Artificial intelligence doesn’t create in a vacuum. Rather, it depends on human work to analyze data, discovering patterns and finding anomalies. That work is essential for AI’s machine learning. Therefore, categorizing such work as “fair use” misses the point.
As artificial intelligence rapidly advances, a fundamental question is emerging: What happens to creators’ rights — journalists, artists, statisticians — when their work becomes essential fuel for AI systems?
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The original purpose of copyright is, simply, a matter of control. Copyright law ensures creators, not downstream users, capture the value of their work — an idea that becomes even more critical when that work is used at scale. These creators — authors, artists, and innovators — have the right to determine how their work is used, distributed, and monetized. That principle does not disappear simply because content is ingested into an AI model. These systems rely on vast amounts of existing writing, art, and code created by humans. If that material is necessary for the system to function, then the rights of those creators should remain firmly in place.
As AI accelerates, the demand for legal clarity is outpacing the development of case law, creating a kind of digital Wild West where the rules haven’t caught up to reality. Any claim that AI training qualifies as “fair use” misunderstands what is actually happening. Training a model is an active process of using copyrighted material to build a new product. Without that material, the system would not exist in its current form.
Allowing companies to use protected works in this way permits them to absorb, repurpose, and possibly monetize creative output without consent or compensation. Luckily, the courts are beginning to recognize and weigh in on this distinction.
In Thomson Reuters v. ROSS Intelligence, a federal judge ruled that using copyrighted material to train an AI system can be infringement, rejecting a fair use defense. The case involved Thomson Reuters, the company behind Westlaw — a widely used legal research platform for lawyers — which creates its own summaries of court decisions, known as “headnotes.” ROSS, a startup building an AI legal research tool, used those summaries to train its system. Plainly, you cannot use protected material to build a competing product without permission.
This issue is now playing out on a larger scale in The New York Times v. OpenAI and Microsoft, where it is alleged that journalism was used without authorization to train AI systems. The case underscores the stakes — whether or not entire bodies of creative and intellectual work can be absorbed into AI without recourse for their creators.
Some argue that requiring permission or compensation will slow innovation. But copyright law has always coexisted with technological progress. It provides a framework for licensing and responsible use, ensuring that innovation does not come at the expense of creators’ rights. AI should be no exception.
Importantly, copyright law does not need to be anti-AI. Rather, it must remain pro-creator. Human-made works must stay eligible for protection, even when AI is used as a tool in the creative process. But fully machine-generated content does not carry the same protections. This distinction reinforces the value of human creativity while still allowing room for innovation.
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The real issue is not whether AI can develop, but how. If companies rely on copyrighted material to train their systems, they should obtain permission and, if applicable, provide compensation. The burden should not fall on creators to accept that their work is simply raw material for someone else’s product.
AI companies face a choice: They can either build systems that respect the legal and economic value of creative work, or they can continue to operate in a gray area that undermines it. Copyright law will evolve, as it always has, but its foundation should remain clear: If creative work powers a system, that creator does not lose his or her protections.
Angelina Myers is a student media fellow at the Network of enlightened Women. She studies political science and government at George Washington University.
