Amplifying Minority Voices: AI-Mediated Devil's Advocate System for Inclusive Group Decision-Making
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912226284142592 |
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| author | Lee, Soohwan Kim, Mingyu Hwang, Seoyeong Kim, Dajung Lee, Kyungho |
| author_facet | Lee, Soohwan Kim, Mingyu Hwang, Seoyeong Kim, Dajung Lee, Kyungho |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_06251 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Amplifying Minority Voices: AI-Mediated Devil's Advocate System for Inclusive Group Decision-Making Lee, Soohwan Kim, Mingyu Hwang, Seoyeong Kim, Dajung Lee, Kyungho Human-Computer Interaction 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. |
| title | Amplifying Minority Voices: AI-Mediated Devil's Advocate System for Inclusive Group Decision-Making |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2502.06251 |