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.
Exploring new rituals, formats, and structures for coming together
Pilots & Programs
An auditable AI framework for tracing competing narratives across podcasts, conversations, and news
Research
Discovering semantically or emotionally salient moments in spoken discourse using LLMs
Research
A new civic infrastructure in Boston grounded in dialogue as a way to building “civic muscle” of democracy
Pilots & Programs
An AI interface that turns raw conversation audio into interactive maps
Research
A training ground to practice consensus-finding with real human perspectives
Research