Dallas Card is an Assistant Professor in the School of Information at the University of Michigan, where his research focuses on making machine learning more reliable and responsible, and on using machine learning and natural language processing to learn about society from text. His work received a best short paper nomination at ACL 2019, a distinguished paper award at FAccT 2022, and has been covered by The Washington Post, Vox, Wired, and other outlets. Prior to starting at Michigan, Dallas was a postdoctoral researcher with the Stanford Natural Language Processing Group and the Stanford Data Science Institute. He holds a Ph.D. in Machine Learning from Carnegie Mellon University.