Holding AI Accountable Like Herding Cats: The Contingent Impact on the Legitimacy of Algorithmic Bureaucracy
通过三个调查实验（1135名中国参与者），发现AI问责在决策给公民带来损失时对合法性感知最关键，而有效性在结果积极时更重要，且两者交互作用也取决于决策结果。
ABSTRACT The rise of artificial intelligence in public decision‐making is reshaping state legitimacy by shifting administrative discretion from human bureaucracies to algorithmic systems. While research has explored AI accountability and legitimacy deficits, how they are related across different decision contexts remains unclear. Drawing on bureaucratic legitimacy, procedural fairness, and forum drifting theories, this study examines how AI accountability and effectiveness shape legitimacy perceptions, depending on decision outcomes. Using three survey experiments with 1135 participants in China, we find that accountability is most crucial when AI decisions introduce losses to citizens, whereas effectiveness plays a greater role when outcomes are positive to them. Additionally, the interaction effects between AI accountability and effectiveness are also contingent on decision outcomes. These findings advance AI governance research by highlighting the conditions under which algorithmic legitimacy is strengthened or weakened, emphasizing the need for tailored accountability and effectiveness strategies based on decision outcomes.