I recently built and delivered an AI-driven novel-writing program. The architecture involved chaining the Claude, GPT, and Gemini APIs together so they could cross-critique and iteratively revise the text, while systematically saving key plot points and lore chapter-by-chapter. (Serialized 'web novels' published on a per-chapter basis are a massive industry here in Korea). AI has already heavily infiltrated the fiction space in Korea, and it looks like the exact same trend is hitting the US.

Personally, I find it incredibly easy to spot AI-generated text in Korean, but catching it in English is much harder for me. That being said, they still have very distinct, overused patterns. You constantly see words like 'ultimately' or 'structural,' and they rely heavily on highly formulaic 'X is Y' sentence structures.

It's a bad short story. Whether it was generated at the hands of humans or a computer isn't really relevant. Speaking in riddles is cheap now, so authors better learn how to surprise the reader in simpler, more readable words. It seems to be something that LLMs are quite bad at.

I liked the playfulness of:

  Mixed metaphors which sound nice at first glance, but slip away from meaning like an echo chasing itself off a cliff.

  Similes that catch in your mind like river trouts tangled in the roots of a redwood tree.

Also mentions some interesting AI tells, for AI generated stories.

The worst thing about this is not really that somebody might have had AI help writing a story, but that an editor thought they could get any kind of useful information from asking an AI whether the story was written by AI. If there's any hope of editors staying ahead of this phenomenon, they will need to educate themselves a lot better about how it actually works.