A Study of Transformations in City Governance Due to the Use of Big Data Analytics

大数据分析带来的城市治理变革研究

• 批准号: 1754594
• 负责人: Michael Schudson
• 金额: $ 1.34万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1754594&HistoricalAwards=false
• 关键词: Study; Transformations; City; Governance; Due

This award supports a dissertation research project, a case study of a smart city in development. The researcher will conduct a year-long, multi-sited ethnographic study of a Kansas City, where public officials, ordinary residents, and local entrepreneurs have joined with tech giants such as Cisco, Google, and Sprint to build citywide fiber-optic broadband and a pilot smart city system. She will examine how the adoption of big data analytics is transforming local government practices and civic engagement, and what the implications of such changes are for social inequality, local governance, and urban policy. It particularly focuses on what happens when smartness as technical innovation drives not only the solutions for local problems, but also the methodology of discovering and defining them. In addition to disseminating the results of this project in scholarly literature, she will share findings with local stakeholder groups and in other non-academic venues including opinion columns and guest posts for popular science and technology blogs such as those hosted by Scientific American and the Atlantic. In doing so, the results will serve to inform ongoing public debates around the cultural role of data analytics in the city. The findings will help technologists and local government officials be cognizant of the cultural paradigms and political decisions they build into technical infrastructure and enable discussion about potential alternatives to these paradigms, informing the future design of actual systems.The project will serve to provide a better understanding of how cities use smart technologies. It will allow for a more nuanced critique of urban big data, one that understands how such data is produced, shared, and analyzed across various communities; conversely, it will show how cities shape smartness as a socio-technical construct. It will challenge the view that organizing data-driven urban systems is a top-down process by showing how civic entrepreneurs are being encouraged to collaborate with city officials and voluntary organizations through smart city experiments. It will also examine a new mechanism that drives the production of social problems in local governance, one in which the adoption of big data analytics leads to identifying new problems in the city through both the incentives of the innovation economy, and the epistemologies of data science. Rather than immediate efficiency gains or systemic advances, city officials and civic entrepreneurs intend less to solve long-standing problems than to discover new ones. Their constant hunt for new problems or novel ways of measuring stands in contrast to expectation that the smart city solves, or aims to solve, extant urban problems. By demonstrating an on-the-ground account of new forms of algorithmic city management, this study will reveal how a city enabled by smart technologies and urban data can engage more effectively with exclusion and disparities across different population groups.

该奖项支持一个学位论文研究项目，一个正在发展中的智慧城市的案例研究。这位研究人员将对堪萨斯城进行为期一年的多地点人种学研究，在那里，公职人员、普通居民和当地企业家与思科、谷歌和Sprint等科技巨头合作，建设全市范围的光纤宽带和试点智能城市系统。她将研究大数据分析的采用如何改变地方政府的做法和公民参与，以及这些变化对社会不平等、地方治理和城市政策的影响。它特别关注当作为技术创新的智能不仅推动解决当地问题的解决方案，而且推动发现和定义这些问题的方法时会发生什么。除了在学术文献中传播这一项目的成果外，她还将与当地利益攸关方团体和其他非学术场所分享研究成果，包括科普科技博客的观点专栏和嘉宾帖子，例如由科学美国人和大西洋月刊主办的那些博客。通过这样做，结果将有助于为正在进行的关于数据分析在城市中的文化角色的公共辩论提供信息。这些发现将帮助技术专家和地方政府官员认识到他们构建在技术基础设施中的文化范式和政治决策，并使人们能够讨论这些范式的潜在替代方案，为未来实际系统的设计提供信息。该项目将有助于更好地了解城市如何使用智能技术。它将允许对城市大数据进行更微妙的批评，了解这些数据是如何在不同社区产生、共享和分析的；相反，它将展示城市如何将智能塑造为一种社会技术构造。它将挑战这样一种观点，即组织数据驱动的城市系统是一个自上而下的过程，展示了公民企业家如何被鼓励通过智能城市试验与城市官员和志愿组织合作。它还将研究一种新的机制，这种机制在地方治理中驱动社会问题的产生，在这种机制中，采用大数据分析导致通过创新经济的激励和数据科学的认识论来发现城市中的新问题。与其说市政府官员和公民企业家打算解决长期存在的问题，不如说他们想要发现新的问题，而不是立竿见影的效率提升或系统性进步。他们不断寻找新问题或新的衡量方法，与智能城市解决或旨在解决现有城市问题的期望形成鲜明对比。通过展示新形式的算法城市管理的实际情况，这项研究将揭示一个由智能技术和城市数据支持的城市如何更有效地参与到不同人口群体的排斥和差异中。