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

Lei TAO, Jinhan WAN, Bo WEN

Research output: Contribution to journalArticlespeer-review

1 Citation (Scopus)

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. Copyright © 2024 Informa UK Limited, trading as Taylor & Francis Group.

Original languageEnglish
JournalPublic Management Review
Early online dateOct 2024
DOIs
Publication statusE-pub ahead of print - Oct 2024

Citation

Tao, L., Wan, J., & Wen, B. (2024). The effects of artificial intelligence and victims’ deservingness information on citizens’ blame attribution towards administrative errors. Public Management Review. Advance online publication. https://doi.org/10.1080/14719037.2024.2411632

Keywords

  • Artificial intelligence
  • Blame attribution patterns
  • Administrative errors
  • Victims’ deservingness information
  • Administrative accountability

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