Beneath the surface of China's Social Credit System

Beneath the surface of

China’s Social Credit System

Malmö University

Supervisor: Mikael Spång Subject: Human Rights Bachelor thesis, spring 2020

Abstract

China has developed a technological Social Credit System that monitors, collects, and analyses behavioural data from citizens and enterprises. The system categorises them

trustworthy or untrustworthy according to their behaviour. This paper aims to investigate the technological elements of China’s Social Credit System and analyse its social functions. In doing so, I will address the human rights implications following from the system. The thesis uses a content analysis method and draws on three theoretical studies, including,

dataveillance, social sorting and neoliberalism and subjectivity. The study shows that China intends to continue investing in immoral technological elements; might succeed to govern citizens in self-governing; and prioritises the system in front of scarce human rights regulations. The conclusion holds that China intends to continue developing and

strengthening the Social Credit System to enhance the behaviour of their society, regardless of some human rights implications, to reach their desired outcome.

Keywords: Social Credit System, Social functions, Technology, Human rights Word count: 13 985

Abbreviations

AI – Artificial Intelligence

API – Application Programming Interface BSN – Blockchain Service Network CCTV – Closed-Circuit Television CPC – Communist Party of China

ICCPR – International Covenant on Civil and Political Rights Ifri – Institute francais des relations international

PBOC – People’s Bank of China PCI – Public Credit Information PRC – People’s Republic of China SCS – Social Credit System

SMT – Statistical Machine Translation

UDHR - Universal Declaration on Human Rights 5G – Fifth Generation

Table of contents Abstract………...…2 Abbreviations………..…..3 Table of contents………..….4 1. INTRODUCTION………..…...5 1.1 Introduction……….……5

1.2 Previous research and research problem……….…5

1.3 Aim & research questions………...6

1.4 Relevance to human rights………..7

1.5 Delimitations………...8

2. THEORY………...8

2.1 Dataveillance………...9

2.2 Social Sorting……….10

2.3 Neoliberalism and Subjectivity………..11

3. METHOD……….12

3.1 Qualitative research………12

3.2 Content analysis………...…..12

3.3 Codes and Coding………..13

3.4 Sampling………....14

4. CHINA’S SOCIAL CREDIT SYSTEM………..15

5. ANALYSIS………..18

5.1 China’s surveillance systems………...18

5.2 Categorising Chinese citizens………25

5.3 Building human capital………..31

6. CONCLUSION………37

6.1 Discussion and findings……….37

6.2 Human rights discussion………39

6.3 Future research recommendations...………..39

1. Introduction 1.1 Introduction

China has built a Social Credit System (henceforth SCS) to create a harmonious society and further enhance their economic growth (Creemers, 2015). A common understanding of China's SCS is that the system is based on accountable principles and implemented in an incentive-grounded system for minimizing risk and managing Chinese citizens behaviour. The system is controlled by the government, regulated by various data-driven platforms and administrated by public and private institutions that collect, aggregate and analyse personal data from individuals and enterprises to delegate credit scores according to their behaviour. The incentive-grounded mechanism is built on a reward and punishment system that rewards trustworthy citizens and punishes untrustworthy citizens (Backer, 2018, Liang et. al, 2018 and Chen & Cheng, 2017). The SCS aims to "allow the trustworthy to roam everywhere under heaven while making it hard for the discredited to take a single step". The data-driven platforms are developed through advanced technological elements that China have been investing in during the last couple of years. The SCS collects personal data from individuals and enterprises by monitoring their online and offline behaviour through various surveillance mechanisms (Creemers, 2015). Many Western media platforms have argued that China’s SCS is like “Big Brother”, a system that controls its population by monitoring them (Liang et, al, 2018: 415). Monitoring Chinese citizens behaviour and categorizing them trustworthy or untrustworthy may infringe upon their human rights to privacy and non-discrimination (Løge, 2019: 2). To get an understanding of the SCS and its human right implications, I have focused my study on the systems technological elements and social functions. The analysis involves the qualitative directed content analysis method and is guided by three theoretical studies. 1.2 Previous research and research problem

Previous research has, for instance, studied the SCS's surveillance and big data's functions, to understand how the system collects personal behavioural data, and rates citizens and

enterprises according to their behaviour. Grote and Bonomi have studied the social and political aspects of this (Grote & Bonomi, 2018: 1), while Chen and Cheng have addressed the legal framework applied to surveillance mechanism of the big data system and how it infringes upon citizens privacy (Chen & Cheng, 2017: 35).

Backer and Liu have studied the assessment and rating mechanisms of the SCS, how it is controlled and what makes a person trustworthy or untrustworthy. Liu examines the

tension between public and private institutions who are responsible for administrating the SCS in different regions, while Backer discusses the effects of trustworthy and untrustworthy behaviour, and if the system could be applied in a western country (Backer, 2018: 1 & Liu, 2019: 30).

China’s SCS is a fairly new political and social concept, involving advanced technological elements that are constantly evolving, due to this previous research is scarce. This thesis studies the latest technological development of the system, which will contribute to a recent study of the system. Except for Chen and Cheng and a few other scholars who briefly cover how the SCS’s infringes upon citizens right to privacy, no other research except a master thesis from Oslo University has studied the SCS from a human rights perspective (Løge, 2019). Since this thesis studies the human rights implications of the SCS, it will contribute to this gap of knowledge. The thesis draws on three different theoretical studies to analyse different perspectives of the SCS that may lead to human rights implications. Two of these theories have been used in studies covering the SCS in previous research, but one of them (neoliberalism and subjectivity) has only been applied in a blog post that discusses the SCS (Tümmler, 2018 & Lee,2019). Due to that, this thesis will contribute to a unique perspective of the SCS and in combination with the two other theories, the paper will investigate different dimensions and perspectives of the system than previous research. 1.3 Aim and research questions

This thesis aims to investigate the technological elements of SCS and analyse its social functions. In doing so, I will address the human rights implications following from the system.

To investigate the technological elements and the social functions of China’s SCS, I use relevant theories for understanding SCS. In the context of studies about

surveillance, I primarily draw on research from dataveillance, which helps me understand the technological elements of surveillance that contribute to the social functions in the Chinese society. For analysing the social functions of the SCS, I use research from social sorting because the reward and punishment aspect of the system implicates that it categorises people, which this theory will help illustrate. In addition to this, I will draw on research from

Neoliberalism and subjectivity, which will help me address the effect the system has on Chinese citizens behaviour.

To achieve the aim, the following objectives have been applied. I will use the latest material released by China’s tech companies and the Chinese government, about

technological elements of the SCS; apply different international and national human rights legislations; discuss the social function of the technological system and how it infringes, directs and nudges upon people’s behaviour; study my chosen subject through the lens of two surveillance theories and one sociological theory; and contribute a section of this thesis to demonstrate the human rights relevance.

