Honestly, I hadn’t thought about Noam Chomsky in years. What brought him back to mind was, of all things, Jeffrey Epstein.

His name turned up in reporting on a recent release of Epstein-related documents. According to those reports, Chomsky stayed in touch with Epstein—by then a convicted sex offender—into around 2017, and in one letter called him a “highly valued friend.”

I only read the article; I’m not passing any judgment. The facts, and whether his conduct was right or wrong, aren’t mine to settle. But the news stopped me at an odd place. Wait—why was this man famous in the first place?

Digging around, I landed on an argument from half a century ago. And hidden inside it was one of those mischievous reversals the history of ideas likes to pull.

A man spent his life arguing that “language is, in the end, a matter of reward and habit.” He lost that argument. Famously. And yet, half a century later, the machines that now talk to us—the things we call chatbots—are being polished with exactly that: reward. The loser’s method came back to run the winner’s territory.

This is a short story about that reversal.

Can you teach language the way you train a dog?

There are two main characters.

One is the psychologist B. F. Skinner. He thought a person learns to talk much the way a dog learns to sit. A dog sits, gets a treat, and sits more often. A child says “milk,” gets milk, and says it more. Reward makes behavior. Language is just behavior trained the same way—no special machinery in the head required. In 1957 Skinner published a thick book making this case.

The other is a young linguist named Noam Chomsky. He said this made no sense, and his reason was simple. Children constantly produce sentences no one taught them and no one ever rewarded. A three-year-old will calmly utter a sentence they’ve never heard, one that has never existed before. Dog tricks don’t work like that. So there must be something already in the human head at birth, something built for language. In 1959 Chomsky wrote a thirty-page review that took Skinner’s book apart line by line.

That review won. The field left Skinner and moved to Chomsky’s side, and “humans are born with something for language” became common sense. (In truth the knockout wasn’t as clean as the story says—but set that aside.) Either way, the version in the textbooks is this: Skinner was wrong, Chomsky was right.

And then machines started to talk

Decades pass.

Now we build machines that talk. Here’s how, in two steps and no jargon.

First, we have the machine read an enormous amount of text—nearly all the books, articles, and conversations on the internet. As it reads, it endlessly practices one game: guess the next word. That alone is enough for the machine to start producing fluent, grammatical sentences.

Second—and this is the interesting part—the raw machine is still rough, so people rate its answers one by one. Good answers get a “well done” signal; bad ones get a “not that.” The machine leans, little by little, toward what gets rewarded: more polite, more helpful, more the way people want.

This second step has a long and complicated name, but strip it down and it is exactly Skinner’s idea. Reward the behavior you want, and you get more of it. Like slipping a dog a treat, we slip the machine a bit of praise.

The very method Skinner was mocked for became a standard step in building machines that talk.

But who actually won?

Here the reversal folds over once more.

The machine doesn’t learn language from that reward. By the time we start rewarding it, it can already talk—and it learned that from reading mountains of text, not from praise. Reward doesn’t teach language; it just refines the manners of something that can already speak.

And to read those mountains of text and pick up language at all, the machine also needs the right “shape of head” to begin with. Just any structure won’t do. A carelessly built machine, no matter how much text you feed it, never learns language properly. Only with a particular design (the Transformer) does language start flowing in.

Which is to say: even the machine needs something in place before it can learn language. That is exactly what Chomsky said about babies—that you have to be born with something built for language.

So the scoreboard gets strange.

Chomsky was right. To learn language you need something already in place, and reward alone can’t teach you to talk.

Skinner was right too. Reward really is a powerful way to steer a thing that can already speak in the direction you want.

The talking machine uses both. The two men, who took each other for enemies, turned out to be describing two different halves of the same system.

A handshake half a century late

Read that 1959 argument again today and it no longer looks like one side knocking out the other. It looks more like two people each holding one half of the answer, each insisting the other’s half doesn’t exist.

And their quarrel was settled, almost by accident, by a machine that appeared after Skinner was gone—settled by simply showing that both halves are needed.

Neither party, as it happens, welcomed the reconciliation. Skinner died in 1990 and never saw the machine. Chomsky lived to see it and, far from welcoming it, dismissed it—in a 2023 newspaper essay he called the chatbot a “lumbering statistical engine” that spits out the likely next word, and flatly declared it isn’t real language.

And there’s the final irony. The machine Chomsky waved off as a “calculator with no structure” can’t, in fact, learn language if you build it any old way. As we just saw, it needs the right shape of head first—something in place before it can learn. That is Chomsky’s own claim. The thing he belittled happens to prove his central insight.

We love a tidy story about who demolished whom. But the real ending here isn’t a demolition, it’s a handshake—not the men’s, but their ideas’, shaken by accident inside a machine.

Further reading

  • B. F. Skinner, Verbal Behavior (1957) — the book that explained language as reward and habit.
  • Noam Chomsky, “A Review of B. F. Skinner’s Verbal Behavior” (1959) — the thirty pages that took it down, often called the opening shot of the cognitive revolution.