Navigating the complexities of AI and digital governance: the 5W1H framework - S. Matthew Liao; Iskandar Haykel; Katherine Cheung; Taylor Matalon (Journal of Responsible Technology)
As AI and digital technologies advance rapidly, governance frameworks struggle to keep pace with emerging applications and risks. This paper introduces a ''5W1H'' framework to systematically analyze AI governance proposals through six key questions: What should be regulated (data, algorithms, sectors, or risk levels), Why regulate (ethics, legal compliance, market failures, or national interests), Who should regulate (industry, government, or public stakeholders), When regulation should occur (upstream, downstream, or lifecycle approaches), Where it should take place (local, national, or international levels), and How it should be enacted (hard versus soft regulation). The framework is applied to compare the European Union's AI Act with the current U.S. regulatory landscape, revealing the EU's comprehensive, risk-based approach versus America's fragmented, sector-specific strategy. By providing a structured analytical tool, the 5W1H framework helps policymakers, researchers, and stakeholders navigate complex AI governance decisions and identify areas for improvement in existing regulatory approaches.