The exploratory research questions are based on the expressed aim of this thesis and reads as follows:

Research questions:

1) What are the technological elements and social functions of China’s Social Credit System?

2) What are the human rights implications of these technological elements and social functions?

1.4 Relevance to Human Rights

As previously expressed in the objectives of the aim, I will demonstrate how China’s SCS might infringe up the human rights of Chinese citizens. It is important to understand the social functions of the SCS's technologies since this forms the way people think and behave, which in turn may have human rights implications. This can be understood as sociology of law, since it seeks to understand the relationship between society and law, by explaining the social process related to law (Ervasti, 2008: 139, 142). In the following section, I will present how surveillance may infringe upon people's right to privacy and non-discrimination, and at the end, I will further display some social processes of the SCS that might challenge human rights.

People's right to privacy is central to the study of human rights. The contemporary

relationship between technology and security offers ways for governments to monitor their citizen's behaviour, not only through cameras but also on social media and other platforms. Lieshout et. al, argue, by investing in new technologies for security reason the Nation-States minimizes citizens right to privacy (Lieshout et. al, 2013: 119). The Chinese SCS understands untrustworthy citizens as a threat to their nation, maybe not primarily towards the country's security, but its social and economic development (Creemers, 2015). In the analysis, I will discuss how the SCS infringes upon Chinese citizens right to privacy and what little protection the national legislation holds.

At first, one might not think that surveillance challenges non-discrimination policies, but according to Lyon “surveillance today sorts people into categories, assigning worth or risk, in ways that have real effects on their life-chances, which allows deep

discrimination to occur” (Lyon, 2003: 1). By applying Lyons social sorting theory, I will get an insight into how the SCS categorises Chinese citizens. In addition to this, I will discuss the categorisation of citizens against non-discrimination policies in international and national legislation.

Furthermore, this paper will reflect other social processes of the SCS that might infringe upon Chinese citizens human rights, including, detaining citizens in education and training centres (NBC News, 2019); restricting citizens social functions within various institutions; and publicly shaming citizens for inadequate behaviour (Creemers, 2015). 1.5 Delimitations

This thesis delimitation has been carried out when choosing theories. There are several surveillance and sociological theories that I also could have used in my analysis. The main reasons I choose to use these theories are because: dataveillance covers data systems used to surveil people’s behaviour; social sorting reveals the relationship between technological elements/surveillance and social functions; and Neoliberalism and subjectivity allows me to study a different angle that highlights how the system affects people’s behaviour.

2. Theories

This thesis examines the technological elements and the social functions of China’s SCS through the theoretical lens of two surveillance studies and one sociological study.

Surveillance is a contemporary issue, with increasing high-tech surveillance technology and a gradually growing scope of persons and spaces that are being surveilled daily. This has developed a scholarly discipline named surveillance studies, which is a broad field covering both empirical and theoretical aspects of the past, present and soon to be future society (Galič, Timan & Koops, 2017: 10). Galič et al. have divided this disciplinary field into three different chronological/thematic phases. The first two forms a concept of ideas about surveillance by including theoretical frameworks, these are further elaborated on in the third phase. The first phase centralises procedures of watching over subjects (people) and self-disciplining them, exemplified by Bentham and analysed by Foucault. They offer

architectural theories of surveillance through the panoptical buildings structured functions, which monitors subjects physically and spatially. The second phase involves elaborating on

infrastructure theories of surveillance, where the power is exercised through networked surveillance. These theories rely primarily on digital technologies rather than physical, and usually watch subjects from a distance and frequently examine data-doubles instead of real people. The third stage extends the key conceptual structures offered earlier, by expanding towards conceptualised surveillance through concepts including, social sorting, dataveillance and peer-to-peer surveillance (Galič et al, 2017: 9).

In this paper, I will apply two theoretical frameworks from the third phase of surveillance studies. The sociological theory I use is Foucault's analysis of neoliberalism and the production of subjectivity.

2.1 Dataveillance

Clarke (1988) claims that tyranny is one of the biggest threats to democracy and surveillance is a component of this tyranny. Clarke has developed the dataveillance theoretical framework. According to him, dataveillance is “the systematic use of personal data systems in the

investigation or monitoring of the actions or communications of one or more persons”. It sets out to gather general information about people, including their activities and of whom they associate with, through computer entities (Clarke, 1988: 498-499).

Clarke divides dataveillance into personal surveillance and mass surveillance. In this paper, I will only consider the mass surveillance aspect of dataveillance. Mass

surveillance is, according to Clarke, “the surveillance of groups of people, usually large groups. In general, the reason for investigation or monitoring is to identify individuals who belong to some particular class of interest to the surveillance organization” (Clarke, 1988: 499). The techniques used in mass dataveillance are, screening all collected data against internal norms; users’ interactions in the digital world should be gathered and compared with similar data from different systems, whether or not the person is exceptional (suspected); user interaction inspection of individual should be gathered and compared with similar data from different systems; and profiling (identifying) individuals from all data collected (Clarke, 1988: 502). According to Clarke, these techniques may be successful when conducted by a single technological system but can become even more successful when conducted by several technological systems. These systems can either be operated by one single organisation or various organisations concerned (Clarke, 1988: 504).

Dataveillance can result in significant benefits, including, for instance, securing people and protecting their properties and preventing fraud (Clarke, 1988: 505). Although, according to Clarke "dataveillance is, by its very nature, intrusive and threatening" (Clarke,

1988: 504). He claims that the theory involves multiple dangers to society. I will only mention one of them, due to its relevance for my analysis. This danger holds that sometimes dataveillance lacks a legal authority, which may result in the individual being exposed to public abuse and perhaps even being neglected the right to undertake some activities (Clarke, 1988: 507).

2.2 Social Sorting

Surveillance, has for a long time, only been a word used by the police or foreign intelligence services. Today it is a part of organisations, companies and individuals’ everyday lives, which most of us generally comply with. Surveillance is usually carried out by advanced

technological network systems and is no longer only a matter of privacy, but also a matter of social justice - as it sorts people into categories after individuals worth or from the risk a person might cause society (Lyon, 2003: 1). To understand surveillance as social sorting, one has to consider economic and social functions and how computer systems collect and

systematize personal data to influence and manage people. One of the key features of

surveillance today is that personal data can be sorted, checked and matched at a distance away from individuals without their knowing (Lyon, 2003: 2). For instance, international and national security measures are programmed to categorize the personal data collected through various platforms, to classify how people should be treated depending on their "threat" to the nation or world (Lyon, 2007: 162). Lyon, the inventor of the social sorting theory holds that “Surveillance is not itself sinister any more than discrimination is itself damaging” (Lyon, 2003: 2). According to him, algorithms are encrypted in computers to automate social and personal categorizing by sorting people’s online and offline behaviour. These algorithms are like invisible doors, that either allows or denies access to social and economic activities. Furthermore, he holds that the algorithms are designed to manage and influence people’s direct and indirect behaviour (Lyon, 2003: 13).

