The program is still in development, but the team intends to integrate it with its existing artist protection tools.
Researchers at the University of Chicago have created a tool that allows artists to “poison” their digital art in order to prevent developers from training AI systems on their work.
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The technology, dubbed “Nightshade” after the plant family notorious for its deadly berries, changes photos in such a way that their inclusion contaminates the datasets used to train AI with false information.
Nightshade, according to MIT’s Technology Review, alters the pixels of a digital image in order to fool an AI system into misinterpreting it. As an example, Tech Review mentions convincing AI that an image of a cat is actually an image of a dog, and vice versa.
The AI’s capacity to create accurate and sensitive outputs would theoretically be harmed as a result. In the preceding scenario, if a user requested an image of a “cat” from the poisoned AI, they might instead receive a dog labeled as a cat or an amalgamation of all the “cats” in the AI’s training set, including those that are actually photographs of dogs edited by the Nightshade tool.
According to Vitaly Shmatikov, a professor at Cornell University, who reviewed the paper, researchers “don’t yet know of robust defenses against these attacks.” The result is that even robust models like OpenAI’s ChatGPT may be vulnerable.
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Professor Ben Zhao of the University of Chicago leads the Nightshade research team. The new technology is basically an enhancement of Glaze, their existing artist protection program. They previously created a mechanism for an artist to conceal, or “glaze,” the style of their artwork.
A charcoal portrait, for example, may be coated to appear like modern art to an AI system.
According to Technology Review, Nightshade will eventually be integrated into Glaze, which is now free for web usage or download from the University of Chicago’s website.
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