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Artificial intelligence and copyright
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<p> In the 2020s, the <a href="/facts/AI_boom/wAPVI1SN">rapid advancement</a> of <a href="/facts/Deep_learning/JLuwD3ea">deep learning</a>-based <a href="/facts/Generative_artificial_intelligence/ykT3GGyT">generative artificial intelligence</a> models raised questions about whether <a href="/facts/Copyright_infringement/33JDsS5S">copyright infringement</a> occurs when such are trained or used. This includes <a href="/facts/Text-to-image_model/ez6APLzp">text-to-image models</a> such as <a href="/facts/Stable_Diffusion/BaXu5Vc8">Stable Diffusion</a> and <a href="/facts/Large_language_model/WnogWVJY">large language models</a> such as <a href="/facts/ChatGPT/ptB1y6J5">ChatGPT</a>. As of 2023, there were several pending U.S. lawsuits challenging the use of copyrighted data to train AI models, with defendants arguing that this falls under <a href="/facts/Fair_use/mlSlfPcB">fair use</a>.</p> <p>Popular deep learning models are trained on mass amounts of media <a href="/facts/Web_scraping/5R4mf1bd">scraped</a> from the Internet, often utilizing copyrighted material. When assembling training data, the sourcing of copyrighted works may infringe on the <a href="/facts/Copyright_holder/7GHEWEx9">copyright holder</a>'s exclusive right to control reproduction, unless covered by exceptions in relevant copyright laws. Additionally, using a model's outputs might violate copyright, and the model creator could be accused of <a href="/facts/Vicarious_liability/ounSBWCs">vicarious liability</a> and held responsible for that copyright infringement. </p>