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Honors and Awards

Annie Liang Receives NSF CAREER Award

The award will support research at the intersection of economic theory and computer science

Annie LiangNorthwestern’s Annie Liang has received a Faculty Early Career Development Program (CAREER) award from the National Science Foundation (NSF), its most prestigious honor for junior faculty members.

Liang is an assistant professor of economics at Northwestern’s Weinberg College of Arts and Sciences and the Karr Family Assistant Professor of Computer Science at Northwestern Engineering.

The CAREER program supports the early-career development of academic role models dedicated to outstanding research, inspired teaching, enthusiastic learning, and disseminating new knowledge to a broad audience. The award is intended to build a firm foundation for a lifetime of contributions to research, education, and their integration.

Liang will receive $408,451.00 over five years from NSF’s Division of Social and Economic Sciences for her project titled “Information, Algorithms, and Learning.” The grant will fund projects at the intersection of economic theory and computer science, which explore the opportunities and the dangers presented by algorithmic approaches within economic settings. Liang will develop new economic models of algorithmic decision-making, and new methodologies for the interpretation of economic data.

“Machine learning algorithms are increasingly used to guide economic predictions and decisions.” Liang said. “We need to better understand how to deploy these algorithms in a thoughtful way, and what the broader social ramifications of these algorithms are.”

The project has three components, which Liang will pursue with different groups of coauthors. In the first project, Liang plans to characterize the welfare implications of algorithmic predictions, focusing on the tradeoffs between goals such as the accuracy versus the “fairness” of the algorithm. In the second, Liang will propose new methods for understanding how predictions made by ML algorithms that are opaque and uninformative about underlying economic forces — so-called black box methods — differ from those made by economic models. In particular, Liang will compare how well these methods generalize to new domains. Finally, Liang will model information flow on social media platforms when the social norms that govern acceptable expression are in flux, characterizing when and how expressed views systematically differ from the true distribution of opinions.

By developing new models, proving new theoretical results, and proposing new statistical measures, these project will advance the research frontier in economic theory. The work is fundamentally interdisciplinary in nature, building on ideas from the neighboring areas of computer science and statistics.

The CAREER project also includes an education component focused on developing curriculum for new courses at the intersection of economics and computer science.

“It’s extremely encouraging to learn that the NSF panel and reviewers are excited, as I am, about understanding the economic and social implications of machine learning,” Liang said. “I look forward to continuing to explore problems in this area.”

Prior to joining Northwestern in 2021, Liang was an assistant professor of economics at the University of Pennsylvania, and a postdoctoral researcher at Microsoft Research-New England. She earned a PhD in economics from Harvard University in 2016.