China's Social Credit System is a big thing, and most - if not all - mainstream reporting on it contains major factual mistakes. I spent a bit of time and 15000 words to review how it developed. Available freely on: papers.ssrn.com/sol3/papers.cf…
Major takeaways: (1) The Social Credit System is not, in fact, one system. It is an ecosystem of initiatives at the central and local level, within State and private actors, that largely share a fundamental logic.
That logic is simple: incentivising individuals and businesses to improve their behaviour by confronting them with the consequences of their behaviour. 2/
For central government depts, that means creating information sharing platforms to enable blacklists. Those breaking particular laws and regulations will enter on a blacklist that disables them from doing certain things. At the central level, there are over a dozen of these lists
Best known: the list for non-performance of court judgments: over 40 govt depts and organisations participating, as well as private parties. This is the list with the broadest consequences, from prohibition of luxury purchases and air tickets to limitations on jobs and loans 4/
Other lists are more specific, for instance for misconduct on trains and airplanes. Sanctions are more focused as well. Note: there is no quantitative scoring involved. You are either on or off the list. Also no algorithmic decision making.
Some, but not all, of the local trials do have some sort of ranking system, such as the Rongcheng trial as reported by @SiminaMistreanu. Here, infringing rules also results in a status that may result in eg. disbarment from govt tendering and govt jobs. foreignpolicy.com/2018/04/03/lif…
Scoring is also present in a very limited way in the financial credit scoring system run by the People's Bank of China, in a manner not dissimilar to FICO scores. 7/
The reason most journalist think the SCS is about scoring, is Alibaba's Sesame Credit programme. However, while Sesame does issue a score, this is perhaps best seen as a combination of an intra-platform assessment together with a loyalty scheme: higher score, more benefits 8/
Furthermore, participation in Sesame is voluntary, and it's not quite clear how Sesame scores could be used in the State's SCS (see also the PBoC's denial of credit scoring licence to Sesame). The idea that Sesame is the blueprint for the future govt system is speculative 9/
(2) The use of technology in the SCS is limited. Decisions are essentially made on the basis of individuals' past conduct. At present, there is none of the sort of algorithmic decisionmaking, artificial intelligence or probabilistic assessment that is often asserted.
Information technology is used to collect, store and share data efficiently, to effectively govern a very large, populous and complex country. Some info is collected through facial recognition cameras in some of the local trials, most of it is digitised govt records. 11/
There is one automated bit: the central system flags entries appearing three times or more on priority scrutiny lists submitted by individual depts. These lists identify misconduct not serious enough for blacklisting 12/
For Sesame, we don't quite know how the scoring algorithm works, and its managers have made some conflicting statements. However, bear in mind that a low Sesame score does not lead to sanctions or constraints. 13/
(3) The SCS is not primarily "political". Its primary role is engineering trust in the market place and social conduct, as well as providing means of internal oversight on govt officials. In that sense, it's actually quite boring. 14/
The major leading institutions for the SCS are the National Development and Reform Commission, and the People's Bank of China. The public security authorities and propaganda authorities merely play a limited supporting role 15/
Put bluntly, on the tough issues, ranging from Uyghur separatism to subversion, the Chinese government has other, much more targeted and scary tools at its disposal. It doesn't need an SCS for those. 16/
(4) Obviously, the SCS is not static. The point of this paper is that its meandering evolution has occurred in step with changes in external circumstances, policy learning within Party and state, and technological innovation. This will continue in the future 17
To gauge shifts in the way the SCS functions, tracking the following five dimensions will be necessary 18/
1) Information sources. For the moment, these are mainly govt records. How will other data, including privately-generated data, be included?
2) Nature of consequences. At the moment, quantitative scoring is largely absent: blacklist systems are binary. Will the much-vaunted idea of a "citizen score" actually be introduced at some point?
3) What is enforced? At the moment, with the exception of financial credit scoring, the SCS is an amplification device for existing laws and regulations. Will the system also come to reward or punish conduct relating to social norms?
4) Time orientation: at the moment, the credit system only looks towards what people and businesses have done in the past. Will the govt, at some point, introduce future-oriented, predictive and/or probabilistic assessment?
5) Individual v. collective: decisions in the current iteration of the SCS are only based on the conduct of a particular individual or business. Will, at some point, algorithms be introduced that include mass correlative analysis of collective behaviour? End/
Acknowledgments: I've been much helped in writing this paper by the work of, and conversations with Shazeda Ahmed, @He_Shumei, @ChinaLawTransl8 and @FloraSapio. They are well worth following.
Thanks also to @SPCmonitor for flagging this: supremepeoplescourtmonitor.com/2016/04/27/sup…
