Where is he talking about it as if he did? Don't the parts you quoted make it clear he has not?
As I said in the comment above, reading a paper has never been a good way of understanding what is in it; usually you either have someone give a talk or get it explained to you. Besides, as in another thread above (https://news.ycombinator.com/item?id=50195392), what matters here is not what the paper says, but whether an o(n log n) algorithm exists. Harvey's write-up is about some (new) intuition around why we should expect one (i.e. why we should expect something like the paper's proposed algorithm to be correct).
To be specific: is your problem that, having been provoked by the announcement into thinking more carefully about the problem, he has shared whatever understanding he has arrived at, without literally reading every word of the (poorly written) paper? Why is that a problem, according to you?
I should add a clarification about the phrase “understanding what is in it” in the previous comment, which I realized is ambiguous: obviously, if you care to distinguish what is present vs absent in a paper, you need to read it. But if you care about understanding any new mathematical content it may have (as applies to this case, as I've been saying in this entire thread — if you, like Prof. Harvey care about a potential o(n log n) algorithm, whether or not such an algorithm is contained in OpenAI's paper per se), then it is neither necessary nor (given how it's written) a good idea.
As I said in the linked comment, it does not matter whether the idea came from OpenAI's paper, or was hallucinated by Fable, or was arrived at by the reader while reading a potential nonsensical explanation from Fable: the main message is that the “o(n log n) bound is plausible” and it is valuable to have it come from a human expert.
The fact that he didn't read the paper and he's talking about it as if he did.