Democratizing AI Governance: Balancing Expertise and Public Participation
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Abstract (arXiv)
The development and deployment of artificial intelligence (AI) systems, with their profound societal impacts, raise critical challenges for governance. Historically, technological innovations have been governed by concentrated expertise with limited public input. However, AI's pervasive influence across domains such as healthcare, employment, and justice necessitates inclusive governance approaches. This article explores the tension between expert-led oversight and democratic participation, analyzing models of participatory and deliberative democracy. Using case studies from France and Brazil, we highlight how inclusive frameworks can bridge the gap between technical complexity and public accountability. Recommendations are provided for integrating these approaches into a balanced governance model tailored to the European Union, emphasizing transparency, diversity, and adaptive regulation to ensure that AI governance reflects societal values while maintaining technical rigor. This analysis underscores the importance of hybrid frameworks that unite expertise and public voice in shaping the future of AI policy.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 25 references that are in the map. First posted on arXiv 16 Jan 2025.
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Citing papers per year: 2026: 1.
1 paper.
- 2026Scaling Participation in Modular AI Systemscited by 2
- 2026Scaling Participation in Modular AI Systems5 Jun 2026