The effects of artificial intelligence and victims’ deservingness information on citizens’ blame attribution towards administrative errors

Lei Tao, Jinhan Wan and Bo Wen

Public Management Review, 2025, vol. 27, issue 12, 3104-3124

Abstract: This study examines how citizens attribute blame to government authorities for administrative errors made by artificial intelligence (AI) compared to human decision-makers. Based on blame attribution theory, we conducted a vignette-based survey experiment with 1,098 Chinese citizens, revealing that respondents assign less blame for errors caused by AI or AI-assisted decisions. Additionally, disclosing victims’ deservingness information heightened blame attribution. These findings contribute to the literature on administrative accountability, highlighting how citizens respond to AI-related errors and informing the growing use of AI in public sector decision-making.

Date: 2025
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DOI: 10.1080/14719037.2024.2411632

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