Agora: Teaching the Skill of Consensus-Finding with AI Personas Grounded in Human Voice

2026-03-07

AI Summary

This study addresses the widespread lack of opportunities for citizens to practice negotiating among diverse viewpoints, weighing competing values, and reaching consensus. To bridge this gap, the authors propose an interactive AI platform powered by large language models (LLMs) that innovatively integrates authentic human perspectives with AI personas to create a scalable simulation environment for policy deliberation. The system incorporates a dynamic feedback mechanism that supports users in reflecting on and revising their positions. Notably, it is the first to structurally embed real public opinion data into an AI-mediated dialogue system at scale, thereby fostering deliberative competencies across broad populations. Preliminary experiments demonstrate that participants using the full interface significantly outperform those exposed only to aggregated data in problem-solving capacity, depth of internal deliberation, and quality of consensus statements.

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Multiagent Systems: Agreement, Argumentation & Negotiation
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation

Abstract

Deliberative democratic theory suggests that civic competence: the capacity to navigate disagreement, weigh competing values, and arrive at collective decisions is not innate but developed through practice. Yet opportunities to cultivate these skills remain limited, as traditional deliberative processes like citizens'assemblies reach only a small fraction of the population. We present Agora, an early-stage AI-powered platform that uses LLMs to organize authentic human voices on policy issues, helping users build consensus-finding skills by proposing and revising policy recommendations, hearing supporting and opposing perspectives, and receiving feedback on how policy changes affect predicted support. In a preliminary study with 44 university students, participants using the full interface (with access to voice explanations) reported higher levels of problem-solving skills, internal deliberation, and produced higher quality consensus statements compared to a control condition showing only aggregate support distributions. These initial findings point toward a promising direction for scaling civic education.

Problem

• deliberative democracy
• civic competence
• consensus-finding
• AI personas
• civic education

Innovation

• AI personas
• consensus-finding
• deliberative democracy
• large language models
• civic education