China’s Social Credit System: A Chimera with Real Claws

Since  the State Council published a “Planning Outline for the Construction of  a Social Credit System (2014-2020)”, all administrations and localities  in China have been busy figuring out ways to develop social credit  systems relevant to their own jurisdiction, while a few corporations  have also been experimenting with private social credit ratings, more  akin to loyalty schemes, in conjunction with the policy.

From this hotchpotch of experimentation, two distinct instruments are  taking shape in the so-called public system: first, personal credit  ratings managed by localities, and secondly, blacklists of individuals  and companies managed by sectorial administrations (the Supreme People’s  Court, the Tax Department, Department of Agriculture, etc).  Arrangements across administrations and corporate partners enable the  implementation of rewards and punishments attached to the blacklists,  while personal ratings carry only perks. 

The overall goal of the system is to strengthen law enforcement, in a  context where the judicial system fails to properly deal with  misdemeanors and where people can get away with repeated infractions.  Ratings and blacklists are meant to create additional leverage to  encourage and coerce citizens into complying with laws and regulations. 

This analysis describes the different features of the  often-misunderstood Social Credit System, and uses the metaphor of a  chimera to discuss some of its problematic aspects. The chimera, in  ancient Greek mythology, is a fantastic, monstrous creature with limbs  from different animals, and it has come to symbolize a mismatched  assemblage of various parts of a different nature. 

Comparing the Social Credit System to a chimera emphasizes its  patchwork, decentralized and bureaucratic character. Thus far, the  system is an assemblage of heterogeneous indicators and enforcement  mechanisms, which differ according to the geographical location  individuals finds themselves in, and the kind of personal or  professional activities they are involved in. Secondly, the data  collection and management is mostly done at the local level or within  specific administrations. Contrary to widespread misunderstanding, the  system uses data already collected by administrations in their ordinary  activities, and not directly data from the surveillance apparatus. It is  generally quite low-tech, as such simple lists do not need big data or  AI-style processing. Moreover, only the blacklists, rather than the raw  data, are channeled onto national platforms for integration and  publication, often on a monthly basis and certainly not in real time. 

Another angle that the chimera metaphor highlights is that the very  idea that all dimensions of one person’s interactions with laws and  regulations at various levels can be rounded up into a single indicator  is a fantasy. This is the case of personal points systems at the level  of municipalities, but even more of the initiatives by private companies  that propose credit ratings as a commercial service, based on a vast  and heterogeneous range of data. It is these points systems that have  most excited the imagination of foreign commentators. Commercial credit  ratings use big data and AI technology, and private companies are likely  to develop increasingly sophisticated tools for the visualization of  public blacklists. The lack of transparency and high risk of algorithmic  bias mean that more high-tech does not make these constructions any  less chimeric. However, the implications for reputation and risks in  terms of misuse of personal data are real. 

With blacklisting, on the other hand, more and more individuals and  company representatives find themselves confronted with punishments that  restrict their mobility, their ability to take loans, or to access  certain kinds of jobs, for instance. This coercive mechanism purposely  challenges notions of data privacy and proportionality of sanctions, and  bears the risk of enforcing extralegal norms at the local level.  However, the Social Credit System only amplifies previously existing  shortcomings of the rule of law in China, such as excessive data  collection or vague norms that can be instrumentalized for commercial or  political purposes. This political and regulatory background makes the  Social Credit System stand out from global trends, as using points  systems (for driving licenses, for example) and blacklists (criminal  records) are increasingly common governance instruments around the  world.

The Social Credit System has real-life consequences, for individuals  as well as for businesses with a foot in China. One has to be wary of  myths and yet prepared to pay attention to the concrete impacts of these  ratings and blacklists, by looking at the localized, specific measures  and countermeasures that involve a variety of actors pulling and pushing  the levers of a complex administrative machine.