Demystifying The Chinese Social Credit System – Presentation for the Symposium on China’s Data Governance and its Impact on US-China Relations, hosted by the Carter Center China Focus

Introduction:

There is nothing new about public authorities using collected numerical info as a governing technology. Census has been a central governance tool throughout Ancient Rome and Imperial China. In fact, the need for keeping taxation records was a key historical exigence driving the invention of many earliest writing systems.

Throughout human history, public authorities have relied on collected numerical data as a tool for governance. This was evident with the census in Ancient Rome and Imperial China, where early writing systems were developed primarily for taxation records. The digitization of data and advancements in data science have revolutionized governance-by-data, making it continuously updated and more encompassing. The Chinese Social Credit System (SCS) is a testament to this evolution. Despite its significance, the SCS remains misunderstood, especially outside the Global North. Today, I aim to provide clarity on this topic, considering its implications on human rights and rule of law both within and beyond China, and shedding light on US-China relations. This talk will bring together relevant historical, rhetorical, socio-cultural and legal contexts to unpack the emergent structures of the Chinese social credit system and data governance experiments. By catalyzing greater open dialogue and critical inquiry on this thorny topic, this lecture seeks to advance the vision of The Carter Center and contribute to a deeper understanding of the past, present, and future of US-China relations.

Revisiting Basic Concepts

In today’s digital age, we often find the lines between “Governance of Data” and “Governance by Data” increasingly blurred. While the former refers to the protocols, standards, and policies that oversee and manage data’s secure and efficient use, the latter alludes to the application of data-driven methodologies for deliberation and making governance decisions. As technology becomes more intertwined with rule-making and rule-enforcement processes, distinguishing between these two becomes ever more challenging. This blending of boundaries underscores how crucial it is for all societies to recognize and adapt to the nuanced shifts in how data analytics is both managed and utilized in public messaging and governing frameworks.

The data market serves dual purposes. On one hand, it fuels data-driven innovation, spearheading the growth of data-capital. This innovation drives various sectors, from e-commerce to social media, using algorithms to tailor experiences based on user data. However, the flip side of this coin is the application of the same data for policy-making, shaping public discourse and public opinions, and regulating “disorderly” capital expansion. Remarkably, the same algorithms and datasets that platforms use for behavioral-targeted advertising might also serve law enforcement purposes. [1] This dual use of data brings to the fore ethical, legal, social, and human rights implications, especially when considering matters of privacy and public control.

Another area where this duality becomes evident is in the realm of credit scoring and risk assessment. [2] Traditionally, we’ve viewed credit scoring as a tool used by financial institutions to gauge a borrower’s creditworthiness. However, in our increasingly “algocratic” times, both private and public entities are leveraging these systems. While private companies and civil-society actors might use them to offer tailored financial products and advocacy toolkits, public and/or state-owned entities might utilize them to ascertain the financial health or trustworthiness of individuals or businesses, as in the case of the Chinese Social Credit System. This convergence raises questions about transparency, fairness, and the repercussions of shared financial evaluations across sectors.

Data, in its lifecycle, undergoes various stages: it is first collected from myriad sources, then synthesized and analyzed to extract actionable insights, and finally, it is used in decision-making processes, whether by businesses to enhance customer experiences or by governments for public welfare. Understanding this chain is pivotal in recognizing the true value of data and ensuring its optimal use. [3]

It’s notable that the data market is largely dominated by private firms. These corporations harness vast amounts of data, and the very same data infrastructure can support multiple uses, from marketing analytics to predictive modeling for urban planning. The versatility of data and its applications by these private entities emphasizes the need for comprehensive regulations to guide its ethical use. [4]

One of the driving factors behind the rapid expansion of data governance ecosystems is the cost-effective nature of data sharing. Notably, data sharing between private and public sectors is often low-cost and nonrivalrous, meaning that one entity’s use of the data doesn’t diminish its value or usability for another. [5] This economical sharing mechanism can foster collaboration but also demands rigorous oversight to safeguard against potential misuse or overreach.

Historical Pretext: Marketization and “Neoliberal Anomie” in Post-1980s China

In the aftermath of the 1980s, China experienced a significant shift towards marketization, characterized by a movement towards “neoliberal anomie.” This period saw rapid growth in markets and capital, a pace so accelerated that it began to overshadow the development of institutional structures. The immediate consequence was a series of evident institutional gaps.

During this transformative phase, China grappled with several institutional challenges. The financial sector, burgeoning with growth, faced an acute absence of robust risk management frameworks. Simultaneously, the country lacked a comprehensive system for assessing the creditworthiness of borrowers, which made financial lending and borrowing a risky venture. To exacerbate these issues, the judicial system found itself handicapped, often failing to enforce actions against credit defaulters. [6] This environment created a complex web of financial challenges that the nation had to navigate.

