Research
Making visible dynamics within conversations enables us to see conversation quality, dynamics between participants, the impact of facilitators, and perhaps even quality of the conversation itself. In this project, we leverage natural language processing, machine learning, data visualization, and human-computer interaction techniques to unveil and create metrics for dynamics within conversations in an effort to evaluate quality of conversation.
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