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Big data technologies have been adopted by both the public and private sectors to develop and expand surveillance capacities. This article traces the institutional processes and political‐economic interests of the public and private stakeholders involved in the construction of China's Social Credit System (SCS), which is currently on track for full deployment on 1.4 billion citizens by 2020. The SCS aims to centralize data platforms into a big data–enabled surveillance infrastructure to manage, monitor, and predict the trustworthiness of citizens, firms, organizations, and governments in China. A punishment/reward system based on credit scores will determine whether citizens and organizations are able to access things like education, markets, and tax deductions. While the SCS is widely described by the Western news media as a means of “big brother” or political control, we find that it is a complicated system that focuses primarily on financial and commercial activities rather than political ones. This article presents a framework for understanding state surveillance infrastructures by exploring how various government agencies are cooperating to establish this centralized data infrastructure with the aim of scoring credit, and discussing the distinct but interconnected processes of data collection, data aggregation, and data analytics.
Liang et al. (Thu,) studied this question.