Exploring the intersection of artificial intelligence, policy design, and governance through rigorous research and practical applications.
Traditional policy analysis often confuses correlation with causation, leading to ineffective interventions. We explore how causal inference methods can revolutionize policy design by identifying true cause-and-effect relationships.
Exploring how agent-based simulations can address the limitations of current AI forecasting paradigms by modeling dynamic social responses and stakeholder interactions in complex systems.
Why policymakers need to adopt experimental approaches to navigate technological uncertainty and rapid change in the 21st century.
A comparative analysis of different AI governance approaches and their implications for innovation, safety, and economic development.
Exploring how AI can assist in generating policy alternatives by synthesizing vast amounts of research, case studies, and expert knowledge.
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