Distillation: Genius or Theft?

 

n early 2026, OpenAI told a US congressional committee that China's DeepSeek had been "free-riding" on American AI. The technique it named was distillation: training a cheaper model on the outputs of a more powerful one to copy its abilities. Anthropic made a similar charge against several Chinese labs. Much of the Western press reached for the same word. Not innovation. Theft.

Hold that word, because there's an awkward fact sitting right next to it. Those same American labs built their models by scraping the open internet, and with it the copyrighted archives of newspapers, the work of authors and artists, and proprietary text none of them paid for. The New York Times is suing. Hundreds of other publishers are too. OpenAI's defense is "fair use," the legal phrase for we built something new on top of what already existed.

So the principle gets slippery fast. When a Chinese lab learns from an American model, it's theft. When an American lab learns from everyone's writing without asking, it's fair use. Both can't be a clean rule. One of them is just a function of who's holding the lead.

I'll argue something uncomfortable: distillation is not a Chinese trick. It's how innovation has always worked. And whether we call it genius or theft usually depends on which side of the wall we're standing on.

What distillation actually is

Strip away the menace and distillation is closer to apprenticeship than to burglary. The student model never receives the teacher's weights or its training data. It watches the teacher's outputs and learns to generalize from them. If a young engineer studied a master's work, absorbed the patterns, and went on to do similar work more cheaply, we wouldn't call it theft. We'd call it education. When software does the same thing, we suddenly reach for a darker word.

It's also worth noting that many of the Chinese "distilled" models are built on openly released foundations like Llama and Qwen, which were put into the world precisely to be built on. The genuine dispute isn't whether learning-from-outputs happened. It's whose outputs, and under what terms. That's a narrower and more honest question than "theft."

Innovation is a relay race, not a lone genius

We tell a flattering story about invention: the solitary genius, the blank page, the bolt from the blue. It's mostly myth. Newton, no modest man, admitted he saw further only "by standing on the shoulders of giants." Almost everything new is an incremental step on top of someone else's work, often someone in another country, often uncredited.

The irony runs right through AI itself. Every model in this fight, American and Chinese alike, is built on the Transformer, the architecture from a single 2017 Google paper that everyone then copied and extended. The entire industry is one long act of building on a rival's published idea. Three older examples should finish off the myth.

The numbers you do math with were borrowed, then renamed. Place value, the decimal system, and zero as a number were worked out in India; Brahmagupta wrote the rules for zero in the 7th century. Arab scholars absorbed and extended this system. The words "algorithm" and "algebra" both come from al-Khwarizmi and his work. When it reached Europe through Fibonacci in the 13th century, the continent called the digits "Arabic numerals," and India, where they were born, largely fell out of the story. The most basic tool in global commerce is a chain of borrowing in which the original source was written out of its own invention. Nobody now argues Europe should have refused positional notation because it came from elsewhere.

Japan turned copying into a quality empire. For a generation after the war, "Made in Japan" meant cheap imitation. Japanese firms reverse-engineered American cars, cameras, and electronics. Then they took a statistical quality method that US industry had largely ignored, Deming's, and perfected it. The copier became the benchmark the world measured itself against: Toyota, Sony, Canon. Nobody calls Japan's rise theft anymore. We call it excellence. The only thing that changed was the result.

And America climbed the very same way. Britain invented the industrial revolution and guarded it, banning the export of textile machinery and even the emigration of skilled mechanics. So in 1789 a young Briton named Samuel Slater memorized the designs of Arkwright's mills and carried them to America in his head. In Britain he is "Slater the Traitor." In America he is the "Father of the Industrial Revolution." Francis Cabot Lowell did the same with the power loom, touring British factories and rebuilding what he saw from memory. Alexander Hamilton openly urged the young republic to acquire foreign technology by whatever means. American industrial supremacy began as the deliberate copying of a rival who was trying to stop it.

The ladder, and the people who climb it

See the pattern. India seeded the mathematics. The Arab world carried and extended it. Europe took it and built modern science. America copied Europe to industrialize. Japan copied America and beat it on quality. China is now copying America in AI. Each stood on the one before, and each, on reaching the top, was tempted to call the next climber a thief.

Economists have a name for this: kicking away the ladder. You climb using every tool available (copying, borrowing, distilling), and the moment you're on top you develop a deep and sudden respect for intellectual property, then write the rules so the next country can't do what you just did. Britain tried it on America. America is now trying it on China, through export controls and accusations both. The argument always arrives dressed as principle. It is almost always about position.

Where the honest line actually is

I'm not pretending all copying is the same, and the serious version of this argument has to concede the difference. Learning from public work is one thing; deliberately breaking an agreement you signed and using deception to extract outputs at scale is another. If DeepSeek's engineers violated OpenAI's terms of service to do this, that's a legitimate grievance about method, and contracts matter.

But look closely and that is the exact grievance the newspapers have against OpenAI: that it took what it wasn't authorized to take, at scale, and built a competitor on top of it. You don't get to call your own scraping "fair use" and the other side's distillation "theft" from the same set of facts. Either learning-from-the-work-of-others is a legitimate engine of progress, with limits we apply evenly to ourselves and our rivals, or it isn't.

There's a strategic point hiding under the moral one, too. Distillation can shorten the journey, but it can't replace the ecosystem that makes frontier AI: the compute, the chip supply chains, the data pipelines, the talent, the capital. And history is blunt about hoarding: every attempt to lock knowledge in, from Britain's machinery bans to today's chip controls, slowed diffusion a little and spurred the rival's home-grown innovation a lot. The country that wins the next decade won't be the one that litigated hardest. It'll be the one that out-built.

So, genius or theft?

Both, and neither, which is to say the question is the wrong one. It pretends to be about ethics when it's really about power, and about who currently benefits from drawing the line where they've drawn it.

So I'll leave you with this. The next time you hear that a rival "stole" its way to the frontier, ask the older question first: how did the accuser get there? Because almost every great power on that ladder was once the thief in someone else's story.