At the helm during this critical juncture was Deng Xiaoping, whose pragmatic political rhetoric played a significant role in shaping the regulatory trajectory of China’s economic reforms.  Perhaps the essence of Deng’s vision for China’s transformation is best captured in his famous quote from October 23, 1985: “We must allow a portion of areas and people to become wealthy first, to help drive growth in other regions and populations, thereby gradually achieving common prosperity.” [7] This statement epitomized his belief in the trickle-down effect of wealth and the need for a phased approach to achieving nationwide prosperity. Deng favored more flexible, ad hoc solutions, addressing the immediate problems that sprouted from the market reforms, instead of getting entangled in long-drawn, bureaucratic processes. An integral part of his strategy was the clear demarcation between the roles of the party and the government, known as 党政分开. [8] Deng also laid significant emphasis on enhancing the operational effectiveness, autonomy, and professional competence of various state organs, including State-Owned Corporations (SOCs). He believed that these entities needed to operate with greater efficiency to match the dynamic market pace. In line with his pragmatic philosophy, Deng encouraged local governments to undertake policy experiments, giving them the freedom to innovate and find solutions tailored to their unique challenges. [9]

Expansion of Data-Capital in China during the 2000s – 2010s

The 2000s to 2010s marked a significant era for China as it saw an unparalleled expansion in data-capital and digital public sphere. This period was characterized by the rise of technology firms that sought to address the institutional gaps that had previously been identified.  Leading tech companies, such as Alibaba, introduced pioneering solutions like Sesame Credit—a system designed to assess and score individual creditworthiness. [10] Likewise, Tencent ventured into the realm of personal finance and investment through its mobile phone platforms, providing a seamless interface for users to manage and grow their wealth. [11]

However, as these private entities became increasingly influential, the distinction between public and private data governance regimes began to blur. This conflation of governance roles, rhetoric, and responsibilities between public and private entities led to unique challenges and phenomena. One such development was the emergence of what can be termed the “fifty shades of gray banking industry.” This saw a shift from traditional organized crime syndicates to ill-regulated provincial banks that often operated with the tacit approval, if not outright blessing, of local governmental bodies. [12] Their operations, though questionable, highlighted the complexities of China’s evolving financial landscape. A more recent and still under-studied trend that underscores this blurring of lines is the crypto-mining craze in China which took off less than half a decade ago. The surge in cryptocurrency mining operations, often powered by cheap local energy sources, has led to suspicions of local government involvement, either through direct partnerships or a deliberate turning of a blind eye. [13] Compounding these issues is the People’s Bank of China (PBOC) system and its limited regulatory toolkit—especially when contrasted with its U.S. counterparts. [14] The PBOC, tasked with overseeing the country’s monetary policy and financial institutions, often found itself grappling with challenges that were novel not just for China but for the world at large.

Transnational Contexts and Their Influence on Chinese Policy

Placing China’s economic reforms within the broader transnational context is critical for a comprehensive understanding. Deng Xiaoping’s market reforms, a cornerstone of modern Chinese economic transformation, didn’t emerge in isolation. In fact, they were part of a global wave of neoliberal marketisation policies that took shape in the aftermath of the 1973 energy crisis. [15] To truly grasp the nuances of these reforms, one must draw parallels and understand the rhetorical and macro-economic connections between the economic philosophies championed by Deng, often referred to as Deng Xiaoping-nomics, and other global economic movements of the time, such as Reaganomics in the U.S. and Thatchernomics in the U.K. [16] These movements, though distinct in their localized implementations, shared a broader global vision of deregulation, privatization, and open markets.

Similarly, the more recent tightening of the tech regulatory environment in China cannot be viewed as an isolated phenomenon. This shift is part of a broader global response to the challenges and opportunities ushered in by the Marketization of Data wave that followed the Dot Com bubble of the 1990s. [17] This era witnessed a surge in disruptive technological innovations. Breakthroughs in distributed computing, machine learning, and the convergence and decentralization of technology played pivotal roles in reshaping global data landscapes. Moreover, both the U.S. and China adopted similar “data sovereignty” rhetoric and policy countermeasures. Legislative initiatives like Stop Online Piracy Act (SOPA), PROTECT IP Act, and PATRIOT Act the U.S. are not structurally different from China’s Great Firewall (GFW) and Cybersecurity Review legislations in the sense that they represent both countries’ policy responses to the “data sovereignty” problem. [18] The ongoing US-China “chip war” also emerges from this shared rhetorical exigence. [19]  The connected policy approach extends beyond just sovereignty measures; both nations experimented with governance “of” and “by” data. Examples include the Bio-Surveillance & Human Identification at a Distance programs in the U.S. (e.g., TIA and NSA PRISM) and China’s Golden Shield and Tianwang projects. [20] The shared vision sees the government not just as a regulator but also as a platform, leveraging technology for governance.

