From pixels to prompts: Visual misinformation in the age of generative AI
Wednesday, March 11, 2026
6 p.m. – 7 p.m. PT
USC Annenberg School for Communication and Journalism (ASC), ASC 207
As online environments become saturated with a complex mix of text, visual, audio, and synthetic media, understanding how these multimodal signals reshape communication has never been more urgent. In this talk, I explore the evolving anatomy of visual misinformation and the credibility gap—the widening space between the technical sophistication of generative AI and the human cognitive capacity to discern truth. I will report findings from several studies examining how people perceive visual misinformation, potential mitigation strategies, and how we can navigate a digital landscape where the line between the authentic and the artificial is increasingly blurred.
Cuihua (Cindy) Shen is a professor of communication at the University of California, Davis and the co-founder of the Computational and Multimodal Communication (CMMC) Lab. She is a Fellow of the International Communication Association and the past chair of the Computational Methods Division of ICA. She is currently an Editor-in-Chief of Journal of Computer-Mediated Communication and was the founding associate editor of the journal Computational Communication Research. Her research focuses broadly on computational social science and multimodal (mis)information in AI-mediated environments. Her research has been funded by grants from the US National Science Foundation and Meta. She is a recipient of a Fulbright US Scholar Award and numerous top paper awards from ICA. She received her PhD from the Annenberg School for Communication, University of Southern California.
The Walt Fisher Lecture is held annually by USC Annenberg in honor of the late Professor Emeritus Walter R. Fisher.
A reception will be held prior to the lecture starting at 5 p.m. in the ASC Second Floor West Lobby.
This program is open to all eligible individuals. USC Annenberg operates all of its programs and activities consistent with the University’s Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.