From Punishment to Risk Identification: Rethinking the Mechanism for Determining “Serious Breaches of Trust” in China’s Social Credit Governance
This paper argues that determining "Serious Breaches of Trust" in China's social credit system should be reconceptualized from a punitive administrative act to a distinct form of risk identification, proposing a tripartite model of administrative acts and a corresponding risk-based governance framework to better address the system's predictive and preventive functions.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
In the modern world, governments and banks rely on credit systems to decide who is trustworthy enough to borrow money, run a business, or even travel. In many places, this system is built on market forces and data protection laws that focus on keeping records accurate and fair. But in China, the approach is different. The state has built a massive, unified system called the "social credit" system. Its goal is to manage society by tracking behavior, sharing information across different government departments, and applying consequences to those who break rules. A central part of this system is the label of "serious breach of trust." When a person or company receives this label, they face a cascade of restrictions, from being denied loans to being barred from certain jobs. For years, legal scholars have debated what this label actually is. Is it simply a statement of fact, like a doctor confirming a diagnosis? Or is it a punishment, like a fine or a prison sentence for a crime? Understanding the true nature of this label matters because the legal rules that protect people depend entirely on how we define the action. If it is a punishment, strict laws apply to ensure fairness. If it is just a fact, those protections might not exist.
A researcher named Sizhang Luo from Al-Farabi Kazakh National University has examined this debate and found that the current legal definitions are missing the mark. The paper argues that the determination of a "serious breach of trust" is neither a simple confirmation of facts nor a traditional punishment. Instead, the author proposes that it is a distinct type of action called "risk identification." In plain terms, this means the system is not looking backward to punish someone for what they did yesterday, but looking forward to predict what they might do tomorrow. It is a way for the government to sort people into different risk categories so they can manage future problems before they happen. The study suggests that because the current system tries to fit this new, forward-looking tool into old legal boxes designed for the past, it creates confusion, inconsistency, and unfairness.
The paper begins by showing how messy the current system is in practice. There is no single, clear national law that defines exactly what counts as a "serious breach." Instead, the rules are scattered across different regions and industries. In one city, failing to pay an electricity bill on time might get you labeled as dishonest. In another city, the same mistake might be ignored. In the financial sector, one bank might decide a person is a high-risk defaulter after 90 days of missed payments, while another bank waits 120 days. This lack of uniformity means that two people doing the exact same thing can receive completely different labels depending on where they live or which bank they deal with. Furthermore, the process for making these decisions often happens behind closed doors. People are frequently told they have been labeled dishonest only after the decision is made, with little chance to see the data used or to argue their case. Because the rules are so scattered and the procedures so opaque, the system lacks the stability and fairness that a modern legal system should provide.
The author then tests the two main ways scholars have tried to understand this label. The first idea is that it is "administrative confirmation," meaning the government is just stating a fact, like confirming someone has a driver's license. The paper argues this is wrong because the label isn't just about what happened; it involves a judgment about future risk. The government isn't just saying "you missed a payment"; it is saying "you are likely to miss payments again." The second idea is that it is an "administrative penalty," similar to a fine or a jail term. The paper rejects this too. A penalty is meant to punish a specific illegal act. But a "serious breach" can include things that aren't strictly illegal, like breaking a contract or even moral failings. Also, if it were a punishment, it would violate the rule against punishing someone twice for the same act, since many people are already fined for the original mistake before getting the label.
Having shown that the old definitions don't fit, the paper introduces the new concept: risk identification. This is a proactive tool used in the digital age. Instead of waiting for a crime to happen and then punishing it, the system collects data to spot patterns that suggest trouble is coming. When a person is labeled as having a "serious breach of trust," the system is essentially flagging them as a high-risk individual who needs extra monitoring or restrictions to prevent future harm. The goal is not to make them suffer for the past, but to protect the market and society from potential future losses. The author suggests that we need to add this new category to our understanding of government actions, creating a three-part system: confirming facts, punishing past crimes, and identifying future risks.
To make this system work fairly, the paper proposes a new framework for how these risk labels should be managed. First, there must be a single, unified set of rules created by national law so that the definition of a "serious breach" is the same everywhere. Second, the power to make these judgments must be carefully calibrated. Not every small mistake should trigger a serious label; only actions that pose a real, significant risk to the public should qualify. Third, the process must be transparent. People should be told why they are being flagged, what data is being used, and they must have a real chance to correct errors before the label sticks. Finally, the system needs a way to fix mistakes and allow people to move on. Since risk changes over time, a label should not be permanent. If a person corrects their behavior or if the data was wrong, the label should be removed, and their credit should be restored.
The study concludes that China's social credit system is shifting the way governments operate, moving from a model of punishing bad behavior to one of managing future risks. This shift is driven by big data and algorithms that administrative authorities increasingly rely on for continuous data collection, assessment, and automated scoring. However, the legal rules have not caught up to this new reality. By recognizing that "serious breach of trust" is a form of risk identification, the paper argues we can build a system that is both effective at managing risk and fair to the people it affects. It suggests that the future of law in the digital age will depend on our ability to create rules that protect people from the expanding power of predictive systems, ensuring that the drive for safety does not come at the cost of justice.
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