This chapter examines data-driven regulation and governance within smart cities, detailing how these urban centers utilize technologies to gather and analyze data on aspects like citizen behavior, traffic, urban planning, and waste management. It outlines the global adoption of data science, big data, AI, IoT, and predictive analytics by smart cities to enhance service efficiency and decision-making. The chapter also addresses the legal complexities of using these technologies in shaping local regulations and governance. It specifically tackles three challenges: the misalignment between traditional administrative law and data-driven approaches; the impact of privatizing public services through the increased outsourcing of technologies to private companies; and the lack of transparency and accountability in data-driven administrative procedures. Drawing from a wide range of interdisciplinary smart city literature, the chapter provides examples of data-driven practices from various jurisdictions.
Fernandes Da Silva Ranchordas, Sofia Hina; Klop, Abram. (2024). Data-driven regulation and governance in smart cities. In Mak, Vanessa (Eds.), Research Handbook in Data Science and Law, Second Edition (pp. 251-276). Edward Elgar Publishing. Isbn: 9781035316441. Doi: 10.4337/9781035316458.00019.
Data-driven regulation and governance in smart cities
Fernandes Da Silva Ranchordas, Sofia
;
2024
Abstract
This chapter examines data-driven regulation and governance within smart cities, detailing how these urban centers utilize technologies to gather and analyze data on aspects like citizen behavior, traffic, urban planning, and waste management. It outlines the global adoption of data science, big data, AI, IoT, and predictive analytics by smart cities to enhance service efficiency and decision-making. The chapter also addresses the legal complexities of using these technologies in shaping local regulations and governance. It specifically tackles three challenges: the misalignment between traditional administrative law and data-driven approaches; the impact of privatizing public services through the increased outsourcing of technologies to private companies; and the lack of transparency and accountability in data-driven administrative procedures. Drawing from a wide range of interdisciplinary smart city literature, the chapter provides examples of data-driven practices from various jurisdictions.| File | Dimensione | Formato | |
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