According to Lyon, the importance of risk management has risen in the late 20th century, through new electronic infrastructure that allows an increase in recording, collecting and analysing personal data to manage risks effectively. This increase often reflects long-term governmental priorities of economic, social and cultural plans. Nation-State risk management programmes use surveillance techniques to sort their citizens into categories of high risk and low risk and treat them accordingly, or one could also say differently (Lyon, 2007: 163).

Lyon addresses surveillance as social justice, which means on one hand a normative approach of surveillance, but on the other hand an analytical approach to the

categorisation of sorting people. In the analysis, I will in part make use of the normative dimension when accessing social sorting, but primarily use Lyon’s ideas for analysing social sorting empirically. The normative evaluation in the analysis will draw on reports from human rights organisations involving rights found in human rights treaties.

2.3 Neoliberalism and subjectivity

Foucault spent one of his years at Collège de France (1978-1979) to critically examined neoliberalism, during his lectures published as Naissance de la biopolitique. He discussed new critical aspects of neoliberalism, but also extends his criticism to demonstrate how

neoliberalism can be understood as a producer of subjectivity, where people are represented as "subjects of human capital". In other words, his understanding of neoliberalism is not only the behaviour of States and markets, but it also governs individuals into a particular way of living. Compared to classical liberalism which produces exchanging individuals in the marketplace (society), Neoliberalism, according to Foucault, fosters competitive individuals. By fostering competitive individuals, the governing State will have access to intervene, not on society, but on the behaviour of society. To create individuals who feel the urge to compete, we must consider the huge expansion of the economy in neoliberalism. According to Reads understanding of Foucault, (2009: 28) in a neoliberal society "everything for which human being attempt to realize their ends, from marriage to crime, to expenditures on children, can be understood "economically" according to a particular calculation of cost for benefit". This developed a huge shift from "labour" to "worker" where the worker became "human capital" (Read, 2009: 25-28). Balibar holds that this shift involves "labour no longer being limited to the specific sites of the factory or the workplace, but to any activity that works towards desired ends" (Read, 2009: 25-31). By using one's skills, social and personal attributes, a person contributes to a creation of services and goods that produce economic growth, which in turn entails the worker with a salary (his or her desired end). Any activity a person does to advance his/her skills and attributes, to increase one's earnings or achieve satisfaction, is an investment in human capital (Read, 2009: 25-28). Read holds that due to this, the economy can be understood as an actor in every aspect of human life, as every action, including higher education, marriage or even crime can be seen as an investment in one's skills and attributes (Read 2009: 31). This means that economic growth is not only happening at a workplace, quite the opposite, it is happening outside work when a person is investing in his/her skills and attributes through numerous social relationships. According to Negri (1994) "the production moves from the closed spaces of the factory to become distributed across all of

social space, encompassing all spheres of cultural and social existence". Suddenly what influences a person's opinion, feelings and taste become very important for capital growth and according to Read, this subjectivity in a neoliberal society is what has to be controlled. (Read, 2009: 33).

According to Foucault, neoliberalism created a new dimension of

governmentality that governs people and make them govern themselves, by no longer offering them laws and rights but instead, activities of interest that they can invest in and competed amongst. The State allows people to govern themselves by offering them cheap desirable activities and expensive undesirable activities and believes that individuals will make the right choice based on their interests. This new dimension of governmentality needs to offer people freedom, for them to make choices between competing strategies. Although, to produce freedom the State must establish restrictions i.e. obligations relying on threats, limitations and forms of coercion that the people can be free from. In other words, restrictions are crucial for a person to feel free, because if there are no restrictions there is nothing the person can be free from (Read, 2009: 29). By controlling subjectivity and "freeing" individuals to make choices based on interest and competition, neoliberalism governs and regulates the society through isolation and dispersion. When a society becomes wealthy, neoliberalism can present it as a "society made up of self-interested individuals" (Read, 2009: 34).

3. Method

3.1 Qualitative research

This thesis is a result of a qualitative research process, involving the content analysis method to analyse the technological elements and sociological functions of China’s SCS. To answer my research questions, I chose a qualitative approach mainly because I wanted to explore and describe the phenomena of the SCS (Dovetail research, 2018).

3.2 Content analysis

According to Hsieh and Shannon’s article on content analysis, the aim of using content analysis is “to provide knowledge and understanding of the phenomenon under study” (Hsieh & Shannon, 2005: 1278). I chose content analysis, mainly for one reason, that I aim to

understand the two phenomena (technological elements and social functions) of China’s SCS. Since most of my material is found in texts, content analysis is relevant because it allows me to understand certain facts in text material, where other methods focusing on interviews of surveys would be irrelevant.

Hsieh and Shannon hold that content analysis has become a commonly used qualitative research approach, involving three different techniques, including "conventional, directed and summative". In this thesis, I decided to draw on the directed approach. They outline that the directed approach uses earlier knowledge or theory as guidance for the

analysis (Hsieh & Shannon, 2005: 1277). I have chosen to apply theory as the guiding tool for my analysis. Due to this, I have carefully selected my theories to get a general understanding of the technological elements of the SCS and its social functions. According to Hsieh and Shannon’s, the operational steps that should be taken when applying a directed approach is, firstly to identify keywords or concepts as codes (categories). These codes derive from the guiding tool. The second step is coding, which involves breaking down the sampled material under the chosen codes (Hsieh & Shannon, 2005: 1281).

Hsieh and Shannon acknowledge that directed content analysis involves both advantages and disadvantages. The main advantage of this method is that theory or earlier knowledge can be supported or further developed, by examining if the findings from the analysis offer supporting or non-supporting verification of the theory. (Hsieh & Shannon, 2005: 1282). The disadvantage of this method is the risk of bias, the primary reason for this is that the analysis will be guided by theory or earlier knowledge. (Hsieh & Shannon, 2005: 1283). I have chosen to use three theories to guide my analysis, mainly to get different perspectives of the implications of the technological elements and social functions of China’s SCS, but also to form a neutral understanding of these phenomena to avoid the study being biased.

3.3 Codes and coding

By considering the most relevant facts, I have developed different codes from without the three theories. The codes are dependent on the separate theories, which may guide me to see new things in the material. In the following section, I will discuss the codes I have decided upon by presenting one theory at the time. Under the codes I will show the coding process, which I have done by “translating” words from the codes into similar word in the material, allowing me to break down the material under my chosen codes.

