ssrn-5874043

1 China and Regulation of Artificial Intelligence Mingwei Liu, Rutgers University & Yi Sui, Renmin University of China Abstract China has emerged as a global leader in regulating artificial intelligence (AI). By analyzing major national AI-related policies and regulations, we argue that the Chinese state adopts an instrumental approach to shaping AI policies. This approach seeks to balance efficiency and security, influenced by multiple stakeholders, including tech firms, trade unions, intellectuals, journalists, workers, and the public, as well as emerging global norms of AI governance. Furthermore, China’s regulatory approach to AI is extending its global influence through AI infrastructure projects in “Belt and Road” countries, advocacy in international forums, and its participation in international technical standards bodies. -- 1 of 24 -- 2 Introduction China's progress in Artificial Intelligence (AI) in the past decade has been remarkable. It has rapidly become a global leader in AI research, producing a significant volume of publications and patents. Additionally, China has excelled in the commercialization of AI, particularly in sectors such as speech and image recognition, and more recently, in open-source large language models (LLMs), benefiting from DeepSeek’s breakthrough in early 2025 that placed Chinese LLMs squarely at the global frontier. Similarly remarkable, the country has distinguished itself by introducing some of the world’s earliest and most comprehensive regulations concerning algorithms, deepfakes, and generative AI, thereby establishing itself as a frontrunner in AI regulation among other jurisdictions. How does China regulate AI? What are the roles of various stakeholders in China’s AI-related policymaking? And how will the Chinese approach to regulating AI influence global AI governance? This paper seeks to answer these questions through an examination of over 200 major national-level AI-related policies and regulations till October 2025, alongside existing studies, reports, and interviews with Chinese AI and platform companies, trade unions, workers, scholars, and government officials. We argue that the Chinese Party-State adopts an instrumental approach in crafting and implementing AI policies and regulations. This approach aims to strike a dynamic balance between the objectives of technological development and the economic, social, and political security of the Party-State. Yet, although China takes a top-down approach in AI regulation, multiple stakeholders, including tech firms, trade unions, intellectuals, journalists, workers, and the public, have found their respective channels to influence the regulations. Nonetheless, the Party-State’s predominant focus on economic growth, social stability, and political security renders workers vulnerable to the influence of AI, tech firms, and the overarching authoritarian legal and political framework. Furthermore, China’s AI regulation is shaped by emerging international norms while also seeking to influence a still-fragmented global AI governance landscape. Its efforts are carried out through the export of AI-related digital infrastructure via the Belt and Road Initiative (BRI), advocacy in international forums, and participation in international technical standards bodies. Yet China’s influence remains limited and context-dependent, constrained by geopolitical tensions, differing regulatory philosophies, and uneven acceptance of Chinese standards. The Chinese Model of Permissive and Restrictive Regulation of AI Many observers attribute China’s remarkable AI development to the strong supportive policies of the Party-State. Therefore, China’s shift toward comprehensive and, in many aspects, stringent AI regulations at the national, industry, and local levels, alongside a crackdown on its AI tech giants since the late 2010s, has come as a surprise to the world. Does the Party-State intend to stifle China’s innovation? Will AI be completely controlled and monitored by the Party- State? To fully understand AI governance in China, it is crucial to consider the AI policies and regulations within the context of China’s evolving political economy. -- 2 of 24 -- 3 Over the past several decades, China's economic model has evolved from a labor-intensive, export-oriented manufacturing base to a technology-driven, service-oriented structure. In 2024, the service, industrial, and agricultural sectors contributed 56.7%, 36.5%, and 6.8% to the Gross Domestic Product (GDP), respectively (National Bureau of Statistics of China (NBSC), 2025). These figures suggest that China is transitioning into an industrial or even post-industrial society. Furthermore, China has developed the world's second-largest internet economy and is home to the largest number of internet users globally—approximately 1.08 billion as of June 2023 (Xinhua, 2023). However, the development of the digital economy has also dramatically increased the size of the gig economy, with an official estimate of approximately 240 million workers by 20241, among whom 84 million are in new forms of employment, such as food delivery riders, couriers, and ride-hailing drivers2. While market mechanisms have increasingly influenced resource allocation, the Party-State maintains a pivotal role in economic coordination, a role that has even strengthened under Xi Jinping's leadership. Furthermore, the authoritarian political structure remains in place. The concept of a “socialist market economy” in China is therefore characterized by a dualism of coordination, where bureaucratic and market forms of coordination coexist. Since the economic reform, the Party-State has consistently sought to balance two interrelated but inherently contradictory objectives: economic development and political and social stability (Lee, 2007; Zhao, 2004). In particular, the Party-State seeks legitimation through its embrace of authoritarian legality (Whiting, 2023). While the concept of authoritarian legality is debated, it is particularly relevant here, as it is both instrumental and real (Gallagher, 2017). The Party-State utilizes the law to promote economic growth and exercise social and political control (Lee, 2016; Moustafa and Ginsburg, 2008). Authoritarian legality plays a crucial role in structuring Chinese labor markets and employment relations, guiding workers to utilize the law and courts to defend their rights and interests (Gallagher, 2017; Liu and Kuruvilla, 2017; Liu, 2020). It similarly shapes AI development and governance in China’s workplace and society (Liu et al., 2024). We argue that the Party-State uses AI policies and regulations instrumentally to achieve its twin objectives of technological development and security. To balance these potentially conflicting objectives, many policies and regulations are intentionally vague or ambiguous, subject to flexible interpretations and selective, lax enforcement. This approach to AI governance is reflected in the term "inclusive and prudent regulation," first introduced by the late Premier Li Keqiang in his Report on the Work of the Government on March 5, 2017, and later adopted as a regulatory principle for the broadly defined new economy, including AI. According to Li, "inclusiveness" means adopting a tolerant attitude towards new business models where the unknowns outweigh the knowns, as long as they do not cross safety baselines. "Prudence" has two meanings: first, when a new business model is emerging, and its impact is unclear, it should not be immediately and strictly regulated, but rather given a "period of observation." Second, it is crucial to adhere to safety baselines and take strict regulatory measures against actions that 1 https://www.zyshgzb.gov.cn/n1/2025/1016/c461137-40583436.html 2 https://www.sohu.com/a/676416856_121687414. -- 3 of 24 -- 4 involve financial fraud, deception, counterfeit products, infringement of intellectual property rights, etc., regardless of whether they occur in traditional or new business models, and to resolutely enforce the law against such practices. Article 3 of the Interim Measures for the Administration of Generative Artificial Intelligence Services (2023) specifies the "inclusive and prudent" regulatory principle of AI: "The state is to adhere to the principle of placing equal emphasis on development and security, merging the promotion of innovation with governance in accordance with law; employing effective measures to encourage innovation and development in generative AI, and carrying out tolerant and cautious graded management by category of generative AI services." Below, we will examine in detail the major AI policies and regulations that serve the Party-State’s objectives of efficiency, economic security, social stability, and political/public security (see Table 1). While we focus on the major national-level policies and regulations, various industry and local-level AI policies and regulations, in principle, maintain consistency with the national ones. Insert Table 1 about here Supporting and Regulating AI for Efficiency Believing that the information and communication technology (ICT) sector is pivotal for China’s economic growth and technological advancement, the Party-State began fostering a supportive policy environment for internet companies as early as the late 1990s. This effort intensified after the 2008 global financial crisis, when the internet was designated as a national pillar industry essential for the country’s industrial upgrading and "indigenous innovation" (Lei, 2023; McKnight et al., 2023). Around the mid-2010s, the Party-State began to support AI development, as evidenced by national policies such as Made