cs.HCSep 17, 2026

AI Should Facilitate Democratic Deliberation at Scale

Authors: José Ramón EnríquezJiaxin PeiAlex Pentland

Organizations: Stanford Graduate School of Business, Stanford, CA, USA · Stanford Institute for Human-Centered AI, Stanford, CA, USA · MIT Media Lab, Cambridge, MA, USA

Abstract

AI systems can strengthen democracy by supporting deliberation at scale by addressing cognitive, social, platform-design, and market-driven frictions, while preserving human agency. Unlike proposals such as liquid democracy that restructure representation through vote delegation, in this position paper, we argue that AI-assisted deliberation offers a more promising path by lowering barriers to meaningful engagement without substituting machine judgment for human choice. Drawing on evidence from online deliberation platforms and experimental research, we identify four guiding principles: preserving agency and autonomy, encouraging mutual respect, promoting equality and inclusiveness, and augmenting rather than substituting active citizenship. We also address critical challenges, including alignment, sycophancy, training bias, and over-reliance on AI systems. We call on the machine learning community to develop deliberation-focused AI systems evaluated not on engagement metrics but on their capacity to facilitate informed, representative, and friction-robust discourse.

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