The codes I have used for the dataveillance theory are: Monitoring behaviour across platforms; identifying individuals; and systems operated by organisation(s). Here are some examples of words I have “translated”. I have “translated” monitoring into observed and surveilled; platforms into systems, computing and social media; individuals into citizens and groups of people; organisation(s) into the Chinese Council and government. Here is an

example of how I “translated” a code into a sentence. The code systems operated by

organisation(s) can be “translated” into “China shall standardize and develop a credit rating market” (Creemers, 2015).

The codes I have used for the social sorting theory are: Risk management; manage and influence behaviour; and categorizing “low” and “high” risk individuals. Here are some examples of words I have “translated”. I have “translated” risk into security threat and untrustworthy; and “low” and “high” risk into untrustworthy and trustworthy. Here is an example of how I “translated” a code into a sentence. The code manage and influence behaviour can be “translated” into “The goal of the system - to make trustworthy people benefit everywhere and untrustworthy people restricted everywhere. This will encourage citizens to enhance their good behaviour” (Fox, 2019).

The codes I have used for the neoliberalism and subjectivity theory are: Governing behaviour of society; self-governed individuals; and creating subjects of human capital. Here are some examples of words I have “translated”. I have “translated” behaviour into trustworthy and untrustworthy; creating into developing and urging; subjects into citizens and people. Here is an example of how I “translated” a code into a sentence. The code

creating subjects of human capital can be “translated” into “The planning outline agrees with this and further elaborates that Chinese citizens will be guided by trustworthy incentive measurements to make the right choices affecting their social and economic development” (Creemers, 2015).

3.4 Sampling

Hsieh and Shannon hold that researchers using a qualitative content analysis can collect material in print, verbal or electronic form, obtained from sources, including for instance interviews, open-ended survey questions, articles, reports, media, books, videos (Hsieh & Shannon, 2005: 1278).

When sampling I chose to let The Planning Outline for the Construction of a Social Credit System (2014-2020) (henceforth Planning outline) decide on what timeframe I should sample within, to collect the most relevant material for my research. The Planning outline was released in 2014 and is operative until the end of 2020, due to this my material is sampled from 2014-2020, although most of the material is from 2018-2020 to grasp the most relevant understanding. In addition to this, I sampled material from Chinese governmental documents and article; peer-viewed scientific articles; United Nations, Non-Governmental

Organisations and State reports and documents; news articles and videos, to get various perspectives of the subject.

The subject I have chosen to dedicate my research to is occurring right now, this makes the topic very interesting, but also difficult, in the sense that primary material is scarce. All governmental documents and articles, sampled from various official Chinese webpages are primary material, while the rest of the material is secondary. In this paper, I have mainly used primary sources to lead arguments and secondary sources to support these arguments. According to Streefkerk, good and credible research involves both primary and secondary sources, the reason for this is that the sources complete each other which helps the author build a convincing argument (Streefkerk, 2019).

Due to the importance of the Chinese governmental documents and articles, I encountered a language-barrier challenge, since nearly all that material is in Mandarin and unfortunately, I do not possess that competence. To overcome the language barrier, I have used Google Translate. According to a language-teachers blog from 2011, Google Translate started using a translation engine, called “Statistical Machine Translation” (henceforth SMT) a few years before the post was published on the blog. The SMT examines and compares enormous collections of text on the World Wide Web, that have already been translated by professional human being translators, to figure out what translations are valid. The blog holds, that Google Translate will keep on improving the more text the SMT examines (Davies, 2011). To find out how well Google Translate has improved I examined an academic article written by Groves and Mundt at a later stage. In the article, they highlight that although Google Translate has its flaws, the translations are thorough and even sometimes impressive. At the end of the article, they argue "that the Language Teaching profession needs to work with, not against, such technologies" (Groves & Mundt, 2015).

4. China’s Social Credit System

According to the Chinese State Council (henceforth the Council), the modern market

economy in China is currently undergoing a structural reform. They claim that building a SCS is an important step in this process since it will promote equal trust in society and reduce “social contradictions”, which are contributing factors to continue developing the country’s economic growth (Creemers, 2015). In the following section, I will present an overview of China’s SCS, for the reader to get an understanding of its general meaning and functions, by

firstly introducing the meaning of the system and its social functions and secondly, I will present the technological functions.

Introducing the system and its social functions

On June 14th_{, 2014 China’s State Council (henceforth the Council) introduced the Planning} outline, a comprehensive framework for China’s future Social Credit System. The Council outlines that the fundamental ground of the SCS must honour and involve “Deng Xiaoping Theory”, “Three Represents” and scientific technology as guidance in the progress of development (Creemers, 2015). The “Deng Xiaoping theory” is, in short, understood as “socialism with Chinese characteristics” (Moak & Lee, 2015: 91). While the “Three Represents” involves three characteristics which China currently stand for, including

“represents the development trends of advanced productive forces; represents the orientations of an advanced culture; and represents the fundamental interests of the overwhelming

majority of the people of China” (Kwan, 2002). According to the Planning outline, these guidelines will lead to the development of a harmonious socialist society, enhance the social development and socialist economic market, and improve the Chinese civilization (Creemers, 2015).

The Planning outline holds that the government shall choose different regions to carry out pilot programmes of the SCS from 2014 until 2020, to acquire knowledge of a functioning SCS before creating the complete national system which is expected to be launched at the end of 2020. During this period, according to the Council, the following objectives are expected to be established:

“Systems of fundamental laws, regulations and standards for social credit; having essentially built a credit investigation system that covers the entire

society credit on the foundation of sharing information resources, having essentially completed credit supervision and management systems, having a

relatively complete credit services market system, and giving full play to mechanisms encouraging trustworthiness and punishing untrustworthiness”

(Creemers, 2015).

Meanwhile, the Council strongly holds that the SCS must develop social functions that will increase China’s social and economic development, including, spreading knowledge of various levels of creditworthiness to citizens, make trustworthiness behaviour a norm; and enhance an environment where trustworthiness is honoured, and untrustworthiness is punished. The planning outline states that the SCS “shall allow the trustworthy to roam

everywhere under heaven while making it hard for the discredited (untrustworthy) to take a single step”. By using social credit information, multiple institutions will bring linked awards to the trustworthy and at the same time, the institutions will make sure that untrustworthy citizens cannot move an inch. To further encourage citizens good behaviour, governmental webpages post lists of trustworthy citizens and their good deeds and a blacklist involving untrustworthy citizens shameful behaviour (Creemers, 2015).