in China 2025, the Guidance of the State Council on Vigorously Advancing the "Internet Plus" Action, the 13th Five-Year Plan for the National Economic and Social Development, the Robotics Industrial Development Plan (2016-2020), the "Internet+" and Artificial Intelligence Three-Year Action and Implementation Plan, and the Intelligent Manufacturing Development Plan (2016-2020). In 2017, China published the Development Plan on the New Generation of Artificial Intelligence, which positions AI as the primary driver of China’s industrial upgrading and development, outlines its strategy to center AI in its socio-economic development efforts, and articulates its ambition to become a global leader in AI with an industry worth about $1.38 trillion by 2030. Since then, various support policies and regulatory tolerances have been implemented to promote AI development, focusing on talent, data, capital, market, and hardware. Talent Since the late 1990s, China has been actively developing a high-skilled workforce through its education and training policies, particularly achieving notable results in the quantity of science and engineering higher education graduates (Liu and Finegold, 2017). To cultivate and recruit talented AI researchers, various education and training policies adopt a dual "training" and "gathering" approach. On the training front, China takes a long-term view to nurturing AI talent by integrating AI education into the curricula of primary, secondary schools, vocational -- 4 of 24 -- 5 schools, and universities. Efforts include enhancing teachers’ AI skills, incorporating AI into national specialized enrollment plans for urgently needed talents, and increasing investment in educational informatization. There is also a strong emphasis on strengthening international exchanges and cooperation, encouraging joint support from national funds, financial sectors, and societal capital for the development of the AI discipline and talent cultivation. This includes training in both foundational AI theories and interdisciplinary "AI+X" applications, as well as internationalized talents for AI global governance. Experimental zones for digital skills training are being established, fostering collaboration between academia, industry, and research sectors to cultivate AI talent. Moreover, infrastructure development for AI education, such as gigabit optical networks, 5G networks, and IPv6, is being prioritized. Additionally, China is focusing on the orderly and legal opening up of public data resources and improving digital literacy and skills for citizens of all ages and demographics. On the gathering front, numerous national and local- level talent programs have been developed to attract AI talent to work in China. Additionally, China’s AI companies have established their own overseas institutes to recruit international talent, further bolstering the country’s AI development capabilities. Data Several of China's policy initiatives aimed at developing, accessing, and protecting data are particularly significant. These include formulating and implementing a national big data strategy, enhancing research and development in key big data technologies and products, and constructing critical big data infrastructure, such as the national integrated big data center and smart city space-time big data platforms. To ensure the security of data for development, utilization, and industrial growth, China has established a data classification and protection system. There is also a focus on building cross-departmental and cross-regional mechanisms for data circulation and application. Additionally, the establishment of a robust national public data resource system and the legal opening up of data are key components of these initiatives (refer to Table 1). Notably, China’s approach to data protection is encapsulated in regulations such as the Data Security Law and the Cybersecurity Law. These laws favor Chinese AI companies by providing them access to data from China’s large domestic market, thereby granting them a rare competitive advantage on a global scale. The previously lax protection of personal privacy in China allowed AI companies to access vast amounts of data, significantly benefiting their development and innovation efforts. However, this situation has changed with the implementation of new data security and personal privacy laws. Chinese AI companies now face tighter constraints on data acquisition, which alters the landscape of data availability that once fueled their rapid growth. Capital and Market China's AI development policies are intricately connected with substantial financial mechanisms. The national and local governments have made significant investments in the AI sector and start-up firms, especially through Government Guidance Funds established by local governments and state-owned enterprises, the Fund for Industrial Restructuring and Upgrading, and the Central Basic Infrastructure Budget (Ding, 2018). Additionally, through regulatory toleration and exemptions, China offers AI firms, particularly industry giants and promising start-ups, preferential contract bidding, tax benefits or reliefs, easier access to finance, and market share protection. For example, China leverages its ambiguous regulations to allow AI firms to access global financial capital through a unique -- 5 of 24 -- 6 quasi-legal ownership vehicle known as the "Variable Interest Entity" (McKnight et al., 2023). Moreover, to protect and develop its own AI firms, China has restricted foreign investment in the country's internet and AI sectors, citing national security concerns to prevent foreign influence or control (Lei, 2023). Further, policies and regulations that facilitate the registration of platform economy market entities, prohibit administrative authorities from abusing their power to exclude or restrict market competition, and provide ample space for the development of new forms of employment while ensuring safety (see Table 1), suggest that online platform companies may have immunity from legal liability. These measures encourage government agencies to relax or even eliminate administrative permissions for market entry, except in areas associated with substantial risks. These supportive policies and tolerant regulations have not only bolstered the development of China's AI National Champions—Baidu, Alibaba, Tencent, and iFlytek—but also supported the global expansion of Chinese platform companies such as TikTok, Temu, and Shein. Hardware Recognizing its shortcomings in advanced semiconductor and integrated circuit (IC) technologies, China has implemented policy initiatives with a "catch-up" approach to develop the necessary hardware for training and executing AI algorithms (Ding, 2018). These policies include supporting IC companies in securing domestic and international IPO financing and providing corporate income tax and value-added tax incentives to stimulate growth within the industry. Further, the government has exempted import tariffs on essential components of IC equipment, underscoring its commitment to reducing costs and encouraging technological upgrades. Support extends to AI and chip technology research and development (R&D), as well as fostering independent innovation through initiatives such as national pilot zones and open innovation platforms. To maintain competitiveness in supercomputing, China is making long- term investments in its supercomputing facilities. Additionally, it encourages IC companies to acquire chip technology through overseas deals, thereby enhancing their technological base and global presence. Intellectual property protection is another key focus area, with enhanced safeguards for patents, trademarks, copyrights, and IC designs. Improvements in intellectual property information services aim to provide better support and access to information for companies navigating the complex IP landscape. Lastly, policies are in place to prevent vicious competition for IC talents, ensuring a sustainable and stable development environment for professionals in the sector (refer to Table 1). These comprehensive efforts demonstrate China’s strategic initiative to bridge the technological gap and enhance its position in the global ICT and AI sectors. China’s rapid progress in AI development—especially its emerging leadership in open-source LLMs—has strengthened its technological confidence. In December 2024, the government launched the AI+ Initiative, which aims to digitally transform traditional sectors by integrating artificial intelligence into industrial applications and critical infrastructure. In August 2025, China introduced a further policy push, the Opinions of the State Council on Deepening the Implementation of the “Artificial Intelligence+” Action. This policy outlines an ambitious agenda to accelerate the diffusion of AI across six priority domains: scientific and technological innovation, industrial upgrading, consumer quality enhancement, public well-being, governance -- 6 of 24 -- 7 capacity, and international cooperation. It also sets aggressive targets, including the deployment of AI applications across 90 percent of major economic sectors within five years. China's ability to mobilize a whole-of-society approach to achieve national goals of innovation and technological upgrading has led to impressive outcomes in terms of the quantity and scale of AI development. However, the campaign-style policy implementation, which involves setting statistical targets from the top down through government bureaucracy, may inadvertently encourage lower-level bureaucrats and firms to manipulate these targets. This focus on meeting quantitative goals