Despite our diverse experiences, there’s a surprising similarity across people in what they remember and forget, where some items are more inherently “memorable” than others. Using large-scale online experiments, brain imaging, and AI, Wilma Bainbridge’s work focuses on understanding what we remember and why.

In recent research published in Nature, James Evans, Qianyue Hao, Fengli Xu, and Li Yong ask how AI use has shaped scientific careers and science as a whole. They analyzed more than 40 million research papers spanning four decades of natural science to understand how AI is reshaping science. The findings reveal a paradox.

The ongoing work of Marc Berman and his Environmental Neuroscience Lab examines the external environment by combining human behavioral data with computational models and methods, including machine learning and edge sensing, to study how social and physical surroundings affect behavior. Their goal is to more fully understand which features of the physical environment (e.g., natural fractals) lead to improvements in memory and attention as well as identifying other manipulations that increase brain efficiency. 

The rise of social media as a primary source of news and political discourse presents both opportunities and challenges for political scientists. With the support of a Carnegie Fellowship, Molly Offer-Westort is studying the societal transformations brought about by the internet, particularly regarding political polarization and engagement.

Computational sociologist Bernard Koch explores the mechanisms underlying cultural diversification and collapse in fields like AI, Music, and Science. His work blends AI with Bayesian statistics and interviews to develop evolutionary theories and rich historical narratives. Current research focuses on how different evaluation systems (e.g., peer review, benchmarking) guide scientific fields along different trajectories, with significant ethical, epistemic, and cultural consequences. 

Residential partisan segregation---i.e., the tendency for partisans to live near co-partisans and far from anti-partisans---is an extensive and accelerating trend in the United States. As partisans segregate, opportunities shrink for cross-group contact and dialogue, fueling extremism and distrust. Beyond shaping mass attitudes, partisan segregation may also polarize elites, as both electoral campaigns and news media appeal to fractured constituencies. It is urgent we understand what drives partisan segregation, as such processes can amplify echo chambers and create feedback loops that allow even slight levels of segregation to quickly become extreme.

Working at the intersection of human-computer interaction (HCI), natural language processing (NLP), and computational social science (CSS), Mina Lee investigates and shapes the evolving relationship between humans and AI, with a special focus on writing, reading, and thinking.