Technological functions

For citizens to know what trustworthy and untrustworthy behaviour involves, the government will, according to the Planning outline, give full play to television, newspaper, radio, internet, and social media, to guide citizens and companies in all kinds of activities building

trustworthiness. The planning outline also holds that these platforms shall publicly shame those who behave untrustworthy to enhance a trustworthy behavioural norm in society (Creemers, 2015).

As mentioned above, one of the objectives of the SCS is to create a credit investigation system. According to the Planning outline, this system is developed to collect, organize, store and operate credit information of individuals, companies and public institutions and will in turn hand out credit scores depending on their behaviour. The Council holds that it is important to ensure the accuracy of credit information of all part involved, to encourage trustworthy behaviour and shame those who violate the regulations. According to the Planning outline, these regulations are based on Chinese norms and standards (Creemers, 2015).

By now you might be wondering, who operates these credit investigation systems and how do they gather all this information of individuals, companies and public institutions. First of all, let me display an overview of China’s surveillance cameras. According to ABS News, China has 200 million Closed-Circuit Televisions (henceforth CCTV) cameras, which is 50% of all world's CCTV cameras, and they plan on expanding to 620 million CCTV cameras before the end of 2020. ABC News argues that the cameras include advanced techniques that monitor citizens behaviour. Furthermore, ABC News claims that this monitored behaviour is in turn matched with citizens private and online behaviour (ABC News, 2018).

According to Lui, a Ph. D student at the University of California, The Chinese government granted trial license to China’s eight commercial companies, including giant tech companies, on January 5th, 2015, to separately build and launch individuals’ social credit

rating systems that will score individuals behaviour. Lui’s holds that Alibaba, one of China’s largest technology companies and one of these eight companies, build an individual credit rating system called "Sesame credit score" and is the most used commercial credit system in China. He claims that Alibaba has over 800 million users on its two most popular platforms: Taobao and Ali-pay. According to Lui, none of the eight commercial companies got their license renewed when the trial was over at the end of 2017. He states that the reason for this was that “the People’s Bank of China (henceforth PBOC) officials criticized these companies for lack of data sharing across different platforms, conflicts of interests, and lack of

understanding of what should be considered as credit” (Liu, 2019). As a result of this, according to Lui, one single commercial individual credit scoring platform emerged at the beginning of 2018, named Baihang Credit. A government agency under PBOC, together with the eight commercial companies who did not get their license renewed, became the founders and shareholders of Baihang Credit (Liu, 2019).

5. Analysis

In the analysis I will investigate the technological elements through the lens of Clarke’s dataveillance theory in section 5.1. In the following two sections (5.2 and 5.3) I will analyse the social functions of the SCS by drawing on Lyon’s social sorting theory in section 5.2 and Foucault’s neoliberalism and subjectivity theory in section 5.3. To remind the reader of the theories used to analyse the material in the separate sections I will highlight the theories most important details in the beginning of each section. In addition to this, I will address the SCS’s human right implications throughout the whole analysis.

5.1 China’s surveillance system

Dataveillance, according to Clarke (1988: 499) “is the systematic use of personal data systems in the investigation or monitoring of the action or communication of one or more persons.” Mass surveillance, monitors and investigates large groups of people to identify individuals who behave in an exceptional (suspected) manner. It collects general information about people, including activities they engage in and of whom they associate with, through computer systems. (Clarke, 1988: 499-500). The mass surveillance techniques that signify dataveillance are, monitoring and collecting personal data, whether or not the individual is exceptional; comparing personal data with internal databases and norms; and profiling (identifying) individuals through various technical mechanisms (Clarke, 1988: 501). Clarke holds that these techniques can be found successful when conducted by a single technological

system but will significantly emerge if they are conducted by several systems. These systems can either be operated by a single organisation or various organisations concerned (Clarke, 1988: 504).

In the following sections, I analyse the SCS through a dataveillance lens, by highlighting, various systems operated by organisation(s); Blockchain; 5G; monitoring behaviour across platforms; and how the SCS identifies individuals.

Various systems operated by organisation(s)

According to the Planning outline, the Council acknowledges that they have to improve national and regional institutions ability to screen, record and collect behavioural information. To accomplish this, they will give full play to multiple credit associations and social

organisations, to create and advance the SCS (Creemers, 2015). Furthermore, the Peoples Republic of China (henceforth PRC) have decided to strengthen central innovations of

technologies and bolster fundamental research programmes to support this development, since they believe that scientific and technological innovations are the future in all areas of

innovation. An example of this is their decision to fully implement big data as their main strategic resource to bring about innovation in social governance (NDRC, 2016). In the following section, I will first discuss how big data plays an important role in the SCS, and secondly, I will examine Artificial Intelligence (henceforth AI) contributions to China’s SCS.

The Chinese big data department have calculated that 80% of the data available in China is centred in the government, due to this they must enhance the operation of

government data to develop the big data system the government desires. So far, the big data department together with big data administration and big data development bureau have established departments in various places across the country, to manage and collaborate big data resources nationwide. The big data department says that although the big data innovation has come a long way and many safety control systems have been implemented, it still faces some issues that need to be explained and systematized, including, amongst others, data regulations, data sharing mechanisms, unorganized data collection, issues of data application, and extensive data governance. The Chinese big data department holds “the goal of the big data system is to form data assets through the collection and exchange of a wide range of data sources, through data governance and development, and in accordance with the internal and external sharing needs of the government, thereby proving a comprehensive, efficient, and reliable data supply chain” (Big Data Department, 2019).

China’s National Information Centre has released a book about China’s technical innovations. It holds that big data is not the only technical innovation China is bolstering to enhance innovation in social governance, quite the opposite, China is strongly promoting and investing in further innovation of AI, Fifth Generation (henceforth 5G) and Blockchain (Ministry of Public Time, 2020).

