问责
赔偿
政府(语言学)
偏爱
执行
公共关系
业务
顺从(心理学)
中心性
芯(光纤)
公共行政
政治学
突出
作者
Naikang Feng,Yanto Chandra
摘要
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 appeal s—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.
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