Talk Abstract: Generative AI – so-called deepfakes – have captured the imagination of some and struck fear in others. These stunningly realistic images, audio, and videos are the product of AI-powered synthesis tools. Although just the latest in a long line of techniques used to manipulate reality, deepfakes pose new opportunities and risks due to their ease of use and their democratized accessibility. I will describe how deepfakes are created, how they are being used and misused, and if and how they can be perceptually and computationally distinguished from reality.

Speaker Biography: I am a Professor at the University of California, Berkeley with a joint appointment in Electrical Engineering & Computer Sciences and the School of Information. My research focuses on digital forensics, forensic science, misinformation, image analysis, and human perception. I received my undergraduate degree in Computer Science and Applied Mathematics from the University of Rochester in 1989, and my Ph.D. in Computer Science from the University of Pennsylvania in 1997. Following a two-year post-doctoral fellowship in Brain and Cognitive Sciences at MIT, I joined the faculty at Dartmouth College in 1999 where I remained until 2019. I am the recipient of an Alfred P. Sloan Fellowship, a John Simon Guggenheim Fellowship, and am a Fellow of the National Academy of Inventors.