Rui, a giant tech-company expert, wrote a column on china.org.cn at the beginning of 2020, claiming that AI and blockchain are the future leading technologies of scientific and technological innovation. Furthermore, he presents that China will become the leader of this game-changing and widely influential technology, due to the “Next Generation Artificial Intelligence Development Plan” (henceforth the Plan), which the Council developed in 2017. The column holds that this was a huge event in history of science and technology since it was the first AI plan ever developed. The Plan holds “that it will give full play to the role of AI technology in enhancing social interaction, promoting credible communication, facilitating the integration of blockchain technology and AI, establishing a new social credit system, and minimizing the cost and risk of interpersonal communication” (Rui, 2020). The Plan acknowledges that although AI is revolutionary, its development is uncertain and brings along new challenges. These challenges may impactregulations and social norms and involve issues such as infringing upon personal privacy and questioning international relations. The Peoples Republic of China Department of International Cooperation Ministry of Science and Technology understands that they need to be aware of and acknowledge these challenges brought to them through AI’s development (Department of International Cooperation MOST, 2017). To protect Chinese citizens, and enterprises from the interference of technological elements, the Standing Committee of the National People's Congress issued a Cybersecurity law in 2016, which came into effect 2017 (Cybersecurity Law of PRC, SFS 2017:53). Blockchain

In the following section, I will discuss Blockchains latest development: The Blockchain Service Network (henceforth BSN) and its functions. The BSN announced their official release on Weixin (WeChat) the world’s largest mobile app developed by Tencent, October 15th_{, 2019. The announcement holds that the network will enter a six month “internal beta} period” and will formally enter the global market on April 25th_{, 2020. Furthermore, the} announcement describes BSN as “a global infrastructure network, serving enterprise-level applications of blockchain. Committed to changing the current high cost of alliance chain applications, providing developers with a public blockchain resource

environment, and reducing the development, deployment, operation, maintenance, interoperability, and regulatory costs of blockchain applications” (BSN, 2020). According to an article published on Coindesk, a news site specialized on blockchain, the BSN will help companies and software developers to build blockchain-based applications. The article holds that this task used to be difficult, but with the help of BSN it will be as easy as assembling a Lego set. The project aims to supply technical support to coders, but the article criticizes this by claiming that the technological function of the system will most probably go beyond that goal. The article mentions that after the announcement of BSN, the Chinese government demonstrated different areas where its technological functions can be used, including city applications, collecting data, storing data and energy conservation.

According to a blockchain expert, the government has mainly been concentrating its resources on private blockchain projects, although it has cautiously and discreetly been engaging in public blockchain projects too. The expert believes that the government aims to track everything with this new technological network (Zhao & Pan, 2020).

Fifth Generation cellular network

In this section, I will discuss the functions of 5G and the worries for its future implications. On October 31st_{, 2019, the Chinese newspaper Xinhua wrote that three of China’s biggest} mobile operators announces their release of the ultra-fast 5G cellular network. The network is expected to have over 600million nation-wide subscribers by 2025, which accounts for about 40% of the global total according to Chen who is the head of the tech giant GSMA Greater China. Chen says that 5G is the beginning of a new cellular era with its tremendously fast wireless technology that can connect everything, including market players, services and actual things. Xinhua holds that 5G in combinations with big data and AI, will take revolutionary steps towards a digital economy and this will make a huge positive impact on China’s future economy (Xinhua, 2019). Gorman, a fellow for Emerging Technologies at the Alliance for Securing Democracy, displays a more sceptical view of China launching the 5G cellular network. According to her, some tech futurists worry about the 5G future, believing it will perform advanced unimagined functions which the world is not ready for yet. She holds that one of the reasons for this is that the Chinese National Intelligence Law requires 5G network suppliers to follow Communist Party of China’s (henceforth CPC) orders, to hand over whatever data they require and threatens to disrupt the network activity if they refuse to. She explains that Huawei, which is one of the tech-companies supplying 5G, is already suspected for “committing blatant corporate espionage” according to a U.S Justice Department

indictment from 2019 (Gorman, 2020). To summarize the accusation against Huawei, the Western District of Washington State accused Huawei of attempted theft of trade secrets, trade secrets conspiracy, one account of obstruction of justice and seven counts of wire fraud. The Indictment holds a detailed description of how Huawei attempts to steal trade secrets from T-Mobile USA, including Huawei offering bonuses to employees who managed to steal confidential information from other cellular network entities (Office of Public Affair, 2019). Monitoring behaviour across platforms

In the following section I will examine how the Chinese government monitors citizens behaviour across various platforms, by firstly discussing CCTV cameras and their

surveillance technique, secondly, I will examine behavioural data, and in the end Chinese citizens right to privacy.

A video made by ABC News In-depth finds that China has an extensive amount of CCTV cameras that are developing and getting “smarter” every day. “Smarter” in the sense that the body scanning, facial recognition and geo-tracking that AI surveillance technology can extract from CCTV cameras, will not only make people feel like they are being filmed, but will make them know that someone is watching every step they take. Furthermore, the video claims that some people are not aware that the personal data collected through the CCTV camera is measured against their private online and offline behavioural data in the SCS (ABC News, 2018). The videos understanding of the SCS surveillance techniques are aligned with Clarke's mass surveillance techniques, that monitor and collects personal data, whether or not people are exceptional, and compares personal data with internal databases (Clarke, 1988: 51), in this case, the behavioural data in the SCS.

A United States Human Rights report (Henceforth U.S HR-report) claim that behavioural data can include: “collected information on academic records, traffic violations, social media presence, friendships, adherence to birth control regulations, employment performance, consumption habits, and other topics”. The report criticizes China’s expansion of AI, by arguing that the system is already causing damage by monitoring speech and movement, not only through cameras but also through other electronics such as phone apps (Bureau of DRL, 2019). But the question is, how is all of this behavioural data collected? The Institute francais des relations international (henceforth Ifri) research centre gives us an example of this by referring to an article written by two employees at 100Credit (a social credit rating company recommending algorithms for various websites in China). According to the article, the company installs Application Programming Interface (henceforth API) on all

their client’s websites. The API collects personal behavioural data by monitoring websites user’s navigation habits, clicks, public data, purchase history and social credit blacklists. 100Credit then builds a profile on the users and sends personalized recommendations to them (Arsène, 2019).

At this point, you might be wondering if this mass data collection is a threat to Chinese citizens private life? China has signed, but not yet ratified the International Covenant on Civil and Political Rights (henceforth ICCPR), where article 17 holds that “no one shall be subjected to arbitrary or unlawful interference with his privacy, family home or

correspondence” (OHCHR, 1966). On Beijing’s (the city, henceforth I will refer to the city when mentioning Beijing) governments official homepage, it clearly states that social credit system development companies must take citizens privacy and measures towards systematic functions revealing individual’s personal data, into consideration before rolling out new systems (eBeijing, 2019a). Article 40 of the Constitution of the PRC holds that “the freedom and privacy of correspondence of citizens of the PRC are protected by law. No organisation or individual may, on any ground, infringe upon citizens freedom and privacy…” (Constitution of PRC, SFS 2018). A VICE News video claims "in China there is little protection on what information the government may collect on its citizens” (Vice News, 2019). Chen and Cheng present a similar understanding of Chinese citizens right to privacy. Their article holds that China’s national doctrine does not consist of any legal protection towards its citizens right to privacy against the intrusion of public authorities. This results in the government having free play to release Public Credit Information (PCI) about their citizens online and offline

behaviour (Chen & Cheng, 2017: 27). Depending on what region Chinese citizens live in, they have very little protection against regional government interference with their private life. Shanghai’s official credit homepage publishes an updated transparent list of citizens behaviour, called “The Shanghai credit behavioural list” (Credit Shanghai, 2019). Chen et. al, argue that a Chinese citizen cannot sue the regional government administrations for

publishing PCI, due to there is no national judicial law or regulation forbidding such behaviour. Although there are a few regional governments, including Jiangsu Province and Shaanxi Province, who have drafted a local regulation on citizens right to privacy against the intrusion of the authorities (Chen & Cheng, 2017: 29). When discussing Chinese law, Chen and Cheng’s article and the input from VICE News and Shanghai’s official credit homepage, I find that the right to privacy issue falls within the scope of the dangers dataveillance can produce. According to Clarke’s study, sometimes dataveillance lacks either prohibition or legal authority, or both of them, this may result in the individual being exposed to public

abuse and perhaps even being neglected the right to undertake some activities (Clarke, 1988: 507).

