4/4/24 | 4:15pm | E51-376

Yiling Chen

Gordon McKay Professor of Computer Science
Harvard

Abstract: When information is generated, collected and spread by people, ensuring the integrity of information is critical for downstream use of the information. In this talk I will discuss two of our efforts in improving information integrity through intentional design. I will mainly focus on the first effort where we propose using information design as a tool for social media platforms to combat the spread of misinformation. As platforms can predict the popularity and misinformation states of to-be-shared posts, and users are motivated to only share popular content, platforms can strategically reveal this informational advantage to persuade users to not share misinformed content. We characterize the platform’s optimal information design scheme and resulting utility when platform has access to an imperfect classifier for predicting post states. I will then discuss a second and ongoing effort on designing reliability tests for data collected from strategic agents when there is not direct ground truth to evaluate the integrity of data. We show that if we can observe some other reliable data and have a little knowledge about the relationship between agents’ private data and our observed data, then it’s possible to design a reliability test such that agents will pass the test with probability one only when they truthfully report their private data. 

The talk is based on joint works, one with Safwan Hossain, Andjela Mladenovic, and Gauthier Gidel, and the other with Shi Feng, Fang-Yi Yu, and Paul Kattuman. 

Bio: Yiling Chen is a Gordon McKay Professor of Computer Science at Harvard University. She received her Ph.D. in Information Sciences and Technology from the Pennsylvania State University. Prior to working at Harvard, she spent two years at Yahoo! Research in New York City. Her research lies in the intersection of computer science, economics and other social sciences,  with a focus on social aspects of computational systems. She was a recipient of The Penn State Alumni Association Early Career Award, and was selected by IEEE Intelligent Systems as one of "AI's 10 to Watch” early in her career. Her work received best paper awards at ACM EC, AAMAS, ACM FAT* (now ACM FAccT) and ACM CSCW conferences. She was a program co-chair for the 2013 Conference on Web and Internet Economics (WINE’13), the 2016 ACM Conference on Economics and Computation (EC’16), the 2018 AAAI Conference on Human Computation and Crowdsourcing (HCOMP’18) and the 2023 AAAI Conference on Artificial Intelligence (AAAI-23), and has served as an associate editor for several journals.