Research
Sensemaking often demands significant human effort to identify themes, summarize insights, and share findings with community partners. This ongoing project explores how AI can support and streamline the process—reducing time and labor while preserving quality and human agency. By integrating AI, researchers aim to enhance consistency across sensemakers, offer training support, and facilitate the sharing of best practices. The goal is to design a human-led, AI-assisted approach that makes qualitative analysis more accessible and scalable.
An AI interface that turns raw conversation audio into interactive maps
Research
An LLM-Powered Framework for Analyzing Collective Idea Evolution and Voting Dynamics in Deliberative Assemblies
Research
Supporting decision makers in effective and efficient constituency-informed, AI-supported decision-making. Communicating how constituen...
Research
A curated social experience that transforms dinner between strangers into an opportunity to reimagine how we listen, speak, and share
Research
Over 40 young people participated in a social listening experiment exploring how personal experiences build bridges to better understanding current events and creating mo
Pilots & Programs
A new civic infrastructure in Boston grounded in dialogue as a way to building “civic muscle” of democracy
Pilots & Programs
