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Accountability in Government Use of AI: Citizen Concerns and Preferences

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Abstract

Government adoption of AI opens the “pandora's box” of accountability, a core aspect of public value. Despite the centrality of governmental AI accountability, citizens' concerns and preferences in holding governments accountable for AI usage remain poorly understood. To address these puzzles and advance knowledge on AI accountability in non-Western democracies, we conducted a mixed-method study using data collected from Chinese citizens. A story-completion study (N = 50) suggested concerns over AI's incompetence, inadequate human oversight, algorithmic opacity, and weak accountability enforcement leading to harmful outcomes. A discrete-choice experiment (N = 2080) that measured preferences toward four algorithmic accountability—procurement clauses, transparency, auditing, and appeals—supported all hypotheses. Results showed a preference toward systems with accountability clauses over those without, ecosystem-level over technical transparency, and internal over external auditing. Reactive redress using administrative appeals for AI errors was valued. This study advances knowledge on algorithmic accountability and insights to enhance public trust in government AI use. © 2025 The Author(s). Public Administration published by John Wiley & Sons Ltd.
Translated title of the contribution政府人工智能应用的问责问题: 公众关切与偏好
Original languageEnglish
Number of pages22
JournalPublic Administration
Online published30 Oct 2025
DOIs
Publication statusOnline published - 30 Oct 2025

Funding

The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (project no.: CityU 15513723).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions

Research Keywords

  • AI
  • algorithmic accountability
  • artificial intelligence
  • experiment
  • public value

RGC Funding Information

  • RGC-funded

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