Except for the cases where no writing is better than LLM writing. The author's take seems ok to me, but what I struggle with most in AI writing is that it removes or abstracts away the intent of the original author. Not in every sentence and in every thought. But when a human says something, I can reason about why they said it the way they did. There are threads worth tugging on. 2 easy-to-understand examples: 1. when an ESL writer communicates something in awkward English, it's a fascinating glimpse into how they normally communicate about concepts. The meaning is usually not too difficult to infer and I can see how their language or culture affects how they see mine. It's very fun. 2. if an expert explains something and I get lost, that's usually a hint that my mental model could change to see the problem/solution more like they do.

But when a person expert or no uses an llm, information is being lost. If I misunderstand an llm's sentence, it is possible that "it knows what it's talking about", but with how frequently they don't know what they're talking about, I usually don't try and move on. It's not worth it.

In America, at least, though perhaps this applies more broadly, so many trends over the past decades all converge towards the lowering of the baseline levels of trust you should give towards a stranger (whether valid or not!). And llms have been a net-negative so far. We have exchanged some amount of trust for intelligence. And it didn't have to be an exchange.

I care less about llm disclosure and more about this: If you use an LLM for writing, please think sincerely about whether the output accurately represents what you would say and how you would say it to another person. Please avoid serving others nothingburgers and wordsalads. This has always been possible and it's easy to do it without realizing it with LLMs. The output can survive a scan, but dissolves upon further inspection.

tldr; make sure that what you publish is trustworthy.