Amidst this backdrop, one aspect that emerged with undeniable prominence was the issue of communication and user rights. As data became a dominant force in geopolitics and economics, ensuring that users had rights and avenues for communication became a central concern for policymakers and technocrats alike. The onus shifted towards establishing frameworks that protected users while facilitating the free flow of information in the digital age.

Pressing Issues within the Chinese Tech Regulatory Environment

As the 21st century progresses, China continues to grapple with its regulatory positioning, especially in comparison with countries like the U.S. A notable observation is that China is still in a phase of regulatory catch-up with its western counterparts. For instance, the much-discussed Chinese Social Credit System is, at its essence, a strategic effort to address long-standing institutional voids. Historically, China has faced challenges in creating a robust personalized creditworthiness assessment system. Additionally, there have been deficiencies in the enforcement measures against those defaulting on credit. [21] The Social Credit System, with its multifaceted approach, seeks to address these gaps by providing a more holistic view of individual and corporate trustworthiness.

Navigating the tech regulatory landscape in China reveals another consistent challenge: the alternating rhythms of regulatory approaches. China has exhibited a tendency to oscillate between periods of laissez-faire self-regulation and intense state intervention. This inconsistency can be attributed to China’s historical over-reliance on ad hoc measures and targeted crackdowns. The decentralized nature of Chinese policy making often leads to reactive solutions, responding to issues as they arise rather than anticipating them. [22]

Further complicating matters is the blurred line between policy and law in the Chinese administrative landscape, a phenomenon that can be summarized as a “solution first, law-up later” approach. [23] Typically, when a challenge emerges, the response is initiated by political directives from the central authority. However, these directives are often framed in vague and formalist rhetoric, leaving ample room for interpretation. [24] This ambiguity often leads to multiple overlapping projects initiated by various public organs, both at the central and local levels. Instead of streamlined solutions, what often emerges is a patchwork of initiatives, each addressing facets of the problem but rarely presenting a cohesive solution.

The culmination of these factors creates a data governance environment in China that can best be described as unpredictable. Firms often grapple with unclear compliance requirements and experience uneven enforcement measures. This unpredictability has also sowed seeds of mistrust between public and private actors, making collaboration and consensus even more challenging. It’s clear that for China to move forward effectively in the realm of data governance, a more streamlined and predictable regulatory environment is imperative. [25]

The Great Fire Wall (GFW) Case 

The year 1994 marked a significant milestone for China as the internet became accessible to its general public. [26] However, this advancement wasn’t without challenges. Initially, there was a noticeable void in the cybersecurity framework. China did not have a structured cybersecurity policy or law until 1997, leaving a substantial period where the digital realm was largely ungoverned and exposed to potential vulnerabilities. [27] The introduction of the 1997 Cybersecurity law was indeed a step forward, but it was not a panacea. Despite its inception, the law remained mostly dormant in terms of active enforcement for several years. It wasn’t until 2002 that the digital landscape began to see tangible shifts, marked by the operational commencement of the “Great Firewall” (GFW).

However, it’s essential to understand that the GFW wasn’t a singular, centralized project. Instead, it emerged as an amalgamation of multiple, often overlapping, cybersecurity initiatives spearheaded by a variety of central and local public organs. One of the most prominent among these initiatives was the Public Security Ministry’s “Golden Shield Project.” [28] Parallel to this, the Cyberspace Administration also launched its cybersecurity initiatives. [29] Further, a slew of similar projects were initiated by various other ministries and administrative bodies, including the Ministry of Industry & IT, State Security, Finance, Commerce, People’s Bank of China (PBOC), Administration for Market Regulation, Radio & TV Administration, Securities Regulatory Commission, Administration of State Secrets Protection, and State Cryptography Administration. [30]  Each of these projects added layers to the evolving GFW.

The continuous development and refinement of the GFW underscored a recurring trend in China’s approach to governance: iterative policy implementation often preceding formal legislation. This pattern was evident yet again when the comprehensive Cybersecurity Review legislation was only passed in 2021. [31] This legislative action, coming after years of policy implementation, reaffirmed the “policy implementation before legislation” challenge discussed earlier.

Case Study #2: Exploring the Evolution of China’s Social Credit System

The genesis of China’s Social Credit System (SCS) can be traced back to the tumultuous yet economically uplifting period between the 1980s and 2000s. As mentioned earlier, this era, which witnessed the unfolding of market reforms and later the burgeoning of China’s digital economy, was plagued by a pervasive trust crisis, colloquially termed “失信” (loss of trust). The societal and economic transformations of the time amplified the challenges of trust and accountability. Recognizing the need for intervention, in 2014, the Central Committee and State Council issued a crucial political directive: the “Outline of the Social Credit System Construction Six-Year Plan.” [32] This was an attempt to re-calibrate societal trust, especially in the age of big data. The plan’s inception was a long-awaited answer to the trustworthiness crisis that had persisted for decades.

