[2603.27563] InnerPond: Fostering Inter-Self Dialogue with a Multi-Agent Approach for Introspection

Computer Science > Human-Computer Interaction arXiv:2603.27563 (cs) [Submitted on 29 Mar 2026] Title:InnerPond: Fostering Inter-Self Dialogue with a Multi-Agent Approach for Introspection Authors:Hayeon Jeon, Dakyeom Ahn, Sunyu Pang, Yunseo Choi, Suhwoo Yoon, Joonhwan Lee, Eun-mee Kim, Hajin Lim View a PDF of the paper titled InnerPond: Fostering Inter-Self Dialogue with a Multi-Agent Approach for Introspection, by Hayeon Jeon and 7 other authors View PDF HTML (experimental) Abstract:Introspection is central to identity construction and future planning, yet most digital tools approach the self as a unified entity. In contrast, Dialogical Self Theory (DST) views the self as composed of multiple internal perspectives, such as values, concerns, and aspirations, that can come into tension or dialogue with one another. Building on this view, we designed InnerPond, a research probe in the form of a multi-agent system that represents these internal perspectives as distinct LLM-based agents for introspection. Its design was shaped through iterative explorations of spatial metaphors, interaction scaffolding, and conversational orchestration, culminating in a shared spatial environment for organizing and relating multiple inner perspectives. In a user study with 17 young adults navigating career choices, participants engaged with the probe by co-creating inner voices with AI, composing relational inner landscapes, and orchestrating dialogue as observers and mediators, offering insig...