Landmark Rulings on Fair Use in AI Copyright Cases
Recent court decisions highlight the evolving landscape of copyright law as AI companies face lawsuits from authors, with significant implications for the industry.
Overview
- Two recent U.S. court rulings address fair use in generative AI, impacting ongoing copyright infringement lawsuits against AI companies.
- Anthropic's ruling allows it to continue AI development, while facing trial over allegations of downloading millions of pirated books.
- Another ruling allows a piracy complaint against an AI company to proceed to trial, emphasizing the tension between innovation and copyright laws.
- The legal outcomes could redefine the relationship between AI technology and copyright, as creators continue to challenge fair use claims.
- The cases reflect broader concerns about how copyright laws adapt to advancements in AI and the implications for creators and developers alike.
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Analysis
Center-leaning sources frame the ruling as a pivotal moment in copyright law, highlighting the tension between AI innovation and creator rights. They express concern over the implications for authors, emphasizing the legal complexities of fair use while acknowledging the potential for AI companies to exploit copyrighted materials.
This ruling is the first to address fair use in generative AI systems and is the first time a judge has ruled in favor of an AI company on fair use.
The judge allowed the authors' piracy complaint to proceed to trial, but has not yet ruled on their claim that Meta unlawfully distributed their works during a torrenting process.
The Authors' Guild disagreed with the ruling that using pirated or scanned books for training large language models is fair use, stating that while acquisition and digitization of print books was fair use, creating a permanent library was not.
Anthropic is being tried for illegally downloading over 7 million pirated books.
The judge ruled that the company's training of AI models on copyrighted books was considered 'fair use' under U.S. copyright law.
Judge Chhabria ruled that training an AI model on copyrighted works without permission is not always legal, despite a recent decision in San Francisco.
Anthropic faces a separate trial in December for downloading and storing millions of pirated books, which could determine their liability and potential damages.
Judge Alsup ruled in favor of three authors who sued Anthropic for copyright infringement.
Anthropic is facing trial for obtaining books from online 'shadow libraries' of pirated copies.
Alsup ruled that while training AI models with copyrighted data may be fair use, Anthropic will still face trial for storing pirated books in a searchable repository.
AI companies may have the legal right to train their large language models on copyrighted works if they obtain copies legally, but they are facing multiple copyright lawsuits from writers, news outlets, and other copyright owners for doing so.
Articles (14)
Center (10)
"…The judge painted a picture of the future where AI firms will have to license content from authors, artists and other creators."
Deadline·6d·"…The ruling is significant because it represents the first substantive decision on how fair use applies to generative AI systems."
NPR·6d·"…The decision comes just a few days after a federal judge sided with Anthropic in a similar lawsuit."
TechCrunch·6d·"…Anthropic's use of legally purchased books to train its AI model, Claude, did not violate U.S. copyright law."
CBS News·7d·"…A federal judge has ruled that AI company Anthropic didn’t break the law by training its chatbot Claude on millions of copyrighted books."
Fortune·7d·"…Judge William Alsup’s ruling marks the first of dozens of ongoing copyright lawsuits to give an answer on fair use in the context of generative AI."
NBC News·7d·"…The first-of-its-kind ruling that condones AI training as fair use will likely be viewed as a big win for AI companies, but it also notably put on notice all the AI companies that expect the same reasoning will apply to training on pirated copies of books—a question that remains unsettled."
ARS Technica·7d·"…The ruling is a significant win for generative AI companies and a blow for creators."
CNET·7d·"…The ruling could set a precedent for similar lawsuits that have piled up against Anthropic competitor OpenAI, maker of ChatGPT, as well as against Meta Platforms, the parent company of Facebook and Instagram."
Associated Press·7d·"…Alsup’s ruling may set a precedent for these other copyright cases—although it is also likely that many of these rulings will be appealed, meaning it will take years until there is clarity around AI and copyright in the U.S."
Fortune·7d·FAQ
The judge ruled that Anthropic's use of legally purchased books to train its AI model was 'quintessentially transformative' and did not violate the fair use doctrine because the AI did not replicate or supplant the works but created something different through learning from those works.
Anthropic is facing a separate trial because it downloaded millions of pirated books from the internet to build a digital library for AI training, which the judge found could constitute copyright infringement and is not protected under fair use.
These rulings set important precedents that training AI models on legally acquired copyrighted works may qualify as fair use, but using pirated materials does not, thereby influencing how AI companies approach data sourcing and shaping the evolving legal landscape of copyright in AI development.
The lawsuit was filed by authors Andrea Bartz, Charles Graeber, and Kirk Wallace Johnson, who alleged that Anthropic used their copyrighted works without permission to train its AI systems, challenging the use of their works as inputs for training but not alleging that the AI outputs reproduced their works.
The cases raise key questions about how copyright laws adapt to AI advancements, specifically whether training generative AI on copyrighted data without permission is lawful under fair use, and how liability is determined when pirated content is involved in AI training datasets.
History
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