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.
As COVID-19 is rapidly spreading around the world, some countries have launched or plan to implement contact-tracing apps to detect exposure risks. In China, the government relies on Health Code, developed by Alipay and WeChat, for identifying people potentially exposed to COVID-19. The color-based code can determine people’s exposure risks and freedom of movement based on factors like travel history, duration of time spent in risky areas, and relationships to potential carriers. This essay discusses the rise of Health Code from a platform perspective, arguing that digital platforms are key players conducting health surveillance and mediating state–citizen relations in China. More importantly, tracing apps might become a normal practice in many countries, suggesting that platforms will be substantially adopted for health surveillance.
To improve maneuverability and stability of articulated vehicles, we design an active steering controller, including tractor and trailer controllers, based on linear quadratic regulator (LQR) theory. First, a three-degree-of-freedom (3-DOF) model of the tractor-trailer with steered trailer axles is built. The simulated annealing particle swarm optimization (SAPSO) algorithm is applied to identify the key parameters of the model under specified vehicle speed and steering wheel angle. Thus, the key parameters of the simplified model can be obtained according to the vehicle conditions using an online look-up table and interpolation. Simulation results show that vehicle parameter outputs of the simplified model and TruckSim agree well, thus providing the ideal reference yaw rate for the controller. Then the active steering controller of the tractor and trailer based on LQR is designed to follow the desired yaw rate and minimize their side-slip angle of the center of gravity (CG) at the same time. Finally, simulation tests at both low speed and high speed are conducted based on the TruckSim-Simulink program. The results show significant effects on the active steering controller on improving maneuverability at low speed and lateral stability at high speed for the articulated vehicle. The control strategy is applicable for steering not only along gentle curves but also along sharp curves.
This article critically examines South Korea and China’s COVID-19 tracking apps by bridging surveillance studies with feminist technoscience’s understanding of the “politics of care”. Conducting critical readings of the apps and textual analysis of discursive materials, we demonstrate how the ideological, relational, and material practices of the apps strategically deployed “care” to normalize a particular form of pandemic technogovernance in these two countries. In the ideological dimension, media and state discourse utilized a combination of vilifying and nationalist rhetoric that framed one’s acquiescence to surveillance as a demonstration of national belonging. Meanwhile, the apps also performed ambivalent roles in facilitating essential care services and mobilizing self-tracking activities, which contributed to the manufacturing of pseudonormality in these societies. In the end, we argue that the Chinese and South Korean governments managed to frame their aggressive surveillance infrastructure during COVID-19 as a form of paternalistic care by finessing the blurred boundaries between care and control.
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