AI image generators trained on 5 billion scraped photographer images face lawsuits but no injunctions, leaving photographers in legal limbo where their work trains competitors but courts move too slowly to provide relief

Professional photographers and visual artists discovered that AI image generators including Midjourney, Stable Diffusion, and DALL-E were trained on datasets like LAION-5B containing 5 billion images scraped from the internet, with 47% of the LAION-Aesthetics subset coming from stock photo sites like Shutterstock, Getty Images, and Flickr. Getty Images identified over 15,000 of its own photos in the Stable Diffusion training dataset. Why it matters: photographers' copyrighted work is used without consent or compensation to train AI systems, so those AI systems generate competing images at zero marginal cost, so commercial buyers switch from licensing stock photos to generating AI images, so photographer licensing revenue declines (Getty Creative revenue fell 4.5% in 2024), so photographers cannot afford to continue producing the high-quality original work that AI systems depend on for future training data. The structural root cause is that copyright law was designed for discrete acts of copying and distribution, not for statistical pattern extraction across billions of works, so courts must adjudicate novel legal theories (is training 'fair use'?) through multi-year litigation while AI companies continue operating, and the leaked Midjourney spreadsheet of 16,000 non-consenting artists demonstrates that the industry treats photographer consent as an obstacle to route around rather than a right to respect.