I'm not well-informed on the subject, but I seem to remember that Chomsky's point was exactly on the data: his hypothesis about the human language faculty being

I'm not well-informed on the subject, but I seem to remember that Chomsky's point was exactly on the data: his hypothesis about the human language faculty being innate (a "universal grammar", or "linguistic endowment" as he's been calling it more recently) was about the so-called "poverty of the stimulus". Meaning that human infants learn human languages while being exposed to pitiably insufficient amounts of data. Again, to my recollection, he based this on Mark E. Gold's result about language identification in the limit, which, simplifying, is that any language more complex than a finite language (in the Chomsky hierarchy of languages) is learnable only from an infinite number of positive examples, and languages more complex than regular languages also need an infinite number of negative examples. And those are labelled examples- labelled by an oracle. Since human language is usually considered to be at least context-free, and since infants are not exposed to infinite numbers of examples of their maternal languages, there must be some other element that allows them to learn such a language, and Chomsky called that a "universal grammar" etc. Still from memory, Chomsky's proposition also took account of data that showed that human parents do not give negative examples of language to their children, they only correct by giving positive examples (e.g. a parent would correct a child's grammar by saying something along the lines of "we don't say 'eated', we say 'eaten'"; so they would label a grammar rule learned by the child as incorrect -the rule that produced 'eated'- but they wouldn't give further negative examples of the same, or other rules, that produced similarly wrong instances, only a positive example of the correct rule. That's my interpretation anyway). Again all this is from memory, and probably half-digested. Wikipedia has an article on Gold's famous result: https://en.wikipedia.org/wiki/Language_identification_in_the_limit https://en.wikipedia.org/wiki/Language_identification_in_the... Incidentally, Gold's result, derived in the context of the field of Inductive Inference, a sort of precursor to modern machine learning, caused a revolution in machine learning itself. The very negative result caused Leslie Valiant to develop his PAC-Learning setting, that basically loosens the strong requirements for precision of Gold's identification in the limit, and so justified the focus of modern machine learning research to approximate, and efficient, learning. But that's another story.