Deepfake Detection Is One Corner of AI Tech That Isn’t Booming
Artificial intelligence is now so powerful it can trick people into believing an image of Pope Francis wearing a white puffy Balenciaga coat is real, but the digital tools to reliably identify faked images are struggling to keep up with the pace of content generation.
Just ask the researchers at Deakin University's School of Information Technology, outside of Melbourne. Their algorithm performed the best in identifying the altered images of celebrities in a set of so-called deepfakes last year, according to Stanford University's artificial intelligence Index 2023.
“It's a fairly good performance,” said Chang-Tsun Li, a professor at Deakin's Centre for Cyber Resilience and Trust who developed the algorithm, which proved correct 78% of the time. “But the technology is really still under development.” Li said the method needs to be further enhanced before it's ready for commercial use.
Deepfakes have been around, and prompting concern, for years. Former House Speaker Nancy Pelosi appeared to be slurring her words in a doctored video in 2019 that circulated widely on social media. Meta Platforms Inc. About a month later, Chief Executive Officer Mark Zuckerberg was seen in a video altered to make it seem like he'd said something he didn't, after Facebook earlier refused to take down the Pelosi video.
While the image of the Pope in the puffer was a relatively harmless manipulation, the potential to inflict serious damage from deepfakes, from election manipulation to sex acts, has grown as the technology advances. Last year, a fake video of Ukraine President Volodymyr Zelenskiy asking his soldiers to surrender to Russia, could have had serious repercussions.
Big tech companies as well as a wave of startups have poured tens of
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