J. Nathan Matias
Assistant Professor at Cornell University Department of Communication
April 25, 2023
The governance of adaptive algorithms is one of society’s most pressing scientific challenges. From predictive policing to video recommendations, these algorithms shape outcomes including criminal justice, economic inequality, public health, and social change. Because they adapt to human behaviors that they also influence, their actions have been hard to predict— representing a risk to society and a challenge for anyone who would govern their behavior.
What kinds of knowledge can help us observe and govern these feedback loops between human and machine behavior? And how might this governance challenge require us to rethink how we design the software systems that support this research? This talk, linked with a forthcoming article in *Nature*, will summarize the dilemma of predicting, preventing, and intervening effectively on human algorithm behavior, and how we might develop the knowledge needed to do so.
Matias, J.N., Wright, L. (2022) Impact Assessment of Human-Algorithm Feedback Loops
Dr. J. Nathan Matias organizes citizen behavioral science for a safer, fairer, more understanding internet. A Guatemalan-American, Nathan is an assistant professor in the Cornell University Department of Communication and a field member in Information Science.
Nathan is a 2022-23 Lenore Annenberg and Wallis Annenberg Fellow in Communication and Siegel Research Fellow at the Center for Advanced Study in the Behavioral Sciences, Stanford University. In the summer of 2022-23, he is also a visiting associate research scholar at the Knight First Amendment Institute at Columbia University.
Nathan is the founder of the Citizens and Technology Lab, a public-interest research group at Cornell that organizes citizen behavioral science and behavioral consumer protection research for digital life. CAT Lab has worked with communities of tens of millions of people on Reddit, Wikipedia, and Twitter to test ideas for preventing harassment, broadening gender diversity on social media, responding to human/algorithmic misinformation, managing political conflict, and auditing social technologies. Nathan’s research has been published in PNAS, Nature Human Behavior, FACCT, Computer-Supported-Cooperative Work, CHI, and Behavioral & Brain Sciences. Nathan has received numerous international awards, including awards for computer science and design. His work in journalism has appeared in The Atlantic, PBS, the Guardian, FiveThirtyEight, WIRED, and other international media.