Identifying individuals

In the following section, I will discuss the Internet + AI plan and after that, I will display different examples of how AI identifies individuals through various social platforms.

The Ministry of Foreign Affairs of the PRC holds that the “Next Generation Artificial Intelligence Development Plan Issues by the Council” has developed a three years Internet + AI plan, enhancing the industrial development, and measures for applications and technology Robotic Development. During the last couple of years, this plan has made China become the world-leading within the technology of voice and visual recognition, but also developed advanced biometric recognition and intelligence monitors, and also evolved practical apps of Chinese information processing (Department of International Cooperation MOST, 2017).

The video made by VICE News on the SCS holds that AI appears everywhere, for instance at various fast food restaurant in China, citizens can order their food at a machine and then pay with their face. This system is called “smile-to-pay” and is a highly

technological camera which will scan the persons face and identify him/her. The camera will recognise the paying customer even though (s)he is wearing a wig or a lot of make-up. The video also states that many giant tech-companies in China, are developing video analysis systems. One example is Sense Time, who have developed a "Smart and Safe City" plan. This system can monitor everything from age to what colour pants a citizen is wearing, but also how long time a person spends at one place. Another one is Megvii, a tech-company who develops face recognition technology. They have developed a system named “SkyNet”, which allows cameras to identify criminals and their location. The camera system does this by screening individual faces and crosschecking the information against a criminal database. This identification information is directly forwarded to the closest police station who can track down the criminal at once. Furthermore, the video claims that so far, the “SkyNet” system has been involved in capturing 3000 criminals (VICE News, 2019). Credit China’s official homepage highlights that in the future, Chinese hospitals, plan on having facial recognition technological check-in machine. The technology would save time on procedures such as patient identification and contact with family members (Credit China, 2019a).

The U.S HR-report holds that video analysing systems may be the future and can most definitely be time-saving for many occupations such as for police officers and

medical staff, although the system has its faults too. The report argues that in May 2019 a security system that was monitoring a housing community in Beijing by using facial

recognition technologies leaked personal information about residence living in these houses. The personal data that was leaked contained sufficient information to make a detailed profile of the residence everyday life, including information of where the individuals went when they were not at home (Bureau of DRL, 2019).

5.2 Categorizing Chinese Citizens

Surveillance is a part of everyone’s everyday lives, most of us know it is there but we do not really think about it and we tend to comply with it. According to Lyon, surveillance is a matter of social justice, it sorts people into categories depending, for instance, on their worth or the level of "threat" to the society. He outlines that social sorting is when surveillance is involved with economic, social and political functions, which manages and influences people’s behaviour through an advanced computer system that collects and systematizes personal data (Lyon, 2003: 1-2). Furthermore, he holds that risk management programmes are a good example of a modern innovation which uses surveillance to sort people into categories and in addition to this, allows or denying people access to participate in social and economic processes, events and experiences (Lyon, 2003: 13, 163).

In the following sections, I will analyse the SCS through the lens of Lyon's Social Sorting theory, by discussing Risk management, how the system manages and influences behaviour, and how it categorizes “low” and “high” risk individuals. Risk management

The goal of the Planning outline is to “allow the trustworthy to roam everywhere under heaven while making it hard for the discredited to take a single step” (Creemers, 2015). The Council outlines that the SCS shall speed up the process in establishing a credit investigation system that carries out investigation operations by assessing credit information, that is lawfully collected, sorted and stores, from individuals, public institutions, enterprises and social organisations (Creemers, 2015). In the following section, I will first present a social credit-related risk management programme, and after that, I will discuss human rights issues that risk management projects have caused in Xinjiang province.

On Credit China’s official webpage, we also find an article about the establishment of an enterprise supervision program. The article reads, Shenzhen Qianhai Shenzhen-Hong Kong Modern Service Industry Cooperation Zone has established an

enterprise supervision platform, involving more than 170,000 enterprises. The platform divides corporate attributes and personal attributes into four categories (A, B, C and D) depending on their credit risk level. Lei, Vice President of Bairong Financial Services, holds that risk evaluation reports usually rely on enterprises credit data, but many small enterprises have not established credit records and can therefore not be analysed through a normal risk evaluation. This new platform evaluates both the risk factor of the corporate and also the personal credits of the owner, which allows risk evaluation reporters to evaluate dual

dimensions of enterprises who have credit records and a single dimension of enterprises who only have personal credit. AI and big data have been used to form this program that enables risk evaluations to combine corporate data with personal credit data of the owner (Credit China, 2019a).

In a video about China’s SCS, made by NBC News, human rights defenders strongly argue that surveillance technology is China’s new weapon used to control Xinjiang, a region in western China. The video holds that the PRC despite Xinjiang and view the region as a threat to the nation. Moreover, it mentions that this region is the home of Uyghur, the Islamic population of China. The human rights defenders continue to argue, instead of implementing a “normal” social credit pilot system in Xinjiang, residents are ranked within one of three categories, including trustworthy; average; and untrustworthy. All Han Chinese citizens are placed in the trustworthy category, which grants them, for instance, freedom of movement. All Uyghur Chinese citizens are ranked average, this category restricts travel and religious practices. If a Uyghur individual breach the restrictions, (s)he will fall into the category untrustworthy, although this mostly applies to men. If a resident is marked untrustworthy the government will detain the person in what they call an “education and training centre” also known, according to the human rights defenders, as China’s

concentration camps. A Uyghur man, interviewed in the video, holds that in these centres the detainee’s study Chinese political propaganda twelve hours a day (NBC News, 2019). The human rights defenders understanding of the situation in Xinjiang falls within the scope of Lyon's social sorting theory. In his theory, he acknowledges that risk management

programmes use surveillance techniques to sort their citizens into categories of high- and low risk and treats them accordingly (Lyon, 2007: 163).

