Encourages primary and secondary schools to add, expand, and improve AI education. Urges higher education institutions to integrate AI into courses and promote interdisciplinary talent cultivation. Suggests using AI to transform education governance, scientific research, and vocational education. Strengthens international cooperation and security mechanisms for AI applications.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the risk subdomain are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.
All other risk subdomains had no coverage in this document.
Risk Coverage Summary
The document has minimal to good coverage of approximately 6-7 subdomains, with primary focus on AI system security (2.2), privacy protection (2.1), fraud prevention (4.3), toxic content filtering (1.2), value alignment (7.1), and inequality mitigation (6.2). Coverage is concentrated in security, misuse prevention, and equity domains within the education context.
Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.
Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.
All other sectors had no coverage in this document.
Sectors Summary
This document primarily governs AI use in the Educational Services sector with comprehensive coverage of primary, secondary, higher, and vocational education. It also addresses Scientific Research and Development Services through its focus on AI-driven research paradigms and innovation platforms in educational institutions.
Soft Law
Legislative Status Summary
This is a policy action plan from the Chinese central government that uses predominantly mandatory language ('shall') but lacks explicit enforcement mechanisms, penalties, or sanctions. It functions as strategic governmental guidance with implementation delegated to education departments and localities.
Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems
AI Lifecycle Summary
The document comprehensively covers most AI lifecycle stages with particular emphasis on Plan and Design, Build and Use Model, Deploy, and Operate and Monitor. It extensively addresses curriculum design, AI model development (education large models), deployment of AI applications throughout educational institutions, and ongoing monitoring and assessment systems.
Terms relating to technical scope that are mentioned or implicitly referenced in the document
Technical Scope Summary
The document explicitly mentions AI models and AI systems throughout, with particular emphasis on 'education large models' as a key technical scope. It does not specifically mention frontier AI, GPAI, foundation models, or compute thresholds. The focus is on developing and deploying AI models and systems specifically for educational applications.
Document data from AGORA, CSET Emerging Technology Observatory.