My hunch that this is substantially LLM-generated is based on more than that.
In my head it's like a Bayesian classifier, you look at all the sentences and judge whether each is more or less likely to be LLM vs human generated. Then you add prior information like that the author did the research using Claude - which increases the likelihood that they also use Claude for writing.
Maybe your detector just isn't so sensitive (yet) or maybe I'm wrong but I have pretty high confidence at least 10% of sentences were LLM-generated.
Yes, the stylistic patterns exist in human speech but RLHF has increased their frequency. Also, LLM writing has a certain monotonicity that human writing often lacks. Which is not surprising: the machine generates more or less the most likely text in an algorithmic manner. Humans don't. They wrote a few sentences, then get a coffee, sleep, write a few more. That creates more variety than an LLM can.
Fun exercise: https://en.wikipedia.org/wiki/Wikipedia:AI_or_not_quiz
Someone probably expended a lot of time and effort planning, thinking about, and writing an interesting article, and then you stroll by and casually accuse them of being a bone idle cheat, with no supporting evidence other than your "sensitive detector" and a bunch of hand-wavy nonsense that adds up to naught.
I also hate this style of plastic, pre-digested prose. Its soulless and uninteresting. Maybe I've just read too much AI slop. I associate this writing style with low quality, uninteresting junk.
If there is constant vigilance on the part of the reader as to how it was created, meaning and value become secondary, a sure path to the death of reading as a joy.
More importantly, it's an article about using Claude from a company about using Claude. I think on the balance it's very likely that they would use Claude to write their technical blog posts.
Your job doesn't require you to think or expend effort?
For what it’s worth, Pangram reports that Marcus’ article is 100% LLM-written: https://www.pangram.com/history/640288b9-e16b-4f76-a730-8000...
73% judged GPT 4o to be the human.
https://arxiv.org/abs/2503.23674
Not only are people bad at judging this, but are directionally wrong.
> Our experiments show that annotators who frequently use LLMs for writing tasks excel at detecting AI-generated text, even without any specialized training or feedback. In fact, the majority vote among five such “expert” annotators misclassifies only 1 of 300 articles, significantly outperforming most commercial and open-source detectors we evaluated even in the presence of evasion tactics like paraphrasing and humanization.
Even though they are perfect for usage in writing down thoughts and notes.
“An em dash… they’re a witch!”… “it’s not just X, it’s Y… they’re a witch!”
that's a strawman alright; all the comments complaining how they can't use their writing style without being ganged up on are positive karma from my angle, so I'm not sure the "positive social reactions" are really aligned with your imagination. Or does it only count when it aligns with your persecution complex?
AI writing also tends to show these indicators over and over, consistently, over passages of text. It is very hard for humans, even if they are really familiar with AI writing, to be that consistent, and almost impossible for them to be that consistent for more than a sentence or two. Writing a long blog post by hand that is believably "AI-written" takes the amount of purposeful skill you'd need to forge an entire painting or ancient document.
The problem is that people either look for the wrong things, look for obsolete things ("delve" is dead and modern LLMs have killed it), or extrapolate things from indicators that are extremely narrow and specific.
This insistence that certain stylistics patterns are "tell-tale" signs that an article was written by AI makes no sense, particularly when you consider that whatever stylistic ticks an LLM may possess are a result of it being trained on human writing.