张洪谋
摘 要：随着智慧城市建设的不断发展，许多城市进行了多部门、长周期、大尺度的基础数据积累、整合和数据平台建设，但很大程度上仍停留在“重数据、轻算法”“重平台、轻应用”的阶段。基于城市智能治理和智慧城市的理论与案例分析，我们提出应当将城市数据，特别是城市实时大数据作为城市治理中的“传感器”，将城市政策在各部门中的作用结果通过实时数据进行建模、计算、求解和政策效果评估，进而反馈进入下一阶段的政策制定过程当中，并将这一过程“算法化”和“自动化”，即形成数字治理的“闭环”。在本文中，我们介绍阿姆斯特丹、内罗毕和三亚三个城市在城市环境治理、公共基础设施和政务便民服务三个领域实现城市智能治理闭环的例子，并通过统计学中的贝叶斯学派的观点来阐释这一闭环形成的政策逻辑。本文还将讨论这一政策过程的范式性转变在实践中可能存在的风险及其理论解释。
关键词：城市智能治理，智慧城市，城市感知，反馈，闭环，贝叶斯
【作者】 张洪谋，北京大学政府管理学院助理教授，北京大学公共治理研究所研究员。
【Title】Sensing, Feedback, and Closed-Loops in Urban Intelligent Governance
Abstract: With the development of smart city governance, many cities have accumulated and integrated multi-departmental, long-term, and large-scale urban data, alongside with their data platforms. However, these cities are still largely at the stage of “data more than algorithms,” and “platforms more than applications.” Based the theoretical and empirical analysis of urban intelligent and smart governance, we propose 1) to consider these real-time urban data as the “sensors” in urban governance, 2) to assess urban policies through modeling, calculating, and evaluating these real-time data, and 3) eventually by “algorithmizing” and “automating” the process, to form the “closed loop” of urban intelligent governance. In this article, we introduce and analyze three cases of urban environmental governance, public infrastructure provision, and civic service responses in Amsterdam, Nairobi, and Sanya, respective, to illustrate how the “closed loops” of urban intelligent governance might be like. We employ the Bayesian perspectives in statistics to explain the policy logic of the closed loops. At the end of the article, we also discuss the potential risks and possible theoretical explanations of this urban policy’s paradigm shift.
Key words: Urban intelligent governance, Smart city, Urban sensing, Feedback, Closed-Loop, Bayesian