- Computational Social Science
- Critical Data Studies
- Data Science
- Economics and Information
- Education Technology
- Ethics, Law and Policy
- Human-Computer Interaction
- Human-Robot Interaction
- Incentives and Computation
- Infrastructure Studies
- Interface Design and Ubiquitous Computing
- Natural Language Processing
- Network Science
- Social Computing and Computer-supported Cooperative Work
- Technology and Equity
Baobao Zhang is a postdoctoral fellow in MIT’s Political Science Department, a research affiliate with the Center for the Governance of AI at the University of Oxford, and a fellow at the Berkman Klein Center for Internet and Society at Harvard University. Zhang's current research focuses on the governance of artificial intelligence (AI). In particular, she studies public and elite opinion toward AI and how the American welfare state could adapt to the increasing automation of labor.
Zhang's previous research covered a wide range of topics, including the politics of the U.S. welfare state, attitudes towards climate change, and survey methodology. Her papers have been published in Political Analysis, Nature Climate Change, the Journal of Artificial Intelligence Research, and JAMA Surgery. Her research and graduate education have been funded by the National Science Foundation Graduate Research Fellowship, the Ethics and Governance of Artificial Intelligence Fund, and the OECD.
Zhang graduated with a BA in political science (2013) and an MA in statistics (2015) from Yale University. During graduate school, she worked as a data scientist for the Yale Program for Climate Change Communication and a researcher to former Secretary of State John Kerry.
Talk: No Rage Against the Machines: Threat of Automation Does Not Change Policy Preferences
Abstract: Labor-saving technology has already decreased employment opportunities for middle-skill workers. Experts anticipate that advances in AI and robotics will cause even more significant disruptions in the labor market over the next two decades. This paper presents three experimental studies that investigate how this profound economic change could affect mass politics. Recent observational studies suggest that workers’ exposure to automation risk predicts their support not only for redistribution but also for right-wing populist policies and candidates. Other observational studies, including my own, find that workers underestimate the impact of automation on their job security. Misdirected blame towards immigrants and workers in foreign countries, rather than concerns about workplace automation, could be driving support for right-wing populism. To correct American workers’ beliefs about the threats to their jobs, I conducted three survey experiments in which I informed workers about the existent and future impact of workplace automation. While these informational treatments convinced workers that automation threatens American jobs, they failed to change respondents’ preferences on welfare, immigration, and trade policies. My research finds that raising awareness about workplace automation did not decrease opposition to globalization or increase support for policies that will prepare workers for future technological disruptions.