华东师范大学(哲学社会科学版) ›› 2019, Vol. 51 ›› Issue (5): 53-59.doi: 10.16382/j.cnki.1000-5579.2019.05.006

• 城市治理与发展 • 上一篇    下一篇

大数据技术条件下的城市治理:数据规训及其反思

胡键   

  1. 上海社会科学院软实力研究中心 上海, 200020
  • 出版日期:2019-09-15 发布日期:2019-09-24
  • 作者简介:胡键,上海社会科学院软实力研究中心研究员、博士生导师(上海,200020)。

Data Discipline in Urban Governance under the Condition of Big Data Technology

HU Jian   

  • Online:2019-09-15 Published:2019-09-24

摘要: 城市治理在于构建一种良好的秩序,而构建城市秩序即秩序规训的方式与经济发展水平直接相关。最初的秩序规训是道德规训,其次是行为规训,再次是法制规训。即便是法制规训也由于受法制制定者主观因素的影响而难以达到有效规训的目的,但技术的进步则可以弥补这种缺陷。大数据技术用于城市治理的实践中就是采取数据规训的方式来成功实现城市的秩序规训。技术自古以来对人类而言就是一把双刃剑,在为人类的发展提供便捷服务的同时,也会因人类不同成员的私利而对人类产生危害。这就是技术的异化现象。大数据为构建一个有序的城市发挥着积极的作用,正是大数据的数据规训功能使城市环境处于一种"绝对安全"之中,但数据规训是以牺牲个人隐私为前提的,从而导致环境的绝对安全与内心的恐惧并存。大数据条件下的城市治理短期内可能无法使人类摆脱这种恐惧,但城市治理终究要回归以人为本的本质,使技术在伦理的规训下更好地为人类服务。

关键词: 大数据, 城市治理, 秩序规训, 数据规训

Abstract: Urban governance aims to construct a sound order. In accordance with economic development, the way of order discipline has changed from moral discipline to behavioral discipline and then to legal discipline. While the validity of legal discipline is influenced by subjective factors of law makers, technological progress can offset this flaw. The practice of using big data technology in urban governance adopts the method of data discipline to maintain urban order. Technology has always been a double-edged sword. It brings convenience, but also causes harm due to the selfishness of different members in human community. This is the alienation of technology. While big data plays an active role in constructing an orderly city and its discipline helps to create "absolute security" in a city, data discipline is based upon the premise of sacrificing privacy, which results in a kind of fear in "absolute security". The urban governance under the condition of big data cannot remove such fear in a short time. However, urban governance should ultimately restore to its people-oriented essence and technology should serve people better under moral discipline.

Key words: big data, urban governance, order discipline, data discipline