Generative AI has turned into the kind of arms race we normally associate with doping in sports. By which I mean: the companies involved make a legal product and a bunch of people try to figure out when another bunch of people have used them.
Meanwhile, LLMs and chatbots keep “improving” – by which most people mean that the early obvious markers of non-human prose have diminished. As in doping, every time you develop an accurate test, the companies release a new model that evades the known tests. So you make a new test, and…
Meanwhile, people trade secrets – in this case, “signs of AI”. One of the first casualties of the generative AI era was the innocent word “delve”, which in 2024 was outed as a signal (but also a sign of Nigerian business English). Wikipedia, which battles all sorts of slop, has put real thought into detection. But simpler lists abound: overuse of em-dashes, repetition, a certain “generic blandness”, lacking sources, rule-of-three patterns. Pause to think: isn’t the rule of three the basis of a lot of comedy?
The reality is we can’t tell for sure from short passages of prose. Even the professionals can’t, or not reliably: this year has seen several high-profile cancellations and withdrawals of novels that were read and reread by many layers of readers, editors, and acquisitions teams at multiple agents and publishers before anyone questioned the provenance.
In March, Amelia Hill at the Guardian mulled the fate of the horror novel Shy Girl by Mia Ballard, which Hachette published in the UK in November 2025 only to withdraw it and cancel its US release after a review sparked by questions readers raised on social media. The author denied she used AI, telling the New York Times an acquaintance she hired to edit the self-published version of the novel had used it.
In July, first-time novelist Jerry Falade had a $2 million book deal canceled when the author’s agents withdrew the manuscript on suspicion AI was used to write it. Falade denies the charge.
And just this week, at UC Berkeley, a professor used an AI chatbot to edit an op-ed complaining that her students are underprepared in math – which, frankly, the math thing seems like it ought to be the bigger story.
Aren’t you curious, though, what about Falade’s book made the agents call it – in their cancellation announcement – “amazing”, and “stunningly good” and say “everyone fell in love with it” and “it dazzled us”? It’s hard not to read that praise and think that at some point there will be a hugely successful book that fools everyone and the financial rewards will lead most people to abandon their objections. After all, popular fiction has had numerous human-written successes that critics think are awful by any reasonable standard.
It all depends why you read what you read. AI’s inability to shed new light on the human condition is separate from whether it can churn out serviceable by-the-numbers genre fiction. It’s possible that the only thing standing between us and that future is copyright law: AI-generated prose so far can’t be copyrighted (limiting publishers’ interest) and there’s always the risk it will insert a long enough passage from some other unrecognized copyrighted work to fuel a plagiarism lawsuit. So for now, publishers will go on inserting clauses in authors’ contracts requiring them to guarantee they have not used AI.
David Shariatmadari collected some of these scandals at the Guardian in early July. As he shows, it’s hard for humans to tell human from AI in short passages, and not that hard even to deliberately fool Pangram, currently considered the best of the AI detection sites, which themselves are extensions of the generation of sometimes-flawed plagiarism sites developed circa 2000, when the Internet suddenly offered students billions of words to copy and paste.
In the latest round of updates, Anthropic has said that all new models will mark AI content, in line with the EU AI Act’s Article 50(2) Code of Practice on Transparency of AI-Generated Content. At Tom’s Hardware, Graham Barlow notes that given those are the rules, OpenAI and Google may well follow suit. He also predicts an exodus of Claude customers unless either a) the watermarking is easy to bypass or b) all the other models adopt watermarking.
From Anthropic’s explanation in its announcement, it sounds like the “watermark” will take the form of subtle low-stakes choices of specific words that taken together will create a pattern detectable to anyone who has the encoding key. I am dubious about this, if only because historically watermarks on digital media have been quickly cracked. But also because: text is so easily copied, pasted, edited, swapped around, or stuffed into another chatbot and regenerated.
The issue that’s even harder to solve is that as AI prose proliferates that’s the style new writers will copy: humans learn to write by reading. They will copy the blandness and lack of personal voice many attribute now to AI-generated prose. Only computers will be able to tell – and even then, not for sure.
If this were happening in a sport, authors would be required to do all their work on a shared screen on the most boring livestream of all time that publishers and readers could check whenever they want.
Illustrations: A parrot in a southwest London garden.
Wendy M. Grossman is an award-winning journalist. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.
