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김다정

Kim, Dajung
Design Futures Lab
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dc.citation.conferencePlace IT -
dc.citation.endPage 21 -
dc.citation.startPage 17 -
dc.citation.title International Conference on Intelligent User Interfaces -
dc.contributor.author Lee, SooHwan -
dc.contributor.author Kim, Mingyu -
dc.contributor.author Hwang, Seoyeong -
dc.contributor.author Kim, Dajung -
dc.contributor.author Lee, Kyungho -
dc.date.accessioned 2026-01-05T17:03:09Z -
dc.date.available 2026-01-05T17:03:09Z -
dc.date.created 2025-12-29 -
dc.date.issued 2025-03-24 -
dc.description.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. -
dc.identifier.bibliographicCitation International Conference on Intelligent User Interfaces, pp.17 - 21 -
dc.identifier.doi 10.1145/3708557.3716334 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/89813 -
dc.identifier.url https://dl.acm.org/doi/full/10.1145/3708557.3716334 -
dc.language 영어 -
dc.publisher Association for Computing Machinery -
dc.title Amplifying Minority Voices: AI-Mediated Devil’s Advocate System for Inclusive Group Decision-Making -
dc.type Conference Paper -
dc.date.conferenceDate 2025-03-24 -

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