Amplifying Minority Voices: AI-Mediated Devil's Advocate System for Inclusive Group Decision-Making

TL;DR

This paper presents an AI-mediated devil's advocate system using large language models to anonymously amplify minority voices, aiming to enhance inclusivity and psychological safety in group decision-making.

Contribution

It introduces a multi-agent AI architecture that represents minority opinions anonymously, improving diversity and critical thinking in decision processes.

Findings

System encourages critical thinking and minority voice amplification.

Anonymity reduces social influence and power imbalances.

Framework highlights potential for AI to support inclusive decisions.

Abstract

Group decision-making often benefits from diverse perspectives, yet power imbalances and social influence can stifle minority opinions and compromise outcomes. This prequel introduces an AI-mediated communication system that leverages the Large Language Model to serve as a devil's advocate, representing underrepresented viewpoints without exposing minority members' identities. Rooted in persuasive communication strategies and anonymity, the system aims to improve psychological safety and foster more inclusive decision-making. Our multi-agent architecture, which consists of a summary agent, conversation agent, AI duplicate checker, and paraphrase agent, encourages the group's critical thinking while reducing repetitive outputs. We acknowledge that reliance on text-based communication and fixed intervention timings may limit adaptability, indicating pathways for refinement. By focusing on the representation of minority viewpoints anonymously in power-imbalanced settings, this approach highlights how AI-driven methods can evolve to support more divergent and inclusive group decision-making.