Research
Assumptions are commonplace across human interactions, but while some are harmless, others are not. The present intervention study uses healthcare narratives of invisible disability, which are poorly understood and rarely disclosed due to the stigma experienced by individuals, to reduce false assumptions of others on the basis of visual and semantic cues.
D. T. Kessler, D. Y. Kim, G. S. Ahn, N. Elhaouij and R. Picard, “Assessing Affective Engagement with Narratives of Invisible Disability,” in 2023 11th International Conference on Affective Computing and Intelligent Interaction (ACII), Cambridge, MA, USA, 2023, pp. 1-8, doi: 10.1109/ACII59096.2023.10388159.
An LLM-Powered Framework for Analyzing Collective Idea Evolution and Voting Dynamics in Deliberative Assemblies
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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
An exploration of playful listening through a co-creative AI game
Research