can lead to innovation that is of low quality and productivity. Such phenomena, where entities are motivated to "game the numbers" to meet imposed targets, could undermine the true effectiveness and sustainability of the innovations being developed (Ang et al., 2023; Lei, 2022). Regulating AI for the Party-State’s Economic Control By the late 2010s, the market influence of AI and platform companies had permeated nearly every aspect of the Chinese economy, granting them control over vast amounts of information flows and extensive financial and social activities. The substantial instrumental and infrastructural power held by major AI and platform companies, such as Alibaba and Tencent, effectively positioned them as de facto public utilities and private regulators, posing a threat to the Party-State’s control over the economy. In response, starting in 2016, the Party-State began to shift its regulatory approach towards these companies from "inclusive" to "prudent," with a particular focus on two critical areas. First, the Party-State sought to curb the financial services provided by these platforms, particularly targeting the payment systems of Alipay and WeChat Pay, which operated beyond its regulatory jurisdiction. Guidelines and policies introduced in 2016 began to specifically address fintech and associated financial risks. A notable action took place in late 2020, when the Party- State cancelled the public listing of Alibaba's affiliate, Ant Financial, on the Hong Kong and Shanghai exchanges. Subsequently, it tightened regulatory rules governing the financial sector, including those related to platform payment systems. The second area of focus has been on strengthening antitrust regulation to prevent the excessive expansion of capital within the AI and platform economy. Several laws and policies have been amended or introduced to tackle issues of antitrust and unfair competition in the platform economy and online transactions, delineating the classifications and responsibilities of internet companies. Notably, the amended Anti-monopoly Law (2022) targets the practices of AI and platform companies that exploit data, algorithms, technologies, platform rules, and capital advantages to engage in monopolistic behavior or abuse dominant market positions. The Regulations on the Prohibition of Unfair Competition on the Internet (Exposure Draft) aim to refine the anti-unfair competition rules for the platform economy by prohibiting companies from using data, algorithms, and platform rules to engage in unfair competition. Additionally, the Provisions on the Administration of Algorithm-generated Recommendations for Internet Information Services mandate that providers of algorithm recommendations avoid creating monopolies and engaging in unfair competition. The Guidance for Anti-monopoly in the Field of -- 7 of 24 -- 8 Platform Economy extends these efforts further, aiming to prevent and prohibit monopolistic conduct in the platform economy while safeguarding the interests of consumers and the public. Moreover, China has enforced these regulations against numerous platform companies, including Alibaba and Meituan, imposing significant fines (Lei, 2023). Regulating AI for Social Stability Maintaining social stability has been a key objective for the Party-State since the economic reforms began (Lee, 2007). The rise in labor unrest from 2000 to the mid-2010s prompted the Party-State to re-regulate labor markets (Liu and Kuruvilla, 2017). The platform economy, characterized by a centralized and monopolized market structure and ambiguous employment relationships (Tirole, 2017), presents different and potentially more severe challenges to social stability than traditional sectors (Lei, 2023). Firstly, platform workers, who often operate outside formal employment relationships, are more inclined to engage in collective actions to address their labor disputes. This is largely because they face significant difficulties in accessing legal channels for dispute resolution. Secondly, unlike traditional cellular labor activism (Lee, 2007), platform workers tend to protest against the same companies or different companies over similar grievances, which facilitates the building of solidarity across workplaces or regions. Thirdly, since many platform workers are involved in transportation services, their protests frequently disrupt traffic and public order, posing a greater risk of causing social instability. The risk of labor unrest in the platform economy prompted the Party-State to adopt a prudent approach in formulating regulations and guidelines such as the Opinions on Strengthening the Governance over Ethics in Science and Technology, Guidance on Protecting the Labor Rights and Interests of Workers in New Forms of Employment, Provisions on the Administration of Algorithm-generated Recommendations for Internet Information Services, and Notice on Launching the "Clean Internet Platform: Addressing Typical Algorithm Issues" Special Campaign. These regulations focus on three areas: AI and algorithms, labor standards, and employee voice. In regulating AI and algorithms, China mandates algorithm registration and transparency regarding work rules and labor standards, establishes an AI ethical review and regulatory system, and requires platforms to establish AI accountability mechanisms to prevent prejudice and discrimination. The regulations also support third-party assessments of algorithms and ban algorithmic interference with public opinion. Regarding labor standards, the regulations require platform companies to avoid discrimination in hiring, adopt a "middle-ground algorithm" for work assessment, pay non- standard workers local minimum wages, inform ride-hailing drivers about commission rates and their adjustments, supervise wage payments by partners, provide extra compensation for working on statutory holidays, ensure workers’ rest time, count both online and offline time as working hours, prevent overwork, and establish occupational injury insurance systems for platform workers. Significant labor rules adjustments must be reported to local human resources and social security departments in advance. Platform companies and their partners must clearly -- 8 of 24 -- 9 define employment responsibilities and sign written agreements with workers in non-standard employment relationships. The regulations also seek to promote employee voice to reduce labor disputes and conflicts by mandating platform companies to solicit opinions from workers before formulating or revising labor rules, disclose algorithm rules to them, recognize the right of platform workers to join trade unions and negotiate working conditions, affirm the right of trade unions in supervising labor standards compliance, encourage the establishment of internal labor dispute mediation committees, and develop mediation and litigation mechanisms for resolving labor disputes. However, platform workers are banned from using illegal or extreme means to defend their rights. While these regulations appear comprehensive and stringent, enforcement by the Party-State has been lax. This is partly because, like other labor regulations in China, these new rules are often too vague or unenforceable to be effective. More fundamentally, the intention of the Party- State may not be so much about labor protection as about containing labor unrest (Lei, 2023). The right to unionize and engage in collective bargaining for platform workers, while theoretically beneficial, is not particularly effective due to the nature of the All-China Federation of Trade Unions (ACFTU) as an extension of the Party-State rather than a genuine representative of workers. Regulating AI for Political/Public Security The Party-State has long harbored concerns about the internet's potential to spread grievances against the government and facilitate collective actions outside of its control, posing a threat to its core interest of maintaining a political monopoly. Following Xi Jinping's ascent to power, these concerns were framed as national security threats, leading to crackdowns on the internet and social media, as well as the enactment of the National Security Law (2015) and the Cybersecurity Law (2017), which tightened control over internet content. Initially, due to its priority of achieving global AI leadership, the Party-State adopted a relatively inclusive regulatory approach before 2019, limiting its intervention mainly to censorship and ideological control (McKnight et al., 2023). However, as AI and platform companies gained significant power in building digital infrastructure and collecting extensive data, the Party-State's concern over political security intensified. AI and data have become critically important for China's own surveillance and governance systems (Arcesati, 2021). Consequently, after 2019, the Party-State shifted to a more prudent regulatory approach, imposing greater control over data and AI. Key regulations included Governance Principles for the New Generation Artificial Intelligence-Developing Responsible Artificial Intelligence, Ethical Norms for New Generation Artificial Intelligence, Provisions on the Administration of Algorithm-generated Recommendations for Internet Information Services, Data Security Law, Personal Information Protection Law, Provisions on the Administration of Deep Synthesis of Internet-Based Services, and Interim Measures for the Administration of Generative Artificial Intelligence Services. In addition, the rapid advances of AI after 2024, particularly the proliferation of open-source LLMs and reasoning models, increase -- 9 of 24 -- 10 the Party-State’s concern about broad public security risks