Source: Mondaq

This legal update on Mondaq, provided by the law firm Neal, Gerber & Eisenberg LLP, analyzes how recent court rulings in the United States are beginning to shape a new understanding of the "fair use" doctrine in the context of artificial intelligence. The central legal question addressed is whether scraping vast amounts of copyrighted material from the internet to train generative AI models constitutes copyright infringement or is permissible as a fair use. The article dissects the four factors of the fair use test, explaining how judges are applying this traditional legal framework to the novel challenges presented by AI technology, with a particular focus on the "transformative use" argument.

AI developers typically argue that using copyrighted works for training is transformative because the purpose is not to replicate the original content but to enable a new system to learn patterns and create entirely new outputs. However, recent judicial opinions have shown a more nuanced and sometimes skeptical view. Courts are increasingly scrutinizing whether the AI's output serves as a direct market substitute for the original copyrighted works. The article suggests that these initial rulings are signaling a shift towards a more critical evaluation of transformative use claims, potentially creating significant legal hurdles for AI companies that rely on unlicensed data for training their models. The outcomes of these cases are establishing critical precedents for the future of both AI development and copyright law.