Date
The film "Coded Bias" explores the fallout from an MIT Media Lab researcher’s discovery that facial recognition does not identify dark-skinned faces and women's faces accurately. The film follows her journey to push for the first legislation in the U.S. to govern against bias in the algorithms.
This recording is of a U-M Dissonance Event Series panel of U-M experts "At the Movies" style discussion of the film that took place on Thursday, April 15, 2021, over Zoom. The panelists exchanged views on the challenges presented by technologies that reflect the systemic biases in American society.
Speakers
Assistant Professor of Information, School of Information, and Assistant Professor of Digital Studies Institute, College of Literature, Science, and the Arts
Dr. Andalibi is an Assistant Professor at the University of Michigan School of Information. She is also affiliated with the Center for Social Media Responsibility (CSMR), the Center for Ethics, Society, and Computing (ESC), and the Digital Studies Institute. She is a co-director of the Social Media Research Lab. Her research interests are in social computing, computer-mediated communication, and human-computer interaction, including examining relationships between emotions, identity, and technologies in contexts ranging from social media to artificial intelligence.
Peter and Evelyn Fuss Chair of Electrical and Computer Engineering, Department of Electrical Engineering and Computer Science
Mingyan Liu's research interests are in optimal resource allocation, sequential decision theory, incentive design, and performance modeling and analysis, all within the context of communication networks. Dr. Liu’s most recent research activities involve online learning, modeling and mining of large scale Internet measurement data, and the design of incentive mechanisms for cybersecurity. She received an MS in Systems Engineering (1997) and a PhD in Electrical Engineering (2000) from the University of Maryland, College Park.
Dr. Liu was a recipient of the 2002 NSF CAREER Award, the University of Michigan Elizabeth C. Crosby Research Award in 2003 and 2014, the 2010 EECS Department Outstanding Achievement Award, the 2015 College of Engineering Excellence in Education Award, and the 2017 College of Engineering Excellence in Service Award. She received a number of Best Paper Awards, including one at the IEEE/ACM International Conference on Information Processing in Sensor Networks (IPSN) in 2012 and one at the IEEE/ACM International Conference on Data Science and Advanced Analytics (DSAA) in 2014. She has served on the editorial boards of IEEE/ACM Trans. Networking, IEEE Trans. Mobile Computing, and ACM Trans. Sensor Networks and is a Fellow of the IEEE and a member of the ACM.
Professor of Law, U-M Law School
Nicholson Price teaches and writes in the areas of intellectual property, health law, and regulation, particularly focusing on the law surrounding innovation in the life sciences. He previously was an assistant professor of law at the University of New Hampshire School of Law, an academic fellow at the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School, and a visiting scholar at the University of California, Hastings College of the Law. He clerked for the Hon. Carlos T. Bea of the U.S. Court of Appeals for the Ninth Circuit. He received a JD and a PhD in biological sciences from Columbia University and an AB in biological sciences from Harvard College.
Ethics, Legal, and Social Implications (ELSI) postdoctoral fellow, School of Public Health
Grace Trinidad holds a PhD in Health Infrastructures and Learning Systems from the University of Michigan, where she conducted research on privacy and trust and on public attitudes towards sharing health data with third-party commercial companies. Prior to earning her PhD, she earned a Master of Science in Design and Health from the Taubman College of Architecture and Urban Planning and a Master of Public Health from the University of Michigan School of Public Health.