Algorithms in action

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Chinese social credit systems

Trusting by Numbers: An Analysis of a Chinese Municipal Social Credit System Infrastructure. in progress (with Akos Rona-Tas) |abstract|

Both states and markets collect and evaluate information about people to enact governance and control through various institutions and infrastructures, many of which simplify social realities into numbers. This study examines the infrastructure of a Chinese municipal social credit system (SCS) that aims to collect people’s data of trustworthiness and produces credit scores, pursuing a state goal with a market approach. Through the unpacking and reconstruction of its rules, structure, and metric, we illustrate the SCS’s logic, hidden assumptions, and uneven focuses. We find that systematic biases exist in the system and would distort the representation of trustworthiness. The system unevenly impacts different populations in a nuanced way. While many disadvantaged groups could be further marginalized, some privileged social groups are more disciplined by the system in another way. We further discuss the implications of the SCS in the context of the expanding state and market algorithmic surveillance globally.

Multiple Social Credit Systems in China. Economic Sociology: the European Electronic Newsletter. 21(1): 22-32. |download| - |abstract|

In 2014, the Chinese government proposed to build a social credit system (SCS) to better collect and evaluate citizens’ creditworthiness, and grant rewards and punishments based on one’s social credit. Since then, various SCS pilots have been enacted. While current media and scholars often perceive SCS as a single and unified system, this paper argues that there are in fact multiple SCSs in China. I identify four main types of SCS and articulate the relationships among them. Each SCS has different assumptions, operationalizations, and implementations. China's central bank, People's Bank of China and the macroeconomic management agency National Development and Reform Commission are the two most important actors in the design and implementation of the multiple SCSs. Yet their distinctive views about what a "credit" is and what an SCS should be produced great tensions on the SCS landscape. I also historize current SCSs and show that many elements and assumptions of SCSs can be traced back to a broader People’s Republic of China’s (PRC) political history. At last, I propose an alternative theoretical framework to understand Chinese SCSs as a symbolic system with performative power that is more than a simple repressive and direct political project.

Algorithms in the Covid-19

Algorithms in Action: Reassembling Contact Tracing and Risk Assessment during the Covid-19. in progress.

Making Sense of Algorithms: Relational Perception of Contact Tracing and Risk Assessment during the Covid-19. in progress. (with Ross Graham) |Pre-print| |abstract|

Governments, institutions, and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment, whereby citizen whereabouts are constantly monitored to trace contact with other infectious individuals and isolate contagious parties via algorithmic evaluation of their risk status. This paper investigates how citizens make sense of Health Code (jiankangma), the contact tracing and risk assessment algorithm in China. We probe how people accept or resist the algorithm by examining their ongoing, dynamic, and relational interactions with it over time. By seeking a deeper, iterative understanding of how individuals accept or resist the algorithm, our data unearths three key sites of concern. First, how understandings of algorithmic surveillance shape and are shaped by notions of privacy, including fatalism towards the possibility of true privacy in China and a trade-off narrative between privacy and twin imperatives of public and economic health. Second, how trust in the algorithm is mediated by the perceived competency of the technology, the veracity of input data, and well-publicized failures in both data collection and analysis. Third, how the implementation of Health Code in social life alters beliefs about the algorithm, such as its further role after COVID-19 passes, or contradictory and disorganized enforcement measures upon risk assessment. Chinese citizens make sense of Health Code in a relational fashion, whereby users respond very differently to the same sociotechnical assemblage based upon social and individual factors.

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