Why U.S. Copyright Law Supports AI Innovation
As debates over copyright and AI heat up, misconceptions
about how models learn and what the law protects are driving
confusion. Narrow interpretations of existing U.S.
copyright law risk stalling innovation, slowing progress, and
weakening America’s global AI leadership.
As debates over copyright and AI heat up, misconceptions about how models learn and what the law protects are driving confusion. Narrow views of copyright risk stalling innovation, slowing progress, and weakening America’s global AI leadership.
4 Key Takeaways from the Report
Generative AI — especially large language models (LLMs) — are trained on massive datasets, learning to generate accurate, relevant responses based on statistical relationships and patterns between words and ideas. These four takeaways clarify the facts — and highlight what’s at stake for innovation, the law, and the future of AI.
AI models generate
new works based on patterns
AI models learn by breaking down text and other data into smaller parts. They can’t store, retrieve, or reproduce the original materials they’ve been trained on.
Law protects expression,
not ideas or competition
U.S. copyright law protects creative expression, not underlying ideas, facts, or patterns. Similarly, the law doesn’t protect against new competition — only against copying existing expression.
Courts back using
copyrighted materials in AI training
Courts have found that transformative uses — including AI training on whole books or datasets — are lawful when they serve a new purpose and don’t compete with the original works.
Restricting AI training
threatens American innovation
Limiting access to training data would undermine the development of AI technologies and run counter to the goals of copyright, which seeks to promote creativity and progress.
