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The folks over at the European Chinese Law Research Hub
(with thanks to Marianne von Blomberg, Editor ECLR Hub, Research
Associate, Chair for Chinese Legal Culture, University of Cologne) have
posted a marvelous summary of a new paper by Angela Huyue Zhang (Associate Professor of Law at The University of Hong Kong and Director of the Phillip K. H. Wong Center for Chinese Law), ‘The Promise and Perils of China’s Regulation of Artificial Intelligence’ .
The paper is highly recommended. One of its most interesting features is the way in which Professor Zhang is able to weave the trajectories of tech regulation with the premises and organizing structures of the political-economic system in which it is developed. And that points to the fundamental challenge of tech regulation for both Marxist-Leninist and liberal democratic systems--how does one weave together--or disentangle--regulatory structures where the state, as Professor Zhang writes "has multiple roles: it simultaneously acts as a policymaker, an investor, a supplier, a customer, and a regulator."
The answer, or perhaps better put, the path, will be determined by the ordering premises of a socio-political-economic system.While there might be convergence in effect at the operational level, the modalities toward that convergence will follow very different routes and must, at their limits, suggest as much points of divergence, as of convergence. Of course, states have been consuming what they regulate for a very long time; states have been investing in favored and seeking to suppress disfavored activity for even longer; and states by nature, have always been a supplier of a very specific set of goods--order and and enforcement. They create, build, clean, watch, order, and protect the spaces (markets, and preferred forms and modes of social relations) within which it may produce policy, invest, supply, consume and regulate. Nonetheless, AI regulation specifically, and tech regulation generally, present a transformative challenge that occurs infrequently in the development of the human social condition. It is among those technologies that can transform not just its suppliers investors, consumers, but also transform its policymakers and regulators by changing the field within which all social actors operate.
Professor Zhang correctly notes China's pioneering role as a policymaker and regulator of the investment, consumption, and supplier of tech, generally, and AI now more frequently. That is inevitable given the core premises of the Chinese Marxist-Leninist political order. Perhaps earlier than most, and no doubt with the usual and now common admixture of delight, desire, and fear, that characterizes regulatory approaches to AI--that is with the overall desire to subsume AI within the premises, parameters, operating style, and structural division of authority of a social-political-economic system against the possibility of uncontrolled transformative effect. Professor Zhang provides an excellent analysis of its details in a policy area that remains very much a work in progress.
Professor Zhange considers several key issues. The first is between regulatory scope, thrust, consistency and the cultivation of innovation in a field that is dependent on innovation but where innovation itself may threaten the contemporary operation of the regulatory structures. Professor Zhang reminds us that the controversies and internal conflicts may be as intense in China (though less transparent to outsiders) as it is in liberal democratic systems. One is reminded here of the intensity of that debate by the consequences of tech crackdowns. That, in turn, one can suppose, is to some extent the face of the deeper problem of regulatory philosophy within Marxist-Leninist operating principles that were highlighted in Jack Ma's now (in)famous remarks of 2020 in Shanghai (see here). Those issues have been at least temporarily resolved at the level of high policy but its repercussions at the operational level remain uneven. Professor Zhang correctly notes that current operating policy: "China has adopted a bifurcated approach to AI regulation: strict
information control juxtaposed with industry-friendly regulation." Underlying that is a deeper choice--the need to channel innovation by and through administrative supervision aligned to core governmental policy objectives, at the same time ensuring that innovation does not transform those structures of administrative supervision without the consent of the vanguard (and under its leadership). The European Union has also advanced a similar regulatory approach with liberal democratic characteristics (here). And, indeed, as Professor Zhang suggests, China's regulatory approaches at some level (as a function perhaps of its dual circulation policy) have to acknowledge if not align to some extent with those of other blocs.
I am cross posting the essay below. The original ECLRH post may be accessed HERE. And as a plug for the marvelous work at the European Chinese Law Research Hub: if you have observations, analyses or pieces of research that are not publishable as a paper but should get out there, or want to spread event information, calls for papers or job openings, or have a paper forthcoming- do not hesitate to contact Marianne von Bloomberg.
