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China Issues Guidelines for AI Large Models in Government

China Releases Framework for Government AI Adoption

The Cyberspace Administration of China and the National Development and Reform Commission have jointly issued "Guidelines for the Deployment and Application of Artificial Intelligence Large Models in the Government Sector." This landmark document establishes a framework for safe and effective AI implementation across all levels of government administration.

Strategic Implementation Approach

The guidelines recommend focusing on high-frequency needs including:

  • Government services
  • Social governance
  • Office automation
  • Decision support systems

Image

Image source note: The image was generated by AI, and the image licensing service provider is Midjourney

Authorities emphasize adapting implementations to local conditions, allowing regions to develop tailored solutions while maintaining national standards. The document specifically warns against creating "model islands" through isolated development efforts.

Resource Optimization Measures

Key operational principles include:

  1. "One region construction, multiple reuse" model to maximize efficiency
  2. Shared infrastructure development to prevent duplication
  3. Balanced workload reduction with meaningful empowerment The guidelines explicitly caution against digital formalism - superficial technology adoption without substantive operational improvements.

Safety and Governance Framework

The document establishes comprehensive safeguards:

  • Full-cycle management systems
  • Clear application boundaries
  • Defined supportive (non-decision-making) roles for AI models Special attention addresses potential risks like model "hallucinations" through technical controls and operational protocols.

The release signals China's commitment to intelligent governance transformation, aiming to enhance public service delivery while maintaining strict oversight of emerging technologies.

Key Points:

  • Establishes national standards for government AI applications
  • Promotes resource sharing across departments/regions
  • Balances innovation with risk management
  • Targets practical efficiency gains over symbolic adoption
  • Positions AI as decision-support rather than autonomous systems

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