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TITLE:

Photo Forensics: from Photoshop to Deepfakes

ABSTRACT:

Generative AI—so-called deepfakes—have captured the imagination of some and struck fear in others. Although they vary in their form and creation, deepfakes refer to text, image, audio, or video that has been automatically synthesized by a machine-learning system. Deepfakes are the latest in a long line of techniques used to manipulate reality, yet their introduction poses new opportunities and risks due to the democratized access to what would have historically been the purview of Hollywood-style studios. I will discuss the decades long trajectory of technologies used to distort reality, how these latest AI powered technologies work, how deepfakes are being used and misused, and if (and how) they can be distinguished from reality.

BIO:

I am a Professor at the University of California, Berkeley with a joint appointment in Electrical Engineering & Computer Sciences and the School of Information. I am also the co-founder and Chief Science Officer at GetReal Security. 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 ´óÏ㽶ÊÓƵ 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.