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Reading: Federal Court Rules Copyrighted Books Are Fair Use for AI Training, But Trial to Proceed Over Use of Pirated Versions
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Home » Federal Court Rules Copyrighted Books Are Fair Use for AI Training, But Trial to Proceed Over Use of Pirated Versions

Technology

Federal Court Rules Copyrighted Books Are Fair Use for AI Training, But Trial to Proceed Over Use of Pirated Versions

Eura Tymal
Eura Tymal
June 25, 2025
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The federal court made an important ruling this week, deciding that the use of copyrighted books for artificial intelligence (AI) training can be considered fair use. The decision relates to the case involving Anthropic, an AI company that used protected works without the consent of the authors or publishers to train its chatbot Claude. Although the court recognized fair use as valid, it ordered the company to face trial regarding the alleged use of pirated versions of these books, which constitutes copyright infringement.

The issue of copyrighted books and their use in AI training has been one of the most controversial topics in the technology market. The federal court emphasized that the application of fair use is a significant step for the AI industry, as it allows companies to innovate by utilizing existing content without violating intellectual property laws. However, the decision also highlights the limits of this use, especially when there are indications of pirated materials involved.

According to the court, the concept of fair use authorizes limited utilization of protected works for specific purposes, such as research and development, which includes training AI systems. The ruling in Anthropic’s case reaffirms that using copyrighted books to improve algorithms does not necessarily infringe copyrights. However, the case will be further examined to assess whether illegal versions of the books were used, which could undermine the fair use defense.

The impact of the federal court’s ruling on fair use of copyrighted books for AI training could be widespread and influence other companies working with artificial intelligence. The industry is closely watching the developments, as the decision helps set legal boundaries for collecting and using protected data. Furthermore, the ruling contributes to the debate on protecting authors’ rights amid technological advances and new forms of creation.

Nonetheless, controversy remains regarding the extent to which AI training can be considered creation or mere copying of protected content. Many critics argue that the practice represents an improper appropriation of authors’ rights, as systems learn and reproduce information without compensating the original creators. The federal court’s decision opens the door for broader dialogue about copyright in the digital era and the necessary balance between innovation and legal protection.

Beyond legal aspects, the case involving copyrighted books and their use for AI training raises ethical and commercial questions. Publishers and authors express concerns about the value of their works, while technology companies seek to ensure the advancement and competitiveness of their products. By permitting fair use, the federal court creates a precedent that could accelerate AI development but also demands caution to prevent abuse.

The federal court’s ruling requires Anthropic to face a specific trial to investigate whether pirated versions of copyrighted books were used. This process will be crucial to establish clearer limits on what is acceptable under fair use. The outcome may influence future court decisions and government regulations, as well as guide business practices in the AI and copyright sectors.

Finally, the federal court’s decision on copyrighted books and fair use for AI training marks a milestone for the technology and legal sectors. Balancing innovation with respect for creators’ rights is essential for sustainable AI development. The Anthropic case highlights the complexity of the issue and the need for a thorough debate to adapt rules to the digital and technological realities of the 21st century.

Author: Eura Tymal

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