The irony is that studies show LLM detectors have a much higher false-positive rate for non-native speakers [1]. If most of what you read stems from LLMs, you end up writing like an LLM.
[1]: https://hai.stanford.edu/news/ai-detectors-biased-against-no...
LLM writing has not been overly abundant for more than a couple years. I don't know where you got the idea that an entire generation of people have already learned to write like an LLM.
Specifically, I’ve recently used ChatGPT for legal/administrative writing where the AI seems to be trained on a large corpus and seems to know the conventions and vocabulary well; a lawyer who reviewed the work had important corrections. Before AI, I would have sought model filings and have had less success at emulating the genre. So it’s lowered time/cost somewhat but it takes lots of diligence. By default, current AI outputs seems intelligible but are still really far off the mark. I’ve found a structured interview is a good way to start rather than jumping into draft generation.
And it’s a good contrast with ‘just fcking use Go’ article he linked.
Go article is much more human. I love that and would choose a human centered language and human centered culture over LLM-centered everything every time
I guess I am just old
why scoff over someone doing assisted writing? i might age myself but kids back in the day would try to sound better by using synonym feature in ms word (or through web thesaurus) for their assignment essays. this all looks familiar to the same practice, now only made more accessible.
I feel the opposite, where AI hype is so extreme that merely someone pointing out an article may have had LLM involvement prompts a response like this. Someone incredulously painting people as ivory tower nose thumbers. If anything, it pushes me away from LLM writing more.
I also don't see how you can compare finding a synonym for a word to having your entire writing voice determined for you.
The author of this article has what seems like it could be a relatively thriving consulting business, so he probably writes more to advertise his services than anything else. That kind of writing surely lends itself to a particular writing style, which is a non-insignificant chunk of the kind of writing that LLMs were trained on.
It is, if I may say that, _genuinely_ hard to use LLM assist and not make the text look like LLM generated. Even when I write an email in gmail and it gives its suggestions to make the text better, each one individually makes perfect sense, but when I click a few of them, the whole email now looks like AI slop, so I would normally undo the changes, going back to my imperfect hand-written non-optimized version.
Take this paragraph as example:
> Go got generics in 1.18, and they’re useful, but the implementation has constraints (no methods with type parameters, GC shape stenciling, occasional surprising performance characteristics). Rust generics monomorphize, each instantiation produces specialized code with zero runtime cost. Combined with traits, this gives you real zero-cost abstractions.
Every sentence says something. Every sentence is important and holds its weight. I would expect that kind of writing from very specialized books or papers, not from a blog post. Also, it makes the post harder (and more boring) to read.
I actually prefer that style of writing! (When it's not AI-generated ofc.) And I also try to use it in my technical blog posts. I usually re-read my drafts asking myself: "Does the reader actually care about this? Is this sentence adding something or is it just fluff?"
And actually I feel like AI text usually produces more fluff, or anyway I notice it more, but I see how it can make the result "robotic and boring".