A Human Rights Watch article outlines that the Chinese government uses both online and offline surveillance to monitor and analyse the behaviour of Xinjiang residents. According to the article, government officials rely on AI surveillance systems, including facial recognition and number-plate registration in the Xinjiang region and other regions

around the country, to observe and monitor Uyghur people’s behaviour. In addition to this, the article claims that the Xinjiang regional government collects biometric data from Uyghur individuals, which they store in searchable databases and match with collected data from online and offline surveillance (Roth & Wang, 2019).

The U.S HR-report presents two examples of how offline surveillance can occur in Xinjiang. The report holds the offline surveillance used by the State to monitor Uyghur citizens is something they call linked household” and “home stays”. The “double-linked household” program was developed many years ago in Tibet and involves dividing neighbourhoods into areas of 10 households, where each household is instructed to monitor their neighbours within the unit and report security issues to the government. The “home stay” program involves a government official staying in a Uighur’s family home to monitor their behaviour and report signs of “extremism” such as religious practices or “abstaining from alcohol and tobacco” (Bureau of DRL, 2019). The Human Rights Watch article and the U.S HR-report also fall in line with Lyon’s studies, which recognize that national security measures are programmed to categorize the personal data collected through various platforms, to classify how people should be treated depending on their “threat” to the State (Lyon, 2007: 162).

Manage and influence behaviour

“To make trustworthy people benefit everywhere and untrustworthy people restricted everywhere” will encourage citizens to enhance good behaviour (Fox, 2019) In this section, I will first analyse what China wishes to achieve through the SCS and how they plan to accomplish that, secondly, I will give an example of managing bad behaviour from Beijing’s official webpage, and at the end, I will discuss public shaming and some examples of that.

NBC News holds that the government has decided to develop the SCS to promote and influence trustworthiness behaviour and restrict untrustworthy behaviour (NBC News, 2019). To achieve this the Council outlines that the system shall develop an

environment that honours trustworthiness peoples and promote the benefits of good

behaviour, while untrustworthy behaviour shall be shamed. To accomplish this, the system will establish creditworthiness in every policy affecting citizens livelihoods, such as publishing information and guidance about the SCS; praise role models to inspire others of

their explicitly good behaviour; and link reward and punishment mechanisms across nation-wide departments (Creemers, 2015).

Beijing’s official webpage published an article holding that debates about bad behaviour on Beijing's public transportation have gone viral on the internet in China after people posted videos of passenger's shameful behaviour on the subway, such as eating food, promoting sales and using extra seats. (eBeijing, 2019b). A few weeks after this article was posted, another article was published on their webpage, claiming that due to peoples bad behaviour on Beijing’s public transport, the "Beijing Municipal Commission of Transport" has implemented a rule saying that passengers who participate in uncivilised behaviour on the subway (eating, drinking, occupying more than one seat and promoting sales) and who do not stop when asked to, will have their actions recorded in their credit records. If the violator wishes to correct his/her behaviour, (s)he can volunteer at a subway station. Exceptions from this rule are children and passengers with a medical condition (eBeijing, 2019c).

Similar to what the Planning outline mentioned above, the Ifri study shows that the SCS will establish a specific network for credit blacklists and take measures against those who have entered the blacklist, including reporting them to suitable sectors to deal with “disclosure” and “exposure” of the persons behaviour (Creemers, 2015). The Ifri study holds that it is known that good and bad reputation is considered to be the main key in getting people to behave in a better manner. In China, the SCS takes on this idea by publishing a blacklist of individuals and enterprises involved in untrustworthy behaviour (Arsène, 2019). Credit China and Credit Shanghai’s official webpages show that various regions in China publish a blacklist on their official credit website. The list is available for everyone to view and includes people’s names, identification number, addresses and the untrustworthy act the person has committed (China Jiangxi Net, 2020, Credit Shanghai, 2019). In addition to this, a video from RealLifeLore claims that public shaming occurs on public screens such as

billboards or cinema screens before the movie starts, showing the blacklisted person’s picture, name, id-number and address. The video also holds that Douyin, a Chinese app similar to TikTok, shows pictures of blacklisted people between their videos (RealLifeLore, 2020). Furthermore, human rights defenders from the NBC News video hold that China has

developed an app which tracks down blacklisted people and display their geographic position for other to see if they are surrounded by them (NBC News, 2019).

Categorizing “low” and “high” risk individuals

Fox has made a short documentary on the SCS. He holds that the SCS categorises Chinese citizens behaviour to find out who they can trust and who not. According to him, the human action that is monitored to categorise the individual involves for instance, who the person associate with; how many hours a day the person spends on social media, the person's financial score; how many children the person has; the persons involvement in volunteer work; the person's faith; and all other kinds of behaviour you can possibly imagine. He outlines that depending on a person’s behaviour, (s)he will gain or lose credits and be

rewarded or punished accordingly (Fox, 2019). Fox’s study of the SCS is in line with Lyon's social sorting theory that understands surveillance as a matter of social justice because it sorts people into categories depending on their worth or the "danger" they may cause society (Lyon, 2003: 1).

In this section, I will start by analysing how a person may lose points that can result in him/her becoming “untrustworthy” and what punishments that person may face. After that, I will discuss the same features, but from a trustworthy angle and at the end I will examine how norms encrypted in the SCS may infringe upon non-discrimination policies.

A RealLifeLore video on the SCS highlights some examples of behaviour that potentially may decrease one’s social credit score, including, spreading fake news on the internet; not visiting ageing parents frequently; cheating on online video games; posting anti-government messages on social media; playing an excessive amount of video gaming; paying bills late; participating in protests against the Chinese authorities; blasting loud music or eating on public transportation; booking a doctor's appointment or a hotel room without showing up; ordering take-out without picking it up; not sorting waste properly; walking your dog without a leash; and jaywalking (RealLifeLore, 2020). A “Memorandum of Cooperation on the Implementation of Joint Disciplinary Measures against Untrustworthy Persons (Fagai Caijin No. 141)”, passed in 2016, holds that blacklisted persons should be restricted to buy real estate; have limited access to residency in State-owned buildings; be banned from purchasing flight and train tickets; and be restricted in applying for financial loans (NPCIC, 2019). In addition to this, RealLifeLore claims that in June 2019, the government had denied 6 million high-speed train tickets and 26 million flight tickets to untrustworthy citizens (RealLifeLore, 2020).

The RealLifeLore video also displays examples of behaviour that might increase one’s social credit score: Donating blood; volunteer work; paying bills on time: taking care of elderly family members; publicly praising the Chinese government on social media; donating