I always wonder how people can tell. For this particular article, was it the thirty-four occurrences of em dashes with spaces on either side? Something else obvious?
It is the em dashes and the excessive wordiness as well as a lot of "not this, but that".
Eg:
"Not dramatically. Just quietly. " -- This is filler words. Whether it's dramatic or quiet has no relevance to the point they're making.
It also loves threes: "Well-modelled, properly sourced, beautifully visualised to requirements" - again, all irrelevant. The point they're making is that it's measuring the wrong thing, not that "beautifully visual things can be incorrect".
"There’s a piece of this conversation that most leaders miss, and it’s the part I care about most" - this hook of "most people miss" it is very common in AI writing.
Articles of this type suggest a fun game: "LLM or Marketroid?" Because either one could have written it, and both are capable of about equivalent levels of original thought. (whoops did i just say that out loud)
It was the content. So many very specific claims with no source, just stuff being made up. I don't know who Brené Brown is, perhaps she specifically researches trust, but how curious that her daughter can raise a problem with trust, specifically cite two named behaviours that build trust, and then Brown just happens to have a database of trust-building behaviours to hand, that she hasn't even analysed, ready to output a teachable moment.
In the article, she wasn't introduced as a researcher at all, but suddenly "She went back to her research data...". This totally smells like an LLM refactor where it re-emits surface level details, but completely misses the key beats that tie ideas together across a story.
Well, sometimes there's flat-out nonsense that seems to have been written purely to back into the author's thesis:
You cannot design an algorithm that eavesdrops on dinner conversation and dispatches someone to buy a street hot dog, because the person on the receiving end would immediately sense the machinery of it.
But usually there's also:
- Word count hovering between four and five thousand words
- Dramatic/narrative section titles
- "No X, no Y. Just Z"
Last but certainly not least, there's the Lists of Exactly Three Things. I counted literally thirty in this piece. Examples:
- "...the ritual of a human voice, the small exchange about an anniversary or a first date, the warmth of being recognised."
- "Who was celebrating a birthday? Who was on a first date? What had a regular not finished on their plate six months ago?"
- "You can’t purchase it, automate it, or accelerate it with a clever marketing campaign."
- "...forgive outages, laugh off a late delivery, stay through a price increase."
- "...the food arrives hot, the bill is accurate, the room is clean."
- "You notice, you adjust, you respond."
I personally thought to myself "written by AI" after this part:
... the restaurant was fully booked. No warmth. No conversation. Just a long wait and a closed door. In trying to humanise the process, he’d made it worse.
I'm sure some people write this way, but most don't. And AI writes this way.
Eg:
"Not dramatically. Just quietly. " -- This is filler words. Whether it's dramatic or quiet has no relevance to the point they're making.
It also loves threes: "Well-modelled, properly sourced, beautifully visualised to requirements" - again, all irrelevant. The point they're making is that it's measuring the wrong thing, not that "beautifully visual things can be incorrect".
"There’s a piece of this conversation that most leaders miss, and it’s the part I care about most" - this hook of "most people miss" it is very common in AI writing.