest that responsibility attenuation in AI-assisted decision-making is primarily driven by behavioral delegation rather than trust itself. The study clarifies the psychological mechanism and boundary conditions linking AI trust to responsibility attribution in human-AI collaboration.