J. Nathan Matias of Cornell University
The governance of adaptive algorithms is one of society s most pressing scientific challenges. In public discourse, these algorithms decide what we are allowed to say and rank the information we see. 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 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.
About the speaker:
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 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 an visiting associate research scholar at the Knight First Amendment Institute at Columbia University.
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