4 FALL 2024 NO.88 / THOUGHT LEADERSHIP BRIEF Read all HKUST IEMS Thought Leadership Briefs at http://iems.ust.hk/tlb T: (852) 3469 2215 E: iems@ust.hk W: http://iems.ust.hk A: Lo Ka Chung Building, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon With Support from Masaru Yarime is Associate Professor at the Division of Public Policy and Co-Director of the AI Ethics and Governance Lab at HKUST. He has appointments as Visiting Associate Professor at the Graduate School of Public Policy at the University of Tokyo and Honorary Associate Professor at the Department of Science, Technology, Engineering, and Public Policy at University College London. He is exploring data-driven innovation such as AI, IoT, blockchain, and smart cities for sustainability and implications for public policy and governance. He serves on the editorial board of international journals, including Sustainability Science, Environmental Science and Policy, Environmental Innovation and Societal Transitions, Frontiers in Sustainable Cities - Innovation and Governance, and Data & Policy. He received a B.Eng. and M.S. in Chemical Engineering at the University of Tokyo and California Institute of Technology, respectively, and a Ph.D. in Economics and Policy Studies of Innovation and Technological Change at Maastricht University. Reference: Xie, Siqi, Ning Luo, and Masaru Yarime, “Data Governance for Smart Cities in China: The Case of Shenzhen,” Policy Design and Practice, 7 (1), 66-86 (2024). CONCLUSION There are challenges that need to be addressed in order to effectively implement data governance for people-centered smart cities in China. Private sectors and citizens lack adequate incentives to share their data for the purpose of data sharing. Enterprises involved in the smart city face challenges in assessing the value of their data assets, which hinders the exchange and utilization of data for collaborative innovation with other stakeholders. Individuals are often not adequately informed about the specific types of data being collected, how these data are processed, and the objectives for which they are utilized. There is currently a lack of well-established institutional structures to guarantee the proper handling of data gathered from citizens by public entities, ensuring that it is not used for any reasons other than providing public services. In addition, it is not certain that citizens would possess the requisite knowledge or competence to utilize the data accessible via open data platforms effectively. To better understand data governance in China, future research could focus on more specific aspects and explore emerging institutional arrangements and policy measures. It is crucial to promote the active participation of citizens in data governance to ensure that their opinions and preferences are effectively considered for the people-centered approach to smart city development.
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