brought by AI, including those tied to employment impacts, chemical, biological, radiological, nuclear (CBRN) weapon misuse, and loss of human control over advanced AI systems. A number of regulations focusing on governance of open-source models have been enacted, such as Measures for Identifying Artificial Intelligence-Generated Synthetic Content, Measures for the Security Management of Facial Recognition Technology Application, Measures for the Management and Service of Artificial Intelligence Technology Ethics (Trial), and the AI Safety Governance Framework 1.0 and 2.0. Regarding data and privacy, China’s regulatory framework stipulates that no individual or organization may use networks to jeopardize national security, incite subversion of state power, or undermine the socialist system. These rules mandate that data collection and the processing of personal information must not compromise national security or the public interest. They also establish systems for consumer privacy, the protection of commercial secrets in the cyber environment, and procedures for data security review, emergency response, and network and data security monitoring, warning, and information notification. More recent regulations introduced after 2024 further expand safeguards against the misuse of biometric and synthetic data, emphasizing the importance of provenance verification, traceability, and strict oversight of high- risk data applications. While these frameworks protect individuals’ privacy rights and their right to be informed about and decide on the handling of their personal information, they simultaneously grant the government broad and largely unrestricted authority to access data held by any individual or organization. In terms of AI and algorithms, existing regulations require that generative AI and algorithmic recommendation providers align with socialist core values, report any illegal or harmful activities to the relevant authorities, establish ethical review procedures, and implement accountability mechanisms to ensure that AI systems do not compromise national security or public interests. AI users, platform companies, and business partners are similarly obligated to report violations and emerging risks to the relevant authorities. Online content service platforms must also submit an annual report on internet ecosystem governance. Since 2024, additional sector-defining regulations have further tightened China’s AI governance regime. They introduce more explicit ethical, risk-management, and lifecycle governance requirements, mandating pre- deployment risk assessments, strengthened oversight of foundation models, “labelling” AI- generated content, and enhanced responsibility tracing. Providers of generative AI, deepfake technologies, or algorithmic systems with significant potential to influence public opinion or facilitate social mobilization must conduct security assessments, register their algorithms, and ensure that model outputs are accurate, safe, and controllable. These regulations significantly strengthen the Party-State’s political control over AI and platform giants and are stringently enforced if political security is involved. For example, in 2021, after Didi—the Chinese ride-hailing giant—held an IPO in the US, China promptly initiated an investigation, suspended new downloads of Didi apps, and later in 2022, imposed a US$1.2 billion fine on Didi for its violations in cybersecurity, data security, and personal information protection. -- 10 of 24 -- 11 Balancing Efficiency and Security The Chinese model of AI governance—characterized by a mix of permissive and restrictive regulation—reflects a strategic balancing act between promoting technological efficiency and safeguarding national security. This dual approach is evident across various policy cycles. When the priority is to accelerate AI development, the government typically maintains a permissive stance but intervenes decisively if specific political or ideological red lines are crossed, as demonstrated by the crackdown on the internet and social media platforms in the mid-2010s. Conversely, even during periods of heightened regulatory tightening, the state continues to introduce policies designed to spur AI innovation, such as the Guidance on Accelerating Scenario Innovation and Promoting High-Quality Economic Development with High-Level Application of Artificial Intelligence and the Notice on Supporting the Construction of a New Generation of Artificial Intelligence Demonstration Application Scenarios. This balance is dynamic and shifts in response to broader contextual factors. For example, following the deterioration of U.S.–China relations in 2018, heightened concerns over political security pushed the regulatory pendulum toward greater stringency. By contrast, during the economic slowdown and rising unemployment in 2022, stringent antitrust measures against AI and platform companies were relaxed, moving the balance back toward development (McKnight et al., 2023). The “ChatGPT shock” in 2022 further motivated China to loosen certain aspects of AI governance in order to accelerate domestic innovation, reflected in the Interim Measures for the Management of Generative Artificial Intelligence Services, which were softened after expert and industry pushback. However, following the “DeepSeek moment” in early 2025, when the performance gap between Chinese and U.S. generative AI systems significantly narrowed, China entered a new phase of AI governance—one marked by renewed emphasis on controlling AI outputs, strengthening oversight of user data, and tightening safety and risk-management frameworks. Several characteristics of China’s AI regulations provide the Party-State substantial leeway to strike a balance between efficiency and security. First, many regulations are issued as agency- level directives, which allow for both arbitrariness and adaptability. Second, these regulations often have multiple potential enforcers from different government agencies, each of whom may interpret the rules differently, affording the central government flexibility to intervene as needed. Third, many regulations are deliberately ambiguous, enabling flexible or selective enforcement. This ambiguity is particularly pronounced in labor regulations for the platform economy; for example, Article 20 of the Provisions on the Administration of Algorithm-generated Recommendations for Internet Information Services mandates that platforms ensure algorithms provide workers with adequate compensation and rest, yet it remains unclear what legally constitutes "adequate." Furthermore, significant regulations frequently undergo an exposure draft phase to gather feedback from stakeholders, ensuring that the final regulations are more balanced and reflective of broader interests. For instance, the 2023 generative AI regulations were substantially moderated from their original proposals, reflecting stakeholder input and the government's adaptive regulatory approach. The Role and Responses of Stakeholders -- 11 of 24 -- 12 China's AI policies and regulations, although predominantly influenced by the Party-State, also incorporate input from a diverse range of stakeholders, including tech firms, trade unions, intellectuals, journalists, workers, and the public. Initially operating in a legal grey area, major AI and platform companies have sought to influence policies and regulations from their inception through direct and indirect lobbying of central and local governments. Their tactics include hiring director-level government officials with lucrative compensation to manage government relations, sponsoring academic research that underscores the platforms’ contributions to economic development, employment growth, and poverty relief, and investing in employment opportunities for various vulnerable groups such as the unemployed, disabled, and veterans. Additionally, highly influential tech giants such as Alibaba, Huawei, and Tencent are often directly consulted by government agencies during the process of drafting regulations. For example, the acknowledgement section of the AI Safety Governance Framework 2.0, released in September 2025, listed Alibaba and Huawei among government-affiliated organizations and universities. These efforts of tech firms have contributed to the leniency in AI and platform labor regulations (Zhang, 2024). The ACFTU has been commanded by the Party-State to manage increasing pluralistic interests and counter the emergence of independent labor movements. Despite some innovative and successful reforms within the ACFTU, particularly at the regional and grassroots levels, union organizing and collective bargaining in China have largely remained symbolic due to the tight grip of the Party-State, rendering the ACFTU ineffective at truly representing workers' interests (Liu, 2009, 2020; Friedman, 2014). The inability of the ACFTU and the legal system to resolve labor insurgency has increasingly led the Party-State to adopt a strategy of repression to manage labor unrest (Chen and Gallagher, 2018; Li and Liu, 2018). The rise of worker-led collective bargaining, supported by movement- oriented labor non-governmental organizations (NGOs), has particularly challenged the Party- State, leading to a severe crackdown on labor activists and labor-friendly NGOs since 2015. This repression has limited the space for civil society and independent worker mobilization, coinciding with the development of AI and platforms in China, providing a crucial context for understanding China's AI governance and its workplace implications. The ACFTU plays a significant role in regulating platform labor, particularly at the