'Soon, it's going to get to the point where there is no way that we can actually detect [deepfakes] anymore, so we have to look at other types of solutions,' says Hao Li.
"It's still very easy, you can tell from the naked eye most of the deepfakes," Li, an associate professor of computer science at the University of Southern California, said on ""But there also are examples that are really, really convincing," Li said, adding those require "sufficient effort" to create.
The rise of this technology has, however, given rise to concerns about how these creations could cause confusion and propagate disinformation, especially in the context of global politics. Online disinformation through targeted social-media campaigns and apps such as WhatsApp hasLi's appearance on CNBC follows an appearance earlier this week at a Massachusetts Institute of Technology conference, at which he said he thought perfect deepfakes would arrive in "two to three years.
"Also, in some ways we already know how to do it," Li wrote in an email, adding that it is "only a matter of training with more data and implementing it."
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