Enabling, Coordinating, Waiving Responsibility? AI Regulation with Chinese Characteristics
A new paper by Angela Huyue Zhang
In addressing artificial intelligence, the Chinese government has multiple roles: it simultaneously acts as a policymaker, an investor, a supplier, a customer, and a regulator.
In recent years, China has emerged as a pioneer in formulating some of the earliest and most comprehensive legislations regulating recommendation algorithms, deepfakes, and generative AI services. This has left the impression that China has stood at the forefront as a global leader in regulating AI. Matt Sheehan, a highly-regarded expert in Chinese AI policy suggests that the U.S. can gain valuable insights from China’s approach to AI governance. Industry observers therefore view Beijing’s regulatory approach as a potential obstacle to Chinese innovation. Such concerns are not unwarranted. In 2020-2022, China undertook a sweeping crackdown on its tech firms. The erratic nature of Chinese tech policy has unnerved investors, precipitating severe and unintended consequences of deterring investment and entry into the consumer tech business.
However, this perception that China has stood at the forefront in regulating AI fails to account for the intricate dynamics of the Chinese political economy. Authoritarian states face a dual-challenge with emerging technologies, as these technologies can empower civil society on one hand, while enhancing government surveillance capabilities and strengthening social stability on the other. Furthermore, technological advancements are crucial for economic growth and national competitiveness. To balance the need for stability and the desire to foster innovation, China has adopted a bifurcated approach to AI regulation: strict information control juxtaposed with industry-friendly regulation. This approach keenly reflects the complex utility function of the Chinese Communist Party, who seeks legitimacy through multiple sources including growth, stability, and nationalism.
Yet striking a balance between regulation and innovation is far from easy. The Chinese government assumes multiple roles in the AI ecosystem as a policymaker, an investor, a supplier, a customer, and a regulator. Given the government’s extensive involvement, it lacks a strong commitment to regulate the industry. Moreover, although AI can pose many social harms, they have not yet evolved into immediate threats to social and political stability. AI safety risks remain speculative, despite warnings from experts. The Chinese government also recognizes the economic benefits AI promises, amidst the intense Sino-US tech rivalry. The tightening of US export restrictions, which hinder Chinese AI firms’ access to advanced chips, have only intensified this competitive pressure, thereby diminishing the government’s incentive for strict regulation.
The Chinese government also faces significant constraints in imposing strict regulation on AI. China’s tech crackdown in 2020-2022 has demonstrated that harsh regulatory measures can generate strong repercussion in the market. Since early 2023, the Chinese economy has entered into a slump. The government’s focus has thus shifted towards revitalizing the economy and boosting market confidence. Consequently, despite appearances of proactive intervention, Chinese regulators have focused on fostering AI growth. The regulatory rules being adopted have sent strong pro-growth signals while attempting to facilitate stakeholder coordination to advance AI development. This close integration of industrial policy and law is a defining feature of Chinese AI regulation.
Understanding the nuances of China’s AI regulatory strategy is crucial not only for predicting the trajectory of its technological development but also for assessing its implications on the global tech rivalry. Major jurisdictions including both the U.S. and the EU are actively exploring the establishment of a comprehensive AI regulatory framework, as exemplified by the AI Act and Biden’s executive order. Leading US AI firms are involved in various litigations and face mounting pressure to negotiate licenses with media for the use of their content as training data. In contrast, China’s relatively more relaxed regulatory environment may offer its AI firms a short-term competitive advantage over their EU and U.S. counterparts.
Meanwhile, China’s approach could give rise to serious regulatory lag. This situation is aggravated by China’s weak market conditions, poor legal institutions, and the tightly coupled political system, potentially leading to latent risks that could escalate into AI-related crises. For example, the Chinese government is invigorating a “whole of society” approach to push forward AI development without necessarily taking effective precautionary measures. Under such a command-and-control strategy, by the time the full impact of AI harms become apparent to top policymakers, it could be too late for effective reversal or mitigation. This dynamic complexity of China’s AI regulation therefore underscores the urgent need for increased international dialogue and collaboration with the country to tackle the safety challenges in AI regulation.
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