national level. By early 2024, the ACFTU had issued five AI-related policies/regulations in conjunction with other Party-State agencies, and nine policies/regulations independently (see Table 1). These focus on labor standards, employee voice, and the rights of unionization and collective bargaining in the platform economy, as well as the digitalization of trade unions' work to enhance their efficiency. Adhering to the principle of "where there are workers, there should be trade unions" (Liu et al., 2011), the ACFTU has begun to organize platform workers—who often operate outside formal employment relationships—into unions. However, the traditional ACFTU organizing model, which relies on employers’ permission for unionization, is ineffective in the context of online platforms. Consequently, alternative models such as local industry union associations and regional union associations are being utilized (Liu, 2010). In some instances, these groups engage in collective consultation on working conditions. While these union organizing and bargaining models can rapidly increase union membership among platform workers, the resulting -- 12 of 24 -- 13 unions and negotiations tend to be largely symbolic, bringing minimal benefits to workers. For example, Lalamove in Shenzhen established a company-level union in 2019, which facilitated communication between drivers and the platform, and helped increase task rewards and subsidies. However, it did not address the drivers' core demand for higher commission rates3. Our interviews with platform company managers, workers, and union staff revealed that none could identify any substantial gains for workers from these unionization efforts. Additionally, when dissatisfied platform workers have attempted to organize their own groups, they have faced detention by the police, indicating significant challenges to genuine labor organization and advocacy in China.4 Chinese platform workers often face precarious employment conditions characterized by extremely long working hours, low commission rates, unsafe working conditions, and limited or no access to social insurance. Furthermore, many are technically employed and managed by third parties but do not receive formal labor contracts or social insurance benefits (Lei, 2021; Liu and Friedman, 2021). This hyper-exploitation has led to a rise in both individual and collective protests among platform workers. Despite the Party-State's strict ban on independent worker organizing and repression of radical collective actions, the number of collective protests by platform workers remains notable. For instance, the China Labor Bulletin recorded 90 collective protests by couriers, food-delivery riders, ride-hailing drivers, and truck drivers in 2023 alone.5 Individual protests by platform workers are also numerous, with some resorting to radical means. Consider several examples: in 2021, an Ele.me food-delivery rider set himself on fire over unpaid wages6; in 2022, another Ele.me rider stabbed himself after being threatened with a RMB 1,000 fine if he resigned7; and in 2023, a Lalamove driver fatally stabbed two platform staff after he was unable to retrieve his deposit of RMB 1,000 upon resignation8. These protests by platform workers present unique challenges to social stability, prompting the Party-State to strengthen labor regulations in the platform economy, particularly regarding algorithms. Intellectuals play a critical role in China’s AI policymaking. While various government agencies are responsible for AI policies and regulations, they often lack in-house expertise in the technical and legal specifics of regulating AI and must rely heavily on extensive external consultations with legal and technical experts from academia, think tanks, and industry. Additionally, scholars and experts can actively influence government AI policymaking by organizing academic conferences or publishing papers and reports. For example, after the draft Interim Measures for the Management of Generative Artificial Intelligence Services was released, Chinese scholars and researchers held roundtables and published articles suggesting 3 See the report of China Labor Bulletin, https://clb.org.hk/zh- hans/content/%E8%B4%A7%E6%8B%89%E6%8B%89%E5%8F%B8%E6%9C%BA%E6%8E%A5%E8%BF%9E %E7%BD%A2%E5%B7%A5%E9%9A%BE%E8%A7%A3%E5%B9%B3%E5%8F%B0%E6%A0%B9%E6%9C%A C%E9%97%AE%E9%A2%98-%E5%B7%A5%E4%BC%9A%E5%B7%A5%E4%BD%9C%E4%B8%8D%E5%8F %AF%E5%81%8F%E7%A6%BB%E5%8F%B8%E6%9C%BA%E6%A0%B8%E5%BF%83%E8%AF%89%E6%B1 %82. 4 See https://chinadigitaltimes.net/chinese/663132.html 5 See https://maps.clb.org.hk/. 6 See https://www.ft.com/content/d6189ee8-9aea-41dd-a412-b8daba9cacf2. 7 See https://www.sohu.com/a/620571935_121047174. 8 See https://www.sohu.com/a/666598282_121633568. -- 13 of 24 -- 14 specific changes to soften overly restrictive provisions. These efforts, together with the lobbying of tech firms such as Baidu, effectively pushed back some stringent regulations (Zhang, 2024). The role of journalists, academic researchers, and the general public has been crucial in advocating for labor-friendly regulations in the platform economy. A striking example occurred in September 2020 when the Chinese magazine Renwu published a report that vividly illustrated the challenges faced by food-delivery couriers. These workers' schedules and incomes were dictated by algorithms that failed to consider the realities of navigating Chinese cities. The publication of this report sparked widespread public outcry, which not only pressured platform companies to reassess their practices but also accelerated the implementation of new labor regulations. However, the impact of these regulations on the workers themselves appears to be extremely limited, if any. In interviews we conducted with food-delivery couriers and ride-hailing drivers, the vast majority reported no positive changes in their working conditions or in the resolution of labor disputes. Instead, many expressed frustration that new platform rules had actually reduced their earnings. For instance, some workers criticized regulations that mandate rest periods after certain hours of work, arguing that these do not alleviate fatigue but instead decrease their income. Additionally, despite Meituan and Ele.me making their algorithms public, none of the couriers we interviewed were aware of the details. For these workers, changes that do not directly lead to increased commission rates are perceived as insignificant. From the management side, platform managers reported that the new labor regulations have not significantly burdened their operations. Some regulations, such as mandatory rest periods after certain hours of work and the establishment of an occupational injury insurance system, even help platforms reduce work-related injuries and the associated compensation costs. This discrepancy between the experiences of workers and the perceptions of management highlights a critical gap in the effectiveness of the labor regulations. It suggests that while the regulations may be designed to improve working conditions and fairness, their actual implementation and the tangible benefits they provide to workers might not align with these objectives. China and Global AI Governance Influence of Global Norms on China’s AI Governance China’s AI governance regime does not operate in isolation from global norms; rather, it increasingly incorporates and echoes international standards and frameworks. For example, the 2021 Ethical Norms for the New Generation Artificial Intelligence require AI activities to respect human rights and adhere to regional ethical norms—language typically found in global AI ethics debates. Similarly, China’s AI Safety Governance Framework (v1.0) explicitly affirms the need to align with “global standards and practices” and to cooperate cross-border on AI ethics, cybersecurity, and safety. The Interim Measures for the Management of Generative Artificial Intelligence Services also reflect themes widely discussed in international forums (transparency, labelling, algorithmic risk). In addition, Chinese tech industries and firms have started to embrace some norms of global AI governance. In 2025, sixteen Chinese companies announced domestic AI safety pledges that closely resembled the international commitments made at the -- 14 of 24 -- 15 May 2024 Seoul AI summit (Singer, 2025). Shortly after, the Chinese AI Safety and Development Association (CnAISDA) was established during the Paris summit. CnAISDA, which claims credible support from the Chinese government, defines itself as China's equivalent to other national AI Safety Institutes (Singer et al., 2025). China’s Emerging Influence on Global AI Governance The global governance architecture for AI is only beginning to take shape; rules, norms, and institutions remain fragmented, immature, and contested (Cheng and Zeng, 2023). In this still- fluid environment, China sees an opportunity to contribute ideas and promote standards aligned with its preferences. Indeed, China has demonstrated its ambition to become a leader and rule- maker in global AI governance in its various policies. For example, China’s AI Safety Governance Framework (v2.0), released in September 2025, calls for China to contribute to AI governance rule-making through multilateral bodies such as the United Nations (UN), the Asia- Pacific Economic Cooperation (APEC), and BRICS (Brazil, Russia, India, China, and South Africa). Although China has made visible efforts in technical standard-setting, data governance, and global diplomatic initiatives, aiming to position itself within a still-forming system, its influence remains nascent, uneven, and in many respects still aspirational. 