This paper offers a conceptual analysis of the transformative role of Artificial Intelligence (AI) in urban governance, focusing on how AI can reshape the relationship between bureaucratic discretion and accountability. Drawing on public administration theory and algorithmic governance research, the study argues that AI does not simply restrict or enhance discretion but redistributes it across institutional levels, professional roles, and citizen interactions. While primarily conceptual, this paper uses illustrative cases to show that AI can strengthen managerial oversight, improve service delivery consistency, and expand citizen access to information. These changes affect different forms of accountability: political, professional, and participatory, while introducing new risks, such as data bias, algorithmic opacity, and fragmented responsibility across actors. In response, the paper introduces the concept of accountable discretion and proposes guiding principles, each linked to actionable measures: equal AI access, adaptive administrative structures, robust data governance, proactive human-led decision-making, and citizen-engaged oversight. This study contributes to the AI governance literature by moving beyond narrow concerns with perceived discretion at the street level, highlighting instead how AI transforms rule-based discretion across governance systems. It also reframes the trade-off between discretion and accountability as a dynamic and evolving relationship shaped by algorithmic systems and institutional practices.

翻译：本文对人工智能在城市治理中的变革性作用进行了概念性分析，重点探讨人工智能如何重塑官僚自由裁量权与问责之间的关系。借鉴公共行政理论和算法治理研究，本研究认为，人工智能并非简单地限制或增强自由裁量权，而是将其重新分配于制度层级、专业角色和公民互动之间。尽管主要是概念性的，本文通过例证性案例表明，人工智能能够加强管理监督、提高服务提供的一致性并扩大公民获取信息的渠道。这些变化影响着不同形式的问责：政治问责、专业问责和参与式问责，同时也引入了新的风险，如数据偏见、算法不透明以及各行为体之间的责任碎片化。对此，本文引入了“可问责的自由裁量权”这一概念，并提出了指导原则，每项原则都与可操作的措施相关联：平等的人工智能接入、适应性的行政结构、稳健的数据治理、积极主动的人为主导决策以及公民参与的监督。本研究通过超越对基层感知自由裁量权的狭隘关注，转而强调人工智能如何在整个治理系统中变革基于规则的自由裁量权，从而为人工智能治理文献做出了贡献。它还将自由裁量权与问责之间的权衡重新构建为一种由算法系统和制度实践塑造的动态且不断演进的关系。