The road to establishing the Social Credit System wasn’t straightforward. The system’s formulation underwent multiple phases of internal and external consultations. Moreover, policy experimentation at local governmental levels added layers of complexity and variations to the evolving system, demonstrating the decentralized nature of Chinese policy-making. The SCS wasn’t built in isolation. It drew from existing systems and frameworks. Predecessors to the SCS included the China Organization Data Service under the aegis of the State Council, the Credit Reference Center managed by the People’s Bank of China (PBOC), and a notable blacklist of untrustworthy entities maintained by the Chinese Supreme Court. Each of these played a role in shaping the contours of the emerging SCS. [33]

A defining moment in the SCS’s iterative development came with President Xi Jinping’s speech on May 6, 2016. He articulated the need to “Establish a national population database, a unified social credit code, and related real-name registration systems.” [34] Xi emphasized enhancing the SCS while also highlighting the importance of mental health and counseling services, areas typically considered outside of the narrowly defined financial credit domain, thereby giving a broader rhetorical context to the SCS’s intended reach and impact.

The development of the SCS wasn’t restricted to a singular public entity. Many party and state organs lent their expertise to its formation, including the National Development & Reform Commission (NDRC), the Discipline Inspection Commission, the Propaganda Department, the Political & Legal Affairs Commission, and even the Central Steering Committee of Spiritual Civilization Construction played roles as members of the “Joint Chiefs Conference” in sculpting the system’s features. [35]

While the SCS has been instrumental in many ways, it hasn’t been without controversies. One of the most debated components is the “Joint Sanctions of Discredited Judgment Defaulters,” which has sparked discussions and critiques both within and outside China, especially for its proposed punitive measures against family members of chronic credit defaulters. [36]

Unique Features of Chinese Data Governance Policy Making

At the heart of the Chinese data governance policy-making process is the practice of Consultative Deliberation. This approach emphasizes what’s termed as “Collaborative Governance” (多方共治) and it’s grounded in the principle of “Inclusive Prudence” (包容审慎). [37] The idea is to bring together various stakeholders in a joint effort to address and manage issues, ensuring a balanced approach that is both embracing and cautious.

An interesting practice embedded in China’s policy-making process is “Qujing” (取经). Historically used to describe a journey in search of sacred scriptures, in this context, it refers to the active pursuit of foreign expertise to inform and shape domestic policies. By looking outwards and drawing upon global know-how, China seeks to refine its own governance strategies.

The Chinese policy-making framework is strengthened by a formalized internal political consultation process. Various political parties engage in deliberative dialogues within the structure of the Consultative Conference, ensuring diverse viewpoints are considered in policy formulation. [38] The emphasis on inclusivity extends beyond internal mechanisms. The policy-making process mandates a 30-day public consultation period. This external expert consultation ensures that a wider array of voices, including those from the public, are part of the policy evolution.

As highlighted earlier in our discussion, the post-Deng era iterative policy-making process, despite certain challenges, provides a unique advantage. This method, characterized by ongoing adjustments and adaptations, makes the governance framework more attuned to the rapidly shifting needs and dynamics of the public sphere.

Another defining feature of Chinese governance is its normative conception of law. Unlike some systems that emphasize the purely juridical facets of governance, the Chinese approach leans on a more moralistic conception of public authority. This implies that governance is not just about enforcement but also about setting moral standards and values for society. As suggested by Marcelo Thompson, that the conception of justice based on the SCS enables and unifies accounts of corrective and distributive justice, into a broader conception of normative framework of justice, centered on reasons articulated in the information environment. [39] That said, it remains an unresolved question in terms of preservation of individual autonomy and privacy.

Lastly, there’s been a discernible shift in rhetoric. China is increasingly leaning on its rich cultural legacy, integrating traditional Confucian values into modern governance paradigms. This is especially evident in areas related to AI regulation, where age-old wisdom is being merged with cutting-edge technology to create a holistic governance framework. [40]

In conclusion, the trajectory and intricacies of Chinese data governance policy-making reveal a deeply layered and iterative process. Rooted in historical practices, guided by consultative deliberation, and informed by both domestic imperatives and global expertise, China’s approach is uniquely adaptive and responsive. Despite the challenges posed by rapid technological advancements and the ever-evolving landscape of data management, China nonetheless seeks to bridge past wisdom and future vulnerabilities. The incorporation of traditional values, like Confucian principles, into contemporary governance further underscores both an intrinsic contradiction within the Chinese modernization enterprise, and a commitment to a holistic, morally-grounded, and culturally resonant policy framework. As we continue to navigate the digital age, understanding such diverse governance paradigms becomes crucial, offering lessons and insights for global data governance imperatives.