Research Lab
Pollster introduces a new approach for measuring the effects of media consumption, and for predicting media-driven public opinion. Our approach leverages advances in deep neural network -based language modeling to model populations with specific media diets. We validate our approach using ground-truth surveys in two domains: attitudes towards COVID-19, and consumer confidence. This approach could be used to supplement existing surveys, help public health officials and others improve their messaging, and ultimately inform policy makers.
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