What do young Chinese think about social credit? It's complicated
Main findings and conclusions
- China’s emerging social credit system should be understood not as a single unified system but as a package or policy framework combining many different policies.
- Results of our student survey at three Chinese universities between December 2018 and April 2019 suggest that no easy conclusions about broad-based approval of such policies can be drawn. We also surveyed Taiwanese and German students for comparison.
- Our survey sought their responses to four policies associated with the social credit system mega-project. Students from China rated the measures more positively, with approval rates between 41 and 57 percent, than their German counterparts, who gave a maximum of 19 percent approval. However, approval rates from students in China were lower than the 80 percent approval rates found in a previous study by researchers at Freie Universität Berlin.
- Our results also show a complex picture of how Chinese respondents think about social credit and the associated risks: e.g. government surveillance was rated as a higher risk in China than abuse of data by private companies, although media discussions related to "privacy protection" in China’s official media has focused predominantly on the latter.
- After being informed about potential positive and negative effects, respondents were asked to rate one of the policies again; the proposal for an aggregated social credit score based on a range of behaviors. Germans rated it slightly more positively than before, whereas Chinese respondents adjusted their approval substantially downwards, from 53 percent in favor to just 29 percent.
- A mixture of cultural factors, concerns about safety and trust as well as censorship account for higher approval rates of policies associated with “building social credit” in China.
2. Survey: Questions designed to stimulate reflection
We took examples of real pilot projects in China and briefly introduced the different policy proposals to the participants. As we were most interested in how people think about social credit systems ranking individuals, we chose measures that apply ratings or sanctions to individuals, rather than to enterprises or institutions:
- People who have not complied with court orders to repay some money are punished in the following way: if someone calls them, the caller first hears a message that the person he/she is trying to reach has been blacklisted. The message then asks the caller to persuade them to comply with the court order. Only afterwards are they connected to the person they wanted to talk to.
- Cameras and artificial intelligence (AI) are used to detect any traffic violations. Facial recognition software identifies the culprit and fines them automatically and immediately.
- This idea is extended beyond traffic violations to all kinds of behavior, from making prompt payments to depositing garbage correctly; the system calculates an individual’s aggregated score which determines their privileges and restrictions, such as whether somebody is allowed to book high-speed trains.
- A credit score based on behaviors is used to decide eligibility for loans. We then asked participants how they saw each of these policy proposals. Generally, their responses were in line with Kostka’s previous finding of higher approval rates within China than in, say, Germany. However, our findings challenge the idea that PRC citizens are overwhelmingly supportive of the system and do not care about keeping information private from the government. The survey generated several findings that complicate the current understanding of how China’s citizens view the social credit system.
3. Initial findings: Chinese respondents are concerned about risks of government surveillance
Approval ratings in China were somewhat smaller than in Kostka’s survey. Overall, between 41 and 57 percent of the participants had a “positive” or “very positive” opinion about the projects. There were also slight differences between the proposals: The most-liked one was proposal 2, involving immediate fines for traffic violations, and the least popular was proposal 1 where individuals are asked to reprimand fellow-citizens over non-payments. There was also significant opposition, particularly to proposal 1, which 31 percent rated negatively or very negatively, and to proposal 3 suggesting aggregate individual scores and personalized sanctions for a range of behaviors – it got a 23 percent “negative” or “very negative” response.
The results show the absence of either uniform approval or disapproval towards social credit systems among PRC university students: opinions are mixed. If we were to translate the opinions into school grades (very positive=A, very negative=F), the proposals would only get a C+ (“satisfactory”). Nevertheless, average agreement with such measures was much higher than among respondents in Germany, where none of the projects got more than 19 percent approval.
There are several possible explanations for why China’s citizens like or dislike these proposals. The survey findings mirrored some frequently stated arguments for and against building social credit profiles. On the positive side, there was the potential for increased trust among strangers; reduced crime and greater economic benefits. Cons included threats posed by hackers, privacy concerns, negative consequences of mistakes, rules in favor of institutions but not the people, government surveillance, and sharing data with private companies. Agreements to the positive effects were very similar across survey respondents of different national origins, with reduced crime seen as the biggest advantage.
However, the perceived risks reveal remarkable differences: in China, respondents reported the highest concerns over the risk of government surveillance and government institutions putting their own interests first. Interestingly, sharing huge amounts of data with private companies was seen as much less of a problem. This seems counterintuitive since in recent years, China’s official media has
frequently discussed data privacy with a focus on the protection of individuals from overreach by private companies.2 Overreach on the part of the government is rarely if ever addressed in China’s official media coverage. Therefore, one might assume that PRC students would also be primarily concerned about surveillance and abuse of data by private entities rather than government surveillance, but this is not the case.
1 | Genia Kostka (2019): “China’s social credit systems and public opinion: Explaining high levels of approval,” New Media & Society, in press. Also see Genia Kostka (2018): “China’s social credit systems are highly popular – for now,” MERICS blog, 17 September 2019,
2 | Mareike Ohlberg, Shazeda Ahmed, Bertram Lang (2017): ”Central planning, local experiments– The complex implementation of China’s Social Credit System,“ MERICS China Monitor, 12 December 2017.
3 | G. J. Hofstede, and Michael Minkov (2010), Cultures and organizations: software of the mind, McGraw-Hill Education, 3rd edition.
4 | Fearfulness of crime has already been found to be at high levels in China, e.g., by Yuning Wu and Ivan Y. Sun (2009), “Citizen Trust in Police the Case of China”, Police Quarterly, 12(2), 170-191. For the three items of crime, terrorism and illegal drugs abuse, Chinese stated on average for 2.55 of them that they “caused great worry”. The comparatively low trust level in Chinese society towards outsiders (i.e. people outside family and friends) has been studied, e.g. by Jan Delhey, Kenneth Newton, and Christian Welzel (2011), “How General Is Trust in `Most People’? Solving the Radius of Trust Problem”, American Sociological Review 76(5), 786–807.
5 | Mareike Ohlberg, Shazeda Ahmed, Bertram Lang (2017): ”Central planning, local experiments – The complex implementation of China’s Social Credit System,“ MERICS China Monitor, 12 December 2017.
6 | The cultural differences may not necessarily lie between East Asia and “the West”, as Germany is well-known to put a surprisingly large emphasis on data protection, see Sabine Devins (2017): Why Germans are so private about their data, Handelsblatt, 10 February
7 | In a “trust game”, people are asked how much of a certain amount they would give to another person if this amount gets tripled and the other person can freely decide how much (if any) of it to return. Masaki Yuki, William W. Maddux, Marilynn B. Brewer, Kosuke Takemura (2005): Cross-Cultural Differences in Relationship- and Group-Based Trust, Personality and Social Psychology Bulletin, Vol. 31:1, pp. 48-6.
8 | Pointing towards a possible German media bias in favor of data protection.
9 | Mareike Ohlberg, Shazeda Ahmed, Bertram Lang (2017): ”Central planning, local experiments – The complex implementation of China’s Social Credit System,“ MERICS China Monitor, 12 December 2017.