ARGSBASE: A Multi-Agent Interface for Structured Human–AI Deliberation

AbstractWe present a new deliberation interface that enables users to engage with multiple large language models (LLMs), coordinated by a moderator agent that assigns roles, manages turn-taking, and ensures structured interaction. Grounded in argumentation theory, the system fosters critical thinking through user–LLM dialogues, real-time summaries of agreements and open questions, and argument maps. Rather than treating LLMs as mere answer providers, our tool positions them as reasoning partners, supporting epistemically responsible human–AI collaboration. It exemplifies hybrid argumentation and aligns with recent calls for “reasonable parrots,” where LLM agents interact with users guided by argumentative principles such as relevance, responsibility, and freedom. A user study shows that participants found the tool easy to use, perspective-enhancing, and promising for research, while suggesting areas for improvement. We make the deliberation interface accessible for testing and provide a recorded demonstration.