Recommends coordinating AI security standards, emphasizing ethical principles, and accelerating standards development in key areas. Promotes AI security standards application, talent training, and international collaboration. Suggests high-risk AI early warning mechanisms and improving AI security supervision and supply chain management.
Analysis summaries, actor details, and coverage mappings were LLM-classified and may contain errors.
This is a white paper providing recommendations for AI security standardization work, using voluntary language throughout ('we recommend', 'should be') without binding legal obligations or enforcement mechanisms.
The document has good coverage of approximately 10-12 subdomains, with strong focus on AI system security (2.2), malicious actors and cyberattacks (4.1, 4.2), governance failure (6.5), competitive dynamics (6.4), and AI safety failures (7.1, 7.2, 7.3, 7.4). Coverage is concentrated in security, governance, and AI system robustness domains.
The document governs AI security across multiple critical infrastructure sectors including telecommunications, energy, transportation, power, and finance. It also addresses manufacturing (smart manufacturing, intelligent networked vehicles) and consumer products (smart homes, smart door locks). The governance is cross-sectoral with emphasis on supply chain security management.
The document comprehensively covers all AI lifecycle stages, with particular emphasis on the Plan and Design stage (ethical principles, security architecture), Build and Use Model stage (algorithm security, model trustworthiness), and Operate and Monitor stage (ongoing supervision, supply chain management). It addresses the entire lifecycle from initial planning through deployment and operational monitoring.
The document broadly addresses AI systems, models, algorithms, and products without defining specific technical categories. It mentions AI technologies, products, and applications generally, with references to algorithm models, smart products, and open source frameworks. No specific compute thresholds, frontier AI, or GPAI definitions are provided.
National Information Security Standardization Technical Committee (implied as the authoring body of this white paper)
The document is a white paper providing recommendations for AI security standardization work in China, with references to government planning and national standardization efforts. The National Information Security Standardization Technical Committee is explicitly mentioned as having carried out standards development work.
Chinese government agencies responsible for AI security supervision and standardization oversight
The document recommends that government establish monitoring and supervision systems for AI security, though specific enforcement agencies are not named. References to government supervision and regulatory frameworks indicate governmental enforcement role.
Pilot enterprises, universities, research institutes, and government agencies involved in standards evaluation and implementation tracking
The document establishes monitoring mechanisms through pilot programs and evaluation systems, with multiple stakeholders involved in tracking standards implementation and effectiveness.
Chinese AI industry participants including universities, scientific research institutes, enterprises, and government departments across telecommunications, energy, transportation, power, and finance sectors
The document targets multiple stakeholder groups involved in AI development, deployment, and governance. It explicitly addresses enterprises developing AI products, government agencies implementing supervision, and organizations across critical infrastructure sectors.
13 subdomains (4 Good, 9 Minimal)