My strategy these days is to scan and look for the tells and click out when I see them. Mine was the same "honestly ranked, with no silver bullets on offer". I suspect in less than a year we won't be able to tell the difference.
My strategy these days is to scan and look for the tells and click out when I see them. Mine was the same "honestly ranked, with no silver bullets on offer". I suspect in less than a year we won't be able to tell the difference.
This article was too verbose for me to want to read it, but I'm still not sure about it being LLM-gen'd. All I got is Claude says "honest" a lot.
I’ve thought this for a while, but why hasn’t it happened yet? At this point, OpenAI and Anthropic and friends could definitely remove the AI “smell” from writing output, or give users a first class way to specify a writing style.
So why haven’t they? My theory is they see this as a sort of fingerprint, useful to not train on later. Or something. Maybe they just don’t care. Certainly feels either intentional or a result of ambivalence.
It’s certainly true today that I probably wouldn’t know an AI written article if the author went out of their way to use one of the many prompts available to tone down the AI-isms.
If the underlying prompt of the model stays the same, it seems to me that LLMs will always have common tells unless overridden with a thorough prompt from the end user. It's like if you had 1 person write half of the content on the internet. You'd probably get pretty good at noticing their writing style.
Maybe my understanding of LLMs is wrong, but it seems obvious to me that when you have a large corpus of LLM output you will eventually notice common tells when everyone is using the same models, weights, and base prompt.
It’s natural to the fact it’s the same model. Everyone has tics, and when a given model is asked to write millions of texts, they become visible. But! Some portion of the audience and user base can’t see it, so there is no benefit to fixing it. Case in point, yet another hustler felt very clever posting slop, and the likely actual audience (Google’s ranking system) probably does like it.
Because it's doing what is does best: making predictions, which works great when you're not being judged on aesthetics, such as coding or math, but the human thought process is messy or erratic. It just falls apart when you do the next token process to it. If the goal is to "convey information in readable chunks," AI does great at this.
I have started beating the hell out of Claude with stylometric analyses of writers I admire; usually technical writers like Terry Winograd, Leslie Lamport, Rodney Brooks. Then the “no or minimal rhetorical flourishes” rule; no British em-dashes, and minimize the negative phrase thesis-antithesis fun”. It helps.
I think you are right that in a year or two LLMs will be able to do a good impression of many technical styles. But not Nabokov, Kundera, or Kafka for subtlety.
If one manages to channel Edsger W. Dijkstra I will be impressed and rank it high on my leaderboard.
In a year or more, the audience will likely be an agent instead of a person. It'll be interesting to see how that shifts language and article formats.
It has been for years. The actual audience for a great deal of text you see is Google’s ranking system. Look up any recipe and ask yourself who reads the ten paragraph story time about grandma’s cookies. It literally isn’t intended to be read.
I believe this also partly sprung up because recipes in isolation don't qualify for copyright. The flavor text gives you grounds to sue if a clone of your recipe site pops up somewhere else.
It already is. AI bots overflowing visitor logs now with endless IPs
lol
reminds me of a Claude math paper:
"honestly sharp , no hype: cos(pi+pi)+2+2=cos(2pi)+4=1+4=5"