Automated Analysis of Global AI Safety Initiatives: A Taxonomy-Driven LLM Approach

1. 1Define a shared taxonomy of activities for AI safety initiatives
2. 2Extract and map relevant activities from policy documents using LLMs
3. 3Produce summaries, comparisons, and similarity scores for each aspect
4. 4Assess the stability and validity of LLM-based crosswalk analysis

AI researchers and engineers on a team can benefit from this approach to compare and analyze AI safety policies, while product managers and entrepreneurs can use the insights to inform their AI development strategies

💡 A taxonomy-driven LLM approach can efficiently compare and analyze AI safety initiatives

🚀 Automate AI safety policy analysis with LLMs! 🤖