Britain Getty Images AI Copyright

FILE - The desktop and mobile websites for Stable Diffusion are pictured, Oct. 24, 2023, in New York.

LONDON (AP) — Getty Images is facing off against artificial intelligence company Stability AI in a London courtroom for the first major copyright trial of the generative AI industry.

Opening arguments before a judge at the British High Court are scheduled for Monday. The trial could last for three weeks.

Stability, based in London, owns a widely used AI image-making tool that sparked enthusiasm for the instant creation of AI artwork and photorealistic images upon its release in August 2022. OpenAI introduced its surprise hit chatbot ChatGPT three months later.

Seattle-based Getty has argued that the development of the AI image maker, called Stable Diffusion, involved “brazen infringement” of Getty’s photography collection “on a staggering scale."

Tech companies have long argued that “fair use” or “fair dealing” legal doctrines in the United States and United Kingdom allow them to train their AI systems on large troves of writings or images. Getty was among the first to challenge those practices when it filed copyright infringement lawsuits in the United States and the United Kingdom in early 2023.

“What Stability did was inappropriate,” Getty CEO Craig Peters told The Associated Press in 2023. He said creators of intellectual property should be asked for permission before their works are fed into AI systems rather than having to participate in an “opt-out regime."

Stability has argued that the case doesn't belong in the United Kingdom because the training of the AI model technically happened elsewhere, on computers run by U.S. tech giant Amazon.

Similar cases in the U.S. have not yet gone to trial.

Stable Diffusion’s roots trace to Germany, where computer scientists at Ludwig Maximilian University of Munich worked with the New York-based tech company Runway to develop the original algorithms. The university researchers credited Stability AI for providing the servers that trained the models, which require large amounts of computing power.

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