An Evaluation Framework for National AI Regulation

The document introduces a novel evaluation framework designed to assess the documented design and implementation readiness of national AI policies. This framework is crucial for comparing diverse national approaches to AI regulation, which often involve a mix of laws, institutions, funding, and non-binding guidance. The research applies this framework to compare AI policy instruments across China, India, Japan, Singapore, South Korea, the United Kingdom, the United States, and the European Union as a supranational entity.

Why it matters

This framework offers a structured methodology for understanding and comparing the global landscape of AI governance. For organizations operating internationally or developing AI, understanding the nuances of different national regulatory environments is critical for strategic planning, market entry, and compliance. This analysis contributes to better-informed decisions regarding investment, innovation, and risk management in the context of evolving AI policy.

Key insights

• Governments employ various instruments, including laws, institutions, funding, and non-binding guidance, to direct AI development and deployment.
• Comparing national AI policy approaches is inherently complex due to the varied nature of these instruments and their differing implications for duties and resource requirements.
• The proposed framework evaluates a versioned portfolio of official policy instruments, moving beyond the assessment of single prominent laws or strategies.
• The evaluation covers key global players and a supranational body, indicating a comprehensive scope for comparative analysis.
• The framework focuses on assessing the 'documented design' and 'implementation readiness' of AI policy.
• Different types of policy instruments (e.g., binding rules vs. voluntary frameworks) can address similar problems but create distinct obligations and resource needs.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.15417