AI-generated text and images dominate our social media feeds and the other websites we visit, sometimes without our knowledge, and they are often used to spread unreliable and misleading information. But what if text-generating models like ChatGPT could spot deepfake images?
A University at Buffalo-led research team has applied large language models LLMs, including OpenAIs ChatGPT and Googles Gemini, toward spotting deepfakes of human faces. Theirstudy, presented at the IEEE/CVF Conference on Computer Vision Pattern Recognition, found that LLMs performance lagged behind that of state-of-the-art deepfake detection algorithms, but their natural language processing may actually make them the more practical detection tool in the future.
What sets LLMs apart from existing detection methods is the ability to explain their findings in a way thats comprehensible to humans, like identifying an incorrect shadow or a mismatched pair of earrings, says the studys lead author, Siwei Lyu, PhD, SUNY Empire Innovation Professor in the Department of Computer Science and Engineering, within the UB School of Engineering and Applied Sciences. LLMs were not designed or trained for deepfake detection, but their semantic knowledge makes them well suited for it, so we expect to see more efforts toward this application.
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