Yuchen Chen
University of Michigan, Ann Arbor, Michigan, United States
This paper examines the social, technological, and emotional labor of maintaining China’s data-driven governance broadly, and dynamic zero-COVID management in particular. Drawing on ethnographic research in China, we examine the sociotechnical work of maintenance during the 2022 Shanghai lockdown. This labor included coordinating mass testing, quarantine, and lockdown procedures as well as implementing ad-hoc technological workarounds and managing public sentiments. We demonstrate that, far from being effected from the top down, China’s data-driven governance relies on the circumscribed participation of citizens. During Shanghai’s lockdown, citizens with relevant expertise helped to maintain technological stability by fixing or programming data systems, but also to ensure the ongoing production of “positive feelings” about social stability through data-driven governance. In so doing, such citizens simultaneously enacted an ambivalent and limited form of agency, and maintained social and by extension political stability. This article sheds light on data-driven governance and political processes of maintenance.
https://doi.org/10.1145/3544548.3581299
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)