CLAIIRJun 10, 2024

Harnessing AI for efficient analysis of complex policy documents: a case study of Executive Order 14110

arXiv:2406.06657v12 citations
Originality Synthesis-oriented
AI Analysis

It addresses the time-consuming challenge of interpreting policy documents for analysts and policymakers, but is incremental as it applies existing AI methods to a new domain.

This study evaluated AI systems for analyzing complex policy documents like Executive Order 14110, finding that Gemini 1.5 Pro and Claude 3 Opus performed comparably to human experts in accuracy but with higher efficiency.

Policy documents, such as legislation, regulations, and executive orders, are crucial in shaping society. However, their length and complexity make interpretation and application challenging and time-consuming. Artificial intelligence (AI), particularly large language models (LLMs), has the potential to automate the process of analyzing these documents, improving accuracy and efficiency. This study aims to evaluate the potential of AI in streamlining policy analysis and to identify the strengths and limitations of current AI approaches. The research focuses on question answering and tasks involving content extraction from policy documents. A case study was conducted using Executive Order 14110 on "Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence" as a test case. Four commercial AI systems were used to analyze the document and answer a set of representative policy questions. The performance of the AI systems was compared to manual analysis conducted by human experts. The study found that two AI systems, Gemini 1.5 Pro and Claude 3 Opus, demonstrated significant potential for supporting policy analysis, providing accurate and reliable information extraction from complex documents. They performed comparably to human analysts but with significantly higher efficiency. However, achieving reproducibility remains a challenge, necessitating further research and development.

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