Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Risks
Oier Mentxaka, Natalia Díaz-Rodríguez, Mark Coeckelbergh, Marcos López de Prado, Emilia Gómez, David Fernández Llorca, Enrique Herrera-Viedma, Francisco Herrera
TL;DR
This paper argues that AI can both threaten and strengthen democracy. It introduces two complementary taxonomies—AIRD (AI's Risks to Democracy) and AIPD (AI's Positive Contributions to Democracy)—to systematically map democratic harms and benefits to the EU's seven Trustworthy AI requirements. A cross-cutting finding is that transparency and societal wellbeing are central to preserving democratic integrity, guiding governance, regulation, and system design. By grounding the framework in democratic theory and EU governance tools, the work offers a normative and actionable path for researchers, policymakers, and technologists to align AI with democratic values in diverse contexts, including frontier AI developments like LLMs.
Abstract
Artificial Intelligence (AI) poses both significant risks and valuable opportunities for democratic governance. This paper introduces a dual taxonomy to evaluate AI's complex relationship with democracy: the AI Risks to Democracy (AIRD) taxonomy, which identifies how AI can undermine core democratic principles such as autonomy, fairness, and trust; and the AI's Positive Contributions to Democracy (AIPD) taxonomy, which highlights AI's potential to enhance transparency, participation, efficiency, and evidence-based policymaking. Grounded in the European Union's approach to ethical AI governance, and particularly the seven Trustworthy AI requirements proposed by the European Commission's High-Level Expert Group on AI, each identified risk is aligned with mitigation strategies based on EU regulatory and normative frameworks. Our analysis underscores the transversal importance of transparency and societal well-being across all risk categories and offers a structured lens for aligning AI systems with democratic values. By integrating democratic theory with practical governance tools, this paper offers a normative and actionable framework to guide research, regulation, and institutional design to support trustworthy, democratic AI. It provides scholars with a conceptual foundation to evaluate the democratic implications of AI, equips policymakers with structured criteria for ethical oversight, and helps technologists align system design with democratic principles. In doing so, it bridges the gap between ethical aspirations and operational realities, laying the groundwork for more inclusive, accountable, and resilient democratic systems in the algorithmic age.