Social and Behavioral Dynamics

As AI continues to reshape economies, work, and daily life, we face societal challenges that exceed the capacity of individuals acting alone, instead they require collective intelligence (CI) for large-scale coordination and problem-solving. We investigate how AI can augment human CI by enhancing three key components: collective memory, collective attention, and collective reasoning. Our findings show that AI can boost productivity while also strengthening a group’s ability to think, learn, and act together, highlighting its potential to be designed and deployed in human-centered ways that amplify creativity, collaboration, and societal resilience.

How does misinformation spread, why does it persist, and how can it be effectively corrected? To answer these questions we study the cognitive and social factors that drive belief in false information, and test strategies to improve the impact of corrections, particularly in critical areas like health, with a focus on cancer misinformation. We also investigate how misinformation propagates through social media, the role of platform algorithms, and the effectiveness of interventions such as content labeling. This work informs evidence-based approaches to reducing misinformation’s influence and improving public understanding across domains of science, health, and politics.

Supported by the National Science Foundation, the National Internet Observatory (NIO) seeks to advance understanding of how people behave online and how digital platforms shape their experiences. By inviting U.S. residents to participate in a scientific study, the NIO collects data through software installed on participants’ computers, capturing detailed information about their online activities. The Observatory then provides privacy-preserving access to this data for researchers across disciplines. This two-step approach enables comprehensive research into the Internet’s impact on individuals and society.