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It’s pretty clear that the author isn’t using the technical definition of big O but rather is using it in a descriptive way. It’s not ambiguous in any way so what’s the harm?

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I would say no harm, but rather confusing to people that do not know big O, and useless to those who do.

Can you explain how it's wrong? Obviously, normally you want things to scale more slowly rather than faster, but other than applying to a different thing than usual, it seems accurate to me -- human drivers improve at a constant rate regardless of how many there are, and self-driving cars improve linearly with their number.

A function being in O(f(x)) means the function grows no more than a (multiplicative) constant factor faster than f(x). So O(1) is a subset of O(n). O is analogous to <=.

The semantics that GGP comment meant to convey are better represented by saying that autonomous cars' driving experience grows with Ω(n) (analogous to >=) or Ɵ(n) (analogous to =).

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