1. Technical Standards: Growing Engagement but Limited Global Uptake China’s expanding presence in major standards-developing organizations (SDOs), such as the International Organization for Standardization (ISO), the International Electrotechnical Commission (IEC), and the International Telecommunication Union (ITU), shows that it has become more active in shaping technical standards related to AI, but its capacity to translate participation into global influence remains mixed. As Fuchs and Eaton (2024) and Ruhlig (2023) demonstrate, China has enhanced its technical professionalism and established institutional channels to influence standards. The rise of Chinese firms such as Huawei, Baidu, iFlytek, CAICT, and Haier as participants or conveners in ITU and IEC working groups further consolidates China’s position. These firms have introduced standards and white papers that shape global approaches to foundational issues such as AI evaluation, content authenticity verification, digital human governance, and cloud–AI interoperability. Yet as Cheng and Zeng (2023) emphasize, many Chinese-origin proposals are still rejected at early stages due to insufficient technical quality or lack of consensus support among member states. China’s past “latecomer” status continues to limit its ability to steer agenda-setting in established SDOs, which are dominated by actors from the US, Europe, and Japan. Even where China succeeds, its influence tends to be incremental and technical, shaping definitions, architectures, or evaluation methodologies rather than rewriting governance norms. The infrastructure-led diffusion of Chinese standards through the Digital Silk Road (DSR) creates pathways for indirect influence, especially in developing countries, but this diffusion remains heterogeneous and often depends on local political receptivity rather than automatic adoption (Borgogno and Savini Zangrandi, 2024). Overall, China’s role in global standard-setting can be described as emerging but not yet dominant, with significant potential but limited global traction to date. 2. Data Governance: A Model with Selective Appeal Rather than Global Convergence -- 15 of 24 -- 16 China’s data-governance model—emphasizing sovereignty, security, mandatory review, and state access—differs from both the EU’s rights-based approach and the U.S. market-centered model by positioning the state, rather than the firm or individual, as the principal regulator and guarantor. This model constrains cross-border data flows, imposes mandatory security assessments for data transfers, and requires localization for categories of “important,” “core,” or “sensitive” data, which is not normatively attractive to liberal democracies whose regulations, such as the EU’s General Data Protection Regulation (GDPR), reflect fundamentally different principles (Borgogno and Savini Zangrandi, 2024). Nonetheless, by advocating for broad national-security exceptions and emphasizing regulatory autonomy, China has shifted global debates in international economic institutions, such as the WTO and G20, toward recognizing the legitimacy of security-based restrictions on cross-border data movement. This shift is particularly evident in negotiations involving developing countries, many of which view China’s model as more compatible with their own institutional capacities and security concerns. While the DSR allows China to export data architectures and regulatory templates, such diffusion does not amount to broad global convergence around a Chinese governance model. Instead, it produces regionally varied and selective adoption, shaped by partner countries’ own political systems and institutional capacities. China’s influence in global data governance, therefore, remains context-dependent, more apparent in regions receptive to sovereignty-based governance than in the broader global governance landscape (Borgogno and Savini Zangrandi, 2024). 3. Global AI-Governance Diplomacy: Active Aspirations but Structural Constraints China’s influence also operates through a rapidly expanding landscape of global AI- governance diplomacy. It engages actively in multilateral organizations, regional groupings, and its own diplomatic initiatives to shape the conceptual and institutional direction of global AI governance. China has significantly increased its presence in the UN system. In 2021, it submitted a position paper on regulating the military application of AI, and it later issued a position paper on strengthening ethical governance of AI. China also introduced and successfully passed a UN General Assembly resolution on AI capacity-building for developing countries, positioning itself as a champion of Global South participation in AI governance. These interventions frame AI governance around controllability, safety, development, and sovereign regulatory autonomy—principles that resonate strongly with many developing countries. Outside the UN, China has launched an array of high-profile global AI initiatives. The Global AI Governance Initiative (2023) articulates China’s vision of a cooperative, development- oriented global framework that rejects technological exclusion and affirms each country’s right to choose its own AI development pathway. The Shanghai Declaration on Global AI Governance (2024) further advances principles of shared responsibility and inclusive international cooperation. In July 2025, China released the Action Plan for Global Artificial Intelligence Governance, which proposes the establishment of global risk-classification systems, harmonized evaluation protocols, and standardized rules for the authenticity and traceability of generative AI content. Later in September 2025, China introduced the AI+ International Cooperation Initiative, which promotes global collaboration in five areas—public well-being, industrial development, -- 16 of 24 -- 17 cultural prosperity, talent cultivation, and technological innovation—and explicitly links AI cooperation to China’s broader Global Development Initiative. China’s ambition to institutionalize global AI governance is further reflected in its 2025 proposal to establish a Global AI Cooperation Organization, envisioned as a multilateral body focused on AI safety, evaluation frameworks, ethical guidelines, and capacity-building for developing countries. This proposed institution would complement and partly counterbalance U.S.- and EU-led initiatives, such as the OECD’s GPAI, while providing a platform in which developing countries can exert greater influence over global rule-making. Regional organizations reinforce these efforts. In the Shanghai Cooperation Organization, China has promoted joint AI research agendas, shared guidelines on AI ethics, and coordinated approaches to data security and cross-border digital services. Through BRI summits, China encourages partner countries to adopt Chinese cloud services, AI-enabled governance tools, and digital public infrastructure systems that implicitly carry Chinese governance assumptions. However, China’s actual room for global leadership in AI governance is structurally limited. Many of the most influential global AI governance mechanisms—including the G7, the EU’s AI Act process, the OECD’s GPAI, and the Council of Europe’s Convention on AI—either exclude China or operate within liberal democratic value frameworks that differ significantly from China’s governance philosophy. China’s proposals thus face a legitimacy gap among Western governments and civil society groups, which view China’s AI practices—especially in surveillance—as incompatible with human rights–centric AI regulation (Cheng and Zeng, 2023). Moreover, great-power rivalry, especially with the United States, severely restricts China’s ability to shape global rules. The securitization of AI in U.S. policy and the portrayal of China as a “formidable challenge” have generated politicized resistance to Chinese initiatives in many Western-led forums. As Cheng and Zeng (2023) stress, the geopolitical landscape leaves China limited space to demonstrate leadership, even as global governance remains underdeveloped. Its initiatives, therefore, function more as signals of aspiration than as evidence of institutional influence. Taken together, China’s influence on global AI governance is best characterized as emerging, tentative, and uneven, rather than consolidated or transformative. Its rising presence in technical standards-setting, data-governance diffusion, and multilateral diplomacy reflects a coherent strategy to position itself as a norm-shaper. Yet, the actual effects of these efforts remain constrained by geopolitical tensions, ideological divides, China’s residual status as a latecomer, and the fragmented nature of global AI governance. Conclusion China has established itself as a leader in the AI regulatory sphere, pioneering a range of bureaucratic and technical tools that set a precedent globally. While many of these regulations are tied to censorship efforts, they also introduce innovative mechanisms, such as disclosure requirements, a licensing regime, model auditing systems, and technical performance standards. These regulatory innovations offer valuable insights and lessons that can inform AI governance globally. -- 17 of 24 -- 18 The Chinese approach to AI regulation strikes a balance between promoting innovation and ensuring security, a dynamic that must be understood within the context of the Chinese political economy. A key characteristic of China's regulatory strategy is its strategic ambiguity, which grants regulators considerable flexibility. This flexibility, however, has led to issues such as lax and selective enforcement, especially