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.
ABSTRACT
通过将行政裁量权从人类科层机构转移到算法系统，人工智能在公共决策中的兴起重塑着行政国家的合法性。尽管既有研究已探讨了AI问责与合法性缺失的问题，但二者在不同决策情境中的关系仍不明确。研究结合科层合法性理论、程序公平理论和问责方漂移理论，考察了AI问责与有效性如何影响公众的合法性感知，并分析这种影响是否取决于决策结果。通过对中国1135名研究参与者开展的三项调查实验分析，研究发现：当AI决策为公民带来消极结果时，问责最为关键；而当AI决策为公民带来积极结果时，有效性则更为重要。此外，AI问责与有效性之间的交互效应同样因决策结果而异。上述发现通过揭示算法合法性在何种条件下得以强化或削弱，推进了AI治理研究；并强调有必要依据决策结果制定差异化的问责与有效性策略。