I have spent much of my adult life writing. Fifteen books carry my name, along with more than a thousand articles and commentaries produced over four decades. I also believe America must defeat communist China in the race for artificial intelligence leadership.

This week, those two convictions moved uncomfortably close to collision.

The Justice Department filed an amicus brief supporting OpenAI in its copyright battle with The New York Times, arguing that AI training generally makes fair use of copyrighted material and stressing the stakes for scientific progress, economic growth, and national security. Commerce Secretary Howard Lutnick carried the same argument to the G20, urging governments to permit AI training on copyrighted works while still protecting creators.

Washington is right about the strategic stakes. America cannot surrender AI leadership to Beijing. But national security cannot become a magic phrase that dissolves property rights whenever somebody’s work is useful to a machine.

Still, calling all AI training theft would be too simple. The U.S. Copyright Office has concluded that some uses of copyrighted works for generative-AI training may qualify as fair use and others may not. The answer depends on the purpose of the use, how the material was obtained, what the model produces, and the effect on the market for the original work. The office warned that those market effects could occur on an “unprecedented scale.”

The choice is not copyright or AI. The question is where legitimate technological learning ends and uncompensated commercial appropriation begins.

For authors, that question is not theoretical. Anthropic agreed last year to pay $1.5 billion to settle a class action involving 500,000 pirated books, or about $3,000 per work. The company admitted no liability. Importantly, the underlying case distinguished between training AI on lawfully obtained books and acquiring books from pirate libraries. Piracy and fair use are not the same legal question.

We should not casually label all machine learning theft. But calling a work “training data” does not erase the human being who wrote, researched, edited, photographed, composed, or published it.

There is already a better model: pay for material that has value.

OpenAI has licensing agreements with publishers including the Financial Times and News Corp. Its News Corp arrangement gives OpenAI access to current and archived material from The Wall Street Journal, Barron’s, the New York Post, The Times of London, and other publications. Reuters reported that the deal could be worth more than $250 million over five years.

If professionally created content is valuable enough to support a quarter-billion-dollar licensing agreement, it is hard to argue that the same kind of human work suddenly has no compensable value when absorbed into an AI system.

Yet copyright is only the doorway into a much larger problem.

The International Labour Organization estimates that one in four workers worldwide holds a job with some degree of exposure to generative AI. The ILO expects most jobs to change rather than vanish, calling that the more common outcome. Still, its study of media and culture warns that AI is changing journalism, writing, music, film, and other creative work, affecting not only production but creative and decision-making processes.

For a writer, the concern is therefore no longer simply whether AI copied a book. It is whether AI learned from that book, and millions like it, to build a machine capable of doing some of the work for which writers were once paid.

The danger is not that human work disappears tomorrow. It is that more of the economic value produced by human skill gradually migrates to companies that own machines capable of reproducing portions of that skill. And that reaches far beyond authors.

Professional journalism could become less economically sustainable, leaving fewer reporters to investigate government, war, courts, corruption, and local institutions. What happens when illustrators, photographers, translators, editors, musicians, and other skilled creators are displaced by cheap synthetic substitutes? We may receive vastly more content while producing less genuinely human creation.

There is an irony here. AI depends on the accumulated knowledge and creativity of human beings. If the technology steadily weakens the economic incentives that produce the next generation of books, journalism, music, scholarship, and art, it could eventually impoverish the very intellectual environment from which it learns.

Our Constitution recognized that society has an interest in protecting intellectual work. Article I empowers Congress to secure authors and inventors exclusive rights for limited times “to promote the Progress of Science and useful Arts.” Copyright has never been merely a favor to famous writers or Hollywood studios. Its larger purpose is to encourage people to keep creating.

That incentive matters even more as AI becomes a gatekeeper for what we read and see. European regulators are already asking publishers whether Google’s AI-generated search summaries reduce web traffic and advertising revenue, and whether publishers have meaningful control over how their material is used.

Who captures the value as machines mediate more of what society reads, hears, learns, and eventually produces?

America must remain first in AI. China would gladly dominate frontier models, industrial robotics, autonomous weapons, science, intelligence, and the global AI ecosystem. We should not regulate American companies into strategic defeat.

We should reject that false choice. Preserving fair use, punishing piracy, and building licensing markets that compensate creators are not obstacles to keeping American AI ahead of Beijing; they are how national security and creative freedom can coexist, without treating America’s intellectual inheritance as a free natural resource for the world’s richest technology companies.

Scripture supplies a principle older than copyright law: “The laborer deserves his wages” (Luke 10:7, ESV). Luke was not writing copyright law. But the principle is unmistakable: human labor has moral significance, and paying the worker is not an obstacle to progress.

Technology can multiply the fruits of human creativity. It should not teach us to devalue the creator.

America should lead the world in artificial intelligence. But we should not build that leadership on the proposition that human creativity is valuable enough to train our machines while the people who produced it become economically expendable.

We may become richer in machine-generated output while becoming poorer in something much harder to measure: the dignity, purpose, independence, and judgment that grow from meaningful human work.