evident in labor-related contexts. In contrast to the common perception of China's AI regulation as a top-down, monolithic, and state-driven model, we demonstrate that it actually involves a diverse array of social actors— including tech firms, trade unions, intellectuals, journalists, workers, and the public—who co- produce regulatory norms and mechanisms. Aligned with the concept of authoritarian legality, the Party-State utilizes AI regulations to bolster its legitimacy, underpinned by goals of economic development and social stability. Nonetheless, this approach often subjects workers to the harsh realities of techno-capitalism under authoritarian regimes, highlighting a complex interplay between technological advancements and labor rights. This juxtaposition highlights the inherent tensions in China's AI governance, where technological progress is pursued aggressively, albeit at the potential cost of social implications. The critical question remains whether China can successfully reconcile these tensions in the long term, striking a balance between rapid technological innovation and the broader societal impacts it engenders. Globally, China is not yet shaping global AI governance in a decisive way, but it is actively seeking to influence a governance ecosystem that is itself still fluid. Its activities across technical standards, data governance, and global initiatives demonstrate a country's efforts to establish an early foothold in a nascent field. Whether these attempts will translate into lasting global influence depends on how the broader governance system evolves and whether China can overcome the major structural, normative, and geopolitical challenges that currently limit its leadership credentials. -- 18 of 24 -- 19 References Ang, Y. Y., Jia, N., Yang, B., & Huang, K. G. 2023. China’s Low-Productivity Innovation Drive: Evidence From Patents. 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China’s Key Regulations/Policies/Directives on AI/Algorithm/Platform Work/Personal Information Protection (till early 2024) AI (1-57), Algorithms, and Online Platform (58-83) Efficiency  Implementing AI national major S&T projects and incorporating AI into national specialized talent recruitment plans.  Enhancing teachers’ AI skills and integrating AI education into primary, secondary, vocational, and university curricula to train talents in foundational AI theories, “AI+X” applications, and global AI governance.  Improving digital literacy and skills for citizens of all ages and demographics.  Fostering collaboration between academia, industry, and research for practical application, and encouraging interdisciplinary, cross-sectoral, cross-regional, and international cooperation in AI (e.g., establishing national AI standards and coordinating them with international standards).  Constructing AI and IC R&D infrastructure (e.g., gigabit optical networks, 5G, IPv6, cloud computing, IC laboratories, national pilot zones).  Facilitating registration for platform economy market entities, prohibiting administrative authorities from abusing their power to exclude or restrict market competition, providing ample space for platform development while ensuring safety, and encouraging platform companies to explore international markets.  Supporting IC companies with domestic and international IPO financing, state special financial support, corporate income tax and value-added tax incentives, tariff-free import of equipment components, and intellectual property protection.  Preventing vicious competition for IC talent and allowing software companies to set employee wages independently in accordance with the law. State Economic Control  Enhancing financial regulations and antitrust regulations for platform companies.  Algorithm recommendation providers/platform companies shall avoid monopolies and unfair competition.  Prohibiting dominant platforms from engaging in dumping, denying/restricting transactions, or practicing big data-based price discrimination.  Enhancing tax data collection and supervision of platform companies, as well as cracking down on invoice fraud and tax evasion. Social Stability  Enhancing algorithmic transparency, registration management, and third-party assessments to prevent prejudice, discrimination, and algorithmic interference with public opinion, as well as establishing AI ethical review and regulatory systems, and AI accountability mechanisms.  Platform companies and their partners must clearly define employment responsibilities, sign written agreements with platform workers, and affirm the right of trade unions to monitor compliance with labor standards.  Platform companies shall adhere to the local minimum wage, supervise wage payments by partners, provide compensation for statutory holidays, inform ride- hailing drivers about commission rates and adjustments, ensure workers’ rest time, prevent overwork, and count both online and offline time as work hours.  Platform companies shall avoid discrimination in hiring, adopt a “middle-ground algorithm” assessment, establish platform workers’ occupational injury insurance systems, report significant labor rules adjustments in advance to local human resources and social security departments, seek worker input before formulating or revising labor rules, disclose algorithm rules, and establish internal labor dispute mediation committees.  Platform workers have the right to join trade unions, negotiate working conditions, and apply for mediation from dispute resolution organizations, but must not resort to illegal or extreme means to defend rights.  The authority shall issue case judgments and judicial policies for new forms of employment, optimize the one-stop mediation process, promote the integration of online and offline mediation, and add the function of joint mediation to the labor dispute mediation center. Political/ Public Security  Generative AI and algorithm recommendation providers must adhere to socialist values, prohibit content that incites the subversion of state power or the overthrow of the socialist system, and build feature libraries to detect such content. They should also report users’ illegal activities to the authorities, establish AI ethical review and regulatory systems, and implement AI accountability mechanisms.  AI users and platform companies/partners shall report violations and risks to the relevant authorities and assist in emergency responses by sharing relevant data.  Providers of generative AI/deepfake/algorithm with potential for public opinion shaping or social mobilization shall strengthen security and (political) bottom- line awareness, conduct security assessments, and algorithm registration.  Online content service platforms must compile an annual report on internet ecosystem governance and undergo expert evaluation, super-sized platform operators shall establish compliance departments, and freight platforms are encouraged to set up mobile CCP branches.  The AI judiciary must adhere to a holistic approach to national security and align with socialist values. Data and Privacy (84-94) Efficiency  Implementing the national big data strategy, enhancing R&D in key big data technologies and products, as well as constructing big data infrastructure (e.g., national integrated big data center, smart city space-time big data platform).  Establishing a data classification and protection system, as well as a cross-departmental, cross-regional mechanism for data circulation and application.  Establishing a robust national public data resource system and legally opening the data.  Utilizing big data to serve the real economy and integrating big data with public services (e.g., education, medical treatment, and judiciary).  Establishing an income distribution mechanism aligned with the value and contribution of data elements. Social Stability and Political/ Public  No individual or organization shall use the network to jeopardize national security, incite subversion of state power, or overthrow the socialist system.  Data collection and personal information processing must not jeopardize national security or the public interest.  Establishing a consumer privacy and commercial secrets protection system in a cyber environment, a data security review and emergency response system, as well as a network and data security monitoring, warning, and information notification system.  Individuals have the right to be informed and to decide how their personal information is handled. -- 22 of 24 -- 23 Security  Government agencies processing personal information in the fulfillment of their legal duties shall inform the individuals concerned. Trade Union Initiatives (95-103) Efficiency  Enhancing female employees’ digital skills, as well as providing vocational education and job skills training for platform workers.  Establishing digital artisans’ schools and practice centers, as well as creating websites, mobile apps, and public accounts to enhance digital skills. Social Stability  Encouraging the use of AI in trade union work (e.g., building corpora and large language models) and enhancing trade union cadres’ digital skills.  Ensuring funding for digitization initiatives, unionizing platform workers, and incorporating digitization into the evaluation criteria of trade unions.  Constructing coordination and consultation mechanisms (e.g., trade unions and democratic management systems in platform companies; trade unions at regional/industrial, township, neighborhood, and industrial park levels shall organize platform workers; establish platform workers’ trade union associations).  