CAC Tech Bureau Head on China’s AI-Generated Content Labeling Rules
On February 2, 2026, the head of the Network Management Technology Bureau at China’s Cyberspace Administration published an article explaining the framework behind China’s labeling system for AI-generated content. As generative AI becomes mainstream, the labeling system aims to address governance questions regarding the origin, authorship, and nature of AI-generated content.
Establishment of the AI Labeling System
The AI-Generated and Synthesized Content Labeling Measures represent a mandatory national standard that covers the entire lifecycle of content generation, distribution, and usage. This framework builds upon prior regulations concerning algorithmic recommendations and deep-synthesis technologies, progressively tightening both technical and operational requirements.
The labeling system employs a variety of methods, including corner labels for text and rhythm-based cues for audio, which accommodate different platform capabilities and minimize upgrade costs. This flexible approach allows companies to select solutions that best fit their operational needs.
Collaboration and Implementation
The development of the AI labeling system was a collaborative effort among legal, technical, and standards specialists, with major internet platforms participating in pilot testing. This cooperation ensured that the system was both practical and effective.
Notably, the labeling system incorporates a mix of explicit and implicit labels, allowing platforms to choose options aligned with their technical capacities. Implicit labels, for instance, only retain information about the most recent dissemination platform, preventing unnecessary complexity and cost.
Impact and Compliance
Since the implementation of the AI labeling system, major platforms have rapidly complied with the new requirements. Preliminary statistics reveal that platforms like Doubao and Bilibili have added AI labels to over 150 billion pieces of content, significantly reducing the potential for disinformation.
Public awareness surrounding AI-generated content has also improved, with surveys indicating that 76.4% of internet users have noticed an increase in content labeling, enhancing their ability to identify AI-generated materials.
Addressing Challenges in AI Governance
The AI labeling system serves as a critical mechanism to tackle issues such as disinformation and the malicious use of AI technologies. By clearly defining responsibilities among content creators, disseminators, and users, the system promotes a governance model that encourages accountability and coordination.
Furthermore, the system is designed to adapt to the realities of technological advancements, ensuring that it remains relevant as new challenges arise. It combines regulatory requirements with practical technical solutions, thereby fostering an environment conducive to innovation while maintaining security.
Future Directions
Moving forward, efforts will be made to refine the AI labeling system continually. This includes enhancing technical solutions such as digital watermarking and improving cross-platform interoperability. Additionally, the system aims to encourage international cooperation on AI safety governance, facilitating a balance between technological innovation and risk prevention.
As the landscape of AI continues to evolve, the AI labeling system represents a proactive approach to governance, addressing both current challenges and future developments in the realm of artificial intelligence.
