White Paper on Artificial Intelligence Standardization 2021

• Authority: Other authorities
• Collections: Chinese law and policy
• Most recent activity: Proposed
• Most recent activity date: 2021-07-21

Risk subdomain coverage

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the risk subdomain are described.

• Governance failure

All other risk subdomains had no coverage in this document.

Risk Coverage Summary

This document has minimal coverage of AI risk domains, with only subdomain 6.5 (Governance Failure) receiving a coverage score of 2. The document primarily focuses on standardization mechanisms and international collaboration rather than addressing specific AI risks and harms. Most risk subdomains are not mentioned.

Sector coverage

Good coverage — Comprehensive governance measures or mitigations with clear procedures relating to the sector are explicitly described.

• Information

Minimal coverage — Brief mention but no specific mitigations, recommendations or governance measures relating to the sector are described.

• Trade, Transportation & Utilities
• Scientific Research & Development Services
• Educational Services
• Health Care & Social Assistance
• Public Administration (excl. National Security)

All other sectors had no coverage in this document.

Sectors Summary

The document primarily governs AI standardization across multiple sectors with explicit focus on Transportation (smart transportation), Health Care (smart healthcare), and Educational Services (smart classrooms). It also addresses the Information sector through references to IoT, cloud computing, and big data integration, and implicitly covers Scientific Research and Development Services through standardization development activities.

Legislative Status

Soft Law

Legislative Status Summary

This document is a white paper that provides recommendations and guidance for AI standardization work in China. It uses predominantly voluntary language ('should be', 'must be promoted') and focuses on coordination, development of standards, and international collaboration without establishing binding legal obligations or enforcement mechanisms.

Actors

Proposer

• Entity Types: AI_Governance_Actor
• Summary: The document is proposed by Chinese government standardization bodies, specifically mentioning the National AI standardization working group platform and technical committees that coordinate AI standardization work.

Target

• Entity Types: AI_Developer, AI_Deployer, AI_Governance_Actor
• Summary: The document targets multiple stakeholders in the AI ecosystem including industry developers, deployers, government agencies, and research institutions that participate in AI standardization and application.

Enforcer

• Entity Types: AI_Governance_Actor
• Summary: The document assigns a guiding and promotional role to government departments at various levels to strengthen AI standardization implementation.

Monitor

• Entity Types: AI_Governance_Actor
• Summary: The document establishes monitoring and evaluation mechanisms through pilot zones and public service platforms that assess standard compliance and provide technical services.

AI Lifecycle Stages

Lifecycle stages covered by the documents, as defined in the OECD Framework for the Classification of AI Systems

• Plan and Design
• Build and Use Model
• Verify and Validate
• Deploy
• Operate and Monitor

AI Lifecycle Summary

The document covers multiple AI lifecycle stages with primary focus on Plan and Design (standardization frameworks), Build and Use Model (development standards and frameworks), and Deploy (application standards). It also addresses Verify and Validate through testing and evaluation mechanisms, and Operate and Monitor through pilot demonstrations and compliance assessment systems.

Technical Scope

Terms relating to technical scope that are mentioned or implicitly referenced in the document

• AI Models
• AI Systems
• Open Weight / Open Source

Technical Scope Summary

The document mentions AI systems broadly and references specific AI technologies like machine learning models, intelligent speech, and computer vision. It does not explicitly define or distinguish between frontier AI, general purpose AI, task-specific AI, foundation models, generative AI, predictive AI, or discuss compute thresholds or open-weight models.