Guided Sensemaking: Agents in Collaborative Deliberation
2026-06-01 • Human-Computer Interaction
Human-Computer Interaction
AI summaryⓘ
The authors explain that current AI tools often give quick answers but don't help with deep thinking or teamwork. They created Guided Sensemaking, a system where multiple AI agents help users carefully organize ideas and think critically about a question. This system encourages users to explore different viewpoints and build arguments together, treating AI as a thoughtful helper rather than just an answer machine. Their goal is to support better learning and collaboration by making reasoning clear and interactive.
Generative AICritical ThinkingCollaborative DeliberationMultiagent SystemsArgument VisualizationSensemakingScaffoldingHuman-AI InteractionCognitive Work
Authors
Aaditya Bhatia, Navdeep Kaur Bhatia, Marc-Antoine Parent, Jack Park
Abstract
Generative AI systems are aggressively reshaping how students engage with information and perform cognitive work; convenience-oriented use has the potential to displace effortful reasoning, reflection, and learning, especially for those who lack domain expertise and effective human-AI interaction strategies. Current AI tools are heavily focused on chat-style interfaces geared towards answer generation and efficiency in a linear and fragmented stream of text, offering limited support for structured reflection, argument construction, and sensemaking in collaborative contexts. We introduce Guided Sensemaking, an AI-augmented multiagent discourse platform that facilitates composition of well-thought-out ideas around a central question, provides scaffolding for critical thinking, and enables visualization of argumentative structure to support critical thinking and collaborative deliberation. The system uses several interactive agents to provide context-sensitive questioning prompts and a scaffolding for thought that exposes thematic clusters, agreements, and points of contention without collapsing diverse perspectives. This paper proposes a conceptual design and interaction paradigm that positions generative AI not as a shortcut to answers but as a research partner that externalizes reasoning, preserves user agency, and fosters structured, traceable sensemaking in educational and civic contexts.