Establishing an occupational injury insurance system for platform workers. Political/ Public Security  Union data processing activities must ensure national security and the security of critical work data and personal information.  Strengthening female employees’ awareness of digital security risks.  Incorporating platform workers into the union will be considered as part of the assessment of union formation and membership development. Notes: 1.Interim Measures for the Administration of Generative Artificial Intelligence Services; 2.Implementation Opinions on Promoting IPv6 Technology Evolution and Application Innovation and Development; 3.Measures for the Administration of Generative Artificial Intelligence Services (Exposure Draft); 4.Measures for Scientific and Technological Ethics Review (for Trial Implementation) (Exposure Draft); 5.Outline to Improve Quality of Development; 6.Outline of the Plan for the Domestic Demand Expansion Strategy (2022-2035); 7.Opinions on Regulating and Strengthening the Applications of Artificial Intelligence in the Judicial Fields; 8.Provisions on the Administration of Deep Synthesis of Internet Internet-Based Services; 9.Opinions on Strengthening the Building of a Highly Skilled Workforce for the New Era; 10.Notice on Supporting the Construction of a New Generation of Artificial Intelligence Demonstration Application Scenarios; 11.Guidance on Accelerating Scenario Innovation and Promoting High-quality Economic Development with High-level Application of Artificial Intelligence; 12.Guidance Training Program for Graduate Students in Artificial Intelligence (for Trial Implementation); 13.Opinions on Strengthening the Governance over Ethics in Science and Technology; 14.The 14th Five-Year Plan for National Informatization; 15.The 14th Five-Year Plan for for the Modernization of Market Regulation; 16.The 14th Five-Year Plan for Development of the Digital Economy; 17.The 14th Five-Year Plan for the Big Data Industry; 18.Action Plan for Enhancing Nationwide Digital Literacy and Skills; 19.Opinions on Promoting High-Quality Development of Modern Vocational Education; 20.Ethical Norms for New Generation Artificial Intelligence; 21.Rules for the Administration of the Road Testing and Demonstrative Application of Intelligent Connected Vehicles (for Trial Implementation); 22.Outline of the Nationwide Scientific Literacy Action Plan (2021-2035); 23.Implementation Plan of Computing Power Hub of National Integrated Big Data Center Collaborative Innovation System; 24.Outline of the 14th Five-Year Plan (2021-2025) for National Economic and Social Development and Vision 2035 of the People’s Republic of China; 25.Guidelines for Work to Construct National Pilot Zones for Innovative Development of New-Generation Artificial Intelligence (Revision); 26.Guidelines for the Construction of a National New Generation Artificial Intelligence Standards System; 27.Several Policies for Promoting the High-Quality Development of the Integrated Circuit Industry and the Software Industry in the New Era; 28.Strategies for the Innovative Development of Intelligent Vehicles; 29.Several Opinions on “Double First-Class” Construction of Colleges and Universities to Promote the Integration of Disciplines and Speed up the Education of Postgraduate Students in the Field of Artificial Intelligence; 30.Implementation Opinions on Deepening the Integrated Development of Advanced Manufacturing and Modern Service Industries; 31.Guidelines on Promoting the Development of Artificial Intelligence in Forestry and Grassland; 32.Guidance on Accelerating the Cultivation of New Business Modes and Formats of Shared Manufacturing to Promote High-quality Development of the Manufacturing Industry; 33.Work Guidelines for the Construction of National Open Innovation Platforms for the New Generation Artificial Intelligence; 34.Governance Principles for the New Generation Artificial Intelligence - Developing Responsible Artificial Intelligence; 35.Vocational Skills Improvement Action Plan (2019-2021); 36.Provisions on the Security Assessment for Internet Information Services with Characteristics of Public Opinions or Capable of Social Mobilization; 37.Work Program of Key Tasks for New Generation of Artificial Intelligence Industry Innovation; 38.Educational Informatization 2.0 Action Plan; 39.Artificial Intelligence Innovation Action Plan for Institutions of Higher Education; 40.General Senior High School Curriculum Program and Curriculum Standards for Chinese Language and Other Subjects (2017 Edition); 41.Three-year Action Plan for Promoting the Development of New Generation of Artificial Intelligence Industry (2018-2020); 42.Guidance of the State Council on Deepening the “Internet plus Advanced Manufacturing” and Developing the Industrial Internet; 43.The Development Plan on the New Generation of Artificial Intelligence; 44.The 13th Five-Year Plan for the National Informatization; 45.Intelligent Manufacturing Development Plan (2016-2020); 46.The 13th Five-Year National Plan for the Development of Strategic Emerging Industries; 47.Special Action on Intelligent Hardware Industry Innovation and Development (2016-2018); 48.The 13th Five-Year National Plan for the National Science and Technology Innovation; 49.Outline of the Innovation-Driven Development Strategy; 50.“Internet+” and Artificial Intelligence Three-Year Action and Implementation Plan; 51.Robotics Industrial Development Plan (2016-2020); 52.Implementation of the Intelligent Manufacturing Development Plan (2016-2020); 53.Outline of the 13th Five-Year Plan for the National Economic and Social Development of the People’s Republic of China; 54.Guidance of the State Council on Vigorously Advancing the “Internet Plus” Action; 55.Made in China (2025); 56.Several Policies on Further Encouraging the Development of the Software and Integrated Circuit Industry; 57.Several Policies on Encouraging the Development of Software Industry and Integrated Circuit Industry; 58.Notice on Strengthening the One-Stop Mediation for Labor Disputes in New Forms of Employment; 59.Guidelines for Guaranteeing the Rest and Labor Remuneration Rights and Interests of Workers in New Forms of Employment; 60.Guidelines for the Publicity of Labor Rules for Workers in New Forms of Employment; 61.Service Guidelines for Protecting the Rights and Interests of Workers in New Forms of Employment; 62.Guidelines for the Conclusion of Employment Contracts or Written Agreements with Workers Employed in New Forms (for Trial Implementation); 63.Opinions on Providing Judicial Services and Guarantees for Stabilizing Employment; 64.Anti-monopoly Law; 65.Provisions on the Administration of Algorithm-generated Recommendations for Internet Information Services; 66.Opinions on Promoting the Standardized and Healthy Development of the Platform Economy; 67.Opinions on Strengthening the Protection of the Rights and Interests of Workers in New Forms of Transportation Industry; 68.Guidelines for Internet Platform Categorization and Grading (Exposure Draft); 69.Guidelines for Implementing the Primary Responsibility of Internet Platforms (Exposure Draft); 70.Opinions on Strengthening the Protection of the Rights and Interests of Truck Drivers; 71.Guidance on Strengthening the Comprehensive Governance of Network Information Service Algorithms; 72.Regulations on the Prohibition of Unfair Competition on the Internet (Exposure Draft); 73.Guidance on Implementing the Responsibilities of Online Catering Platforms to Effectively Protecting the Rights and Interests of Takeout Delivery Personnel; 74.Guidance on Protecting the Labor Rights and Interests of Workers in New Forms of Employment; 75.Measures for the Supervision and Administration of Online Trading; 76.Guidance for Anti-monopoly in the Field of Platform Economy; 77.Implementation Outline for Building a Law-based Society (2020-2025); 78.Provisions on the Governance of the Online Ecosystem (Exposure Draft); 79.Guidance on Promoting the Well-regulated and Sound Development of the Platform Economy; 80.Notice on Effectively Conducting the Work concerning the Guidance and Regulation of the Sound and Positive Development of the Sharing Economy; 81.Guidance on Promoting the Development of the Sharing Economy; 82.Interim Measures for the Administration of Online Taxi Booking Business Operations and Services; 83.Guidance on Deepening Reform and Promoting the Sound Development of the Taxi Industry; 84.Measures for Cybersecurity Review; 85.Personal Information Protection Law; 86.Three-Year Action Plan for New Data Center Development (2021-2023); 87.Data Security Law; 88.Civil Code; 89.Technical Outline for the Construction of Smart City Space-Time Big Data Platform (2019 Version); 90.Technical Outline of Smart City Space-Time Big Data and Cloud Platform Construction (2017 Version); 91.Interim Provisions on the Administration of the Pre-Installation and Distribution of Application Software for Smart Mobile Terminals; 92.Cybersecurity Law; 93.Outline of the National Informatization Development Strategy; 94.State Security Law; 95.Digital Skills Upgrading Program for Female Workers; 96.ACFTU’s Actions to Widely Apply Artificial Intelligence; 97.Plan to Accelerate the Digitization of Trade Unions; 98.Three-year Action Plan to Promote Unionization of Workers in New Forms of Employment; 99.Notice on Promoting the Construction of a Coordination and Consultation Mechanism for the Rights and Interests of Workers in New Forms of Employment; 100.Guidance on Further Advancing -- 23 of 24 -- 24 “Grassroots Unionization” Work; 101.Amendment to the Trade Union Law; 102.Several Opinions on Promoting the Unionization of Workers in New Forms of Employment; 103.Program to Promote the Unionization of Truck Drivers and Other Groups. -- 24 of 24 --