On the other hand, if one uses AI but keeps content density constant (e.g. grammar fixes for non-native speakers) or even negative (compress this repetitive paragraph), I think it can be a useful net productivity boost.
Current AI can't really add information, but a lot of editing is subtracting, and as long as you check the output for hallucinations (and prompt-engineer a lot since models like to add) imo LLMs can be a subtraction-force-multiplier.
Ironically: anti-slop; or perhaps, fighting slop with slop.
The essay kind of works for me as an impressionistic context for the three papers, but without those three papers I think it's almost more confusing than it helps.
Eg
> This suggests that the EM structure isn’t just an analogy — it’s the natural grain of the optimization landscape
I don't care if someone uses llm. But it shows a lack of care to do it in this blatant way without noting it. Eg at work I'll often link prompt-response in docs as an appendix, but I will call out the provenance
If you find those sentences to be helpful, great! I find it decreases the signal in the article and makes me skim it. If you're wondering why people complain, it's because sharing a post intended to be skimmed without saying, hey you should skim this, is a little disrespectful of someone's time
As someone in the field, this means nothing, and I'm very suspicious of the article as a whole because it has so many sentences like this.