2024考研英语一 · 阅读理解 Text 3

A Polish digital artist who uses classical painting styles to create dreamy fantasy landscapes, Greg Rutkowski has made illustrations for games such as Dungeons & Dragons and Magic: The Gathering. And he’s become a sudden hit in the new world of text-to-image AI generation.

His distinctive style is now one of the most commonly used prompts in the new open-source AI art generator Stable Diffusion. The tool, along with other popular image-generation AI models, allows anyone to create impressive images based on text prompts. For example, type in “Wizard with sword and a glowing orb of magic fire fights a fierce dragon Greg Rutkowski,” and the system will produce something that looks not a million miles away from works in Rutkowski’s style.

But these open-source programs are built by scraping images from the internet, often without permission and proper attribution to artists. As a result, they are raising tricky questions about ethics and copyright. And artists like Rutkowski have had enough.

According to the website Lexica, which tracks over 10 million images and prompts generated by Stable Diffusion, Rutkowski’s name has been used as a prompt around 93,000 times. Rutkowski was initially surprised but thought it might be a good way to reach new audiences. Then he tried searching for his name to see if a piece he had worked on had been published. The online search brought back work that had his name attached to it but wasn’t his.

“It’s been just a month. What about in a year? I probably won’t be able to find my work out there because the internet will be flooded with AI art,” Rutkowski says. “That’s concerning.”

Other artists besides Rutkowski have been surprised by the apparent popularity of their work in text-to-image generators—and some are now fighting back. Karla Ortiz, an illustrator based in San Francisco who found her work in Stable Diffusion’s data set, has been raising awareness about the issues around AI art and copyright.

Artists say they risk losing income as people start using AI-generated images based on copyrighted material for commercial purposes. But it’s also a lot more personal, Ortiz says, arguing that because art is so closely linked to a person, it could raise data protection and privacy problems.

“There is a coalition growing within artist industries to figure out how to tackle or mitigate this,” says Ortiz. The group is in its early days of mobilization, which could involve pushing for new policies or regulation. One suggestion is that AI models could be trained on images in the public domain, and AI companies could forge partnerships with museums and artists, Ortiz says.