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. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
| Original language | English |
|---|---|
| Pages (from-to) | 3104–3124 |
| Number of pages | 21 |
| Journal | Public Management Review |
| Volume | 27 |
| Issue number | 12 |
| Online published | 7 Oct 2024 |
| DOIs | |
| Publication status | Published - Dec 2025 |
Funding
This work was generously supported by the National Natural Science Foundation of China under Grant Number [72004189], by Dean’s Research Fund of the Education University of Hong Kong under Grant Number [FLASS/DRF/IRS-8], by Start-up Grant of the Education University of Hong Kong under Grant Number [RG 41/2023-2024R], and by the University of Macau’s Start-up Research Grant (SRG) under Grant Number [SRG2024-00005-FSS].
Research Keywords
- administrative accountability
- administrative errors
- Artificial intelligence
- blame attribution patterns
- victims’ deservingness information
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