UC Berkeley researchers develop technique for detecting AI video simulations
By Sasha Langholz
UC Berkeley graduate student Shruti Agarwal and her thesis adviser Hany Farid, an incoming professor in the campus department of electrical engineering and computer sciences and in the School of Information, are developing a new approach to detect deepfakes — artificial intelligence simulations that can portray convincing videos of individuals saying things they never said...
Agarwal and Farid’s technique is estimated to be 92-96 percent accurate based on the team’s tests. However, the technique is less accurate when politicians are speaking outside of rehearsed speeches, when their facial quirks are less identifiable.
“Imagine a world now, where not just the news that you read may or may not be real — that’s the world we’ve been living in for the last two years, since the 2016 elections — but where the images and the videos that you see may or may not be real,” Farid said in the article...
Hany Farid is a professor in the UC Berkeley School of Information and EECS. He specializes in digital forensics.
