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Guest Speaker

Brandon Stewart, Associate Professor, Department of Sociology, Princeton University

Moderated by: DSI Postdoctoral Researchers Amir Feder and Ann Iturra Mena

Talk Information

Algorithmic Recommendations Have Limited Effects on Polarization: A Naturalistic Experiment on YouTube

Abstract: An enormous body of academic and journalistic work argues that opaque recommendation algorithms contribute to political polarization by promoting increasingly extreme content. We present evidence that challenges this dominant view, drawing on three large-scale, multi-wave experiments with a combined 7,851 human users. We show that even large (short-term) perturbations of real-world recommendation systems that substantially modify consumption patterns have limited causal effects on policy attitudes. Our methodology, which captures and modifies the output of real-world recommendation algorithms, offers a path forward for future investigations of black-box artificial intelligence systems. However, our findings also reveal practical limits to effect sizes that are feasibly detectable in academic experiments. We will also talk more generally about the challenges of studying societal-scale black box systems.  Based on joint work with Naijia Liu, Matthew Baum, Adam Berinsky, Allison Chaney, Justin de Benedictis-Kessner, Andy Guess, Dean Knox, Christopher Lucas, and Rachel Mariman.

Bio: Brandon Stewart is an Associate Professor in the Department of Sociology and is also affiliated with the Department of Politics and the Office of Population Research.  He develops new quantitative statistical methods for applications across the social sciences.  Methodologically his focus is in tools which facilitate automated text analysis and model complex heterogeneity in regression.  Many recent applications of these methods have centered on using large corpora of text to better understand propaganda in contemporary China.  His research has been published in journals such as American Journal of Political Science, Political Analysis and the Proceedings of the Association of Computational Linguistics.  His work has won the Edward R Chase Dissertation Prize, the Gosnell Prize for Excellence in Political Methodology, and the Political Analysis Editor’s Choice Award. Learn More.