BCause: Human-AI collaboration to improve hybrid mapping and ideation in argumentation-grounded deliberation
This addresses the challenge of improving public deliberation for communities and policymakers, though it appears incremental as it builds on existing human-AI collaboration methods.
The paper tackles the problem of scattered and shallow discourse in public deliberation by introducing BCause, a system that uses generative AI and human-machine collaboration to transform unstructured dialogue into structured, actionable democratic processes, resulting in innovations like argumentative discussions, geo-deliberated problem-sensing, and smart reporting with customizable widgets.
Public deliberation, as in open discussion of issues of public concern, often suffers from scattered and shallow discourse, poor sensemaking, and a disconnect from actionable policy outcomes. This paper introduces BCause, a discussion system leveraging generative AI and human-machine collaboration to transform unstructured dialogue around public issues (such as urban living, policy changes, and current socio-economic transformations) into structured, actionable democratic processes. We present three innovations: (i) importing and transforming unstructured transcripts into argumentative discussions, (ii) geo-deliberated problem-sensing via a Telegram bot for local issue reporting, and (iii) smart reporting with customizable widgets (e.g., summaries, topic modelling, policy recommendations, clustered arguments). The system's human-AI partnership preserves critical human participation to ensure ethical oversight, contextual relevance, and creative synthesis.