Communications of the ACM
AI Tech Enables Industrial-Scale Intellectual-Property Theft, Say Critics
This is the basic mechanics of all so-called generative AI—first, a company finds or creates a big-enough set of data, then uses various algorithms to train software to spit out specific text, images, or code based on that data.
Credit: Jarred Briggs
Grzegorz Rutkowski has studied the great masters of texture and light—Caravaggio, Rembrandt, Vermeer—and his ability to mimic their techniques has made him an in-demand painter of fantastical beasts and landscapes for the videogame industry.
But these days, instead of devoting all his time to painting in his sun-dappled studio near the picturesque medieval square in the town of Pieńsk, Poland, he's spending ever more of it on Zoom calls, talking to lawyers, artists and others about the strange reason he is suddenly far more famous than he ever thought possible.
It turns out that Mr. Rutkowski's distinctive style and choice of subject matter have made him among the most popular artists to copy using the kind of image-generating artificial-intelligence systems that have exploded in popularity in the past year. The two most prominent of these systems are Dall-E 2, made by San Francisco-based startup OpenAI, and Stable Diffusion, created by Stability AI, though there are an ever-growing number of competitors.
The result is that images made by AI in Mr. Rutkowski's style are suddenly all over forums on the internet where users share works they have generated from text prompts. Mr. Rutkowski's name has become such a popular prompt in such AI art generators that he recently decided to join a federal lawsuit seeking class-action status against several of the companies involved.
From The Wall Street Journal
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