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How do proprietary algorithms on online job platforms affect job recommendations for workers? In this seminar, Professor Shuo Zhang will explore this question based on her resume audit study conducted on four Chinese job boards. Using fictitious profiles that differ only in age and gender, the research reveals that, while there is significant overlap in recommended jobs, these systems also present distinct recommendations based on gender. This work provides an initial insight into potential gender biases within job recommendation algorithms. 

Shuo Zhang is an Assistant Professor of Economics and Computer Science in the Department of Economics and Khoury College of Computer Sciences in Northeastern University. Her research interest is in labor economics, platform design and algorithmic fairness. She mainly works on the empirics of job search and matching in online labor markets, including workers’ job search behaviors, employers’ recruitment decisions, and the role of internet job platforms in online job matching.

This seminar series will give participants an opportunity to engage with research that relates to the topics discussed in the book Make Work Fair. This virtual seminar is part of the Women and Public Policy Program's weekly spring seminar series: Make Work Fair. Attendance is open to all.