AI Strategy Convergence and Divergence: A Policy Design Element Analysis
A recent study published on arXiv (2608.11006v2) investigates 74 national and 3 regional AI strategies, focusing on the similarities and differences in their policy design. This research, which encompasses a global overview of all 205 UN member and non-member nations, employs a latent-inductive coding method to analyze three key policy design components: goals, approaches, and principles. By exploring whether these components are converging or diverging horizontally (between countries) or vertically (between regions and countries) over time, the paper addresses a significant gap in existing research. It aims to equip policy designers with a thorough set of design elements for the ongoing development of AI strategies, highlighting common practices and regional distinctions in governmental responses to AI's rapid growth.
Key facts
- Paper on arXiv: 2608.11006v2
- Analyzes 74 national and 3 regional AI strategies
- Global scan of all 205 UN member and non-member states
- Coding uses latent-inductive approach
- Three functional policy design elements: goals, approaches, principles
- Examines horizontal (country-to-country) and vertical (region-to-country) convergence/divergence
- Two research questions guide the analysis
- Aims to provide comprehensive policy design elements for AI strategy development
Entities
Institutions
- arXiv
- United Nations