A look at various quirks in AI-generated prose, mainly influenced by “overfitting” in AI models, as humans increasingly mimic AI language in writing and speech
Plus: otherworlds, cozy lit and VHS rentals Max Read / Read Max : Will A.I. writing ever be good? Alberto Romero / The Algorithmic Bridge : The Death of the English Language X: Joe McKendrick / @joemckendrick : Every AI-written sentence “sings, yes, but honestly? It sings a little flat. It doesn't open up the tapestry of human experience — it reads like it was written by a shut-in with Wi-Fi and a thesaurus. Not sensory, not real, just ... there.” https://www.nytimes.com/... Matthew Kassel / @matthewkassel : “I think at some point in those first five days, everyone independently noticed that the really funny part about getting A.I. to answer various wacky prompts was the wacky prompts themselves — that is, the human element” https://www.nytimes.com/... Willy / @willystaley : In this week's Magazine: Sam Kriss on the unfortunate quirks of AI's prose style. https://www.nytimes.com/... Nate Silver / @natesilver538 : This is good — even if it slanders the em-dash. AI's tendency to statistically smooth out the rough edges produces extremely mid prose. https://www.nytimes.com/... @esotericcd : I am the king of em-dashes, and have been employing them since I was still literally writing out my school assignments in longhand. (We did this in high school! Couldn't really cheat!) I resent that they have now become an “AI signature.” Matthew Zeitlin / @mattzeitlin : after chatgpt was released, british MPs started using phrases in their parliamentary speeches that american congressmen use in their floor speechs [image] John Merrick / @johnpmerrick : Brilliant essay by Sam Kriss on what is so strange about AI generated text. Also manages to distill my greatest fear about AI: that i too will end up writing, unconsciously, like an AI chatbot https://www.nytimes.com/... [image] Bluesky: Paul Waldman / @paulwaldman : Read this NYT piece by Sam Kriss about AI's distinctive writing style - especially “It's not X - it's Y” - and then look at this horror of an AI-generated article, which uses all the tropes he identifies, over and over again. — www.nytimes.com/2025/12/03/m... [embedded post] Asher Elbein / @asherelbein : This is a very good and interesting rhetorical analysis of AI's very particular and strange quirks Nick Sousanis / @nsousanis : “A lot of A.I.'s choices make sense when you understand that it's constantly tickling the Simpsons.” — Smart and horrifying look at Ai writing and its ubiquity... www.nytimes.com/2025/12/03/m... Cynthia Brumfield / @metacurity.com : “But the simplest theory of why A.I.s are so fixated on the em dash is that they use it because humans do. This particular punctuation mark has a significant writerly fan base, and a lot of them are now penning furious defenses of their favorite horizontal line.” — www.nytimes.com/2025/12/03/m... Arin Arcady / @rnrkd : This has a number of interesting insights. One is something that Gary Shteyngart commented on when I went to see him the other week: that A.I. is almost wholly incapable of writing comedy. It can be inadvertently funny with bizarre responses, but that's not comedy. — www.nytimes.com/2025/12/03/m... Elias Isquith / @eliasisquith.blog : i try not to be a doomer but reading this put me in a real “hannah arendt decides to write a book about how latent totalitarianism is the only thing that matters” mood Forums: r/Longreads : Why Does A.I. Write Like ... That? (Gift Article) r/artificial : Why Does A.I. Write Like ... That?
Context & Ripple Effects
Earlier coverage documented both the hollowness writers found in style-mimicking AI output and the expanding presence of machine-generated text across the internet. This piece shifts the focus from whether generated prose is convincing to how its recurring habits can become recognizable cultural patterns.
The arc also includes authors treating chatbots as a creative muse rather than a replacement author. The concern here is that repeated exposure may blur the distinction: people can begin adopting the same statistically smoothed phrasing the tools produce.
First-order effects
- Writers, editors and readers gain a clearer set of cues—flattened tone, formulaic phrasing and conspicuous punctuation habits—for recognizing and revising AI-shaped prose.
- As people imitate those cues in writing and speech, AI’s stylistic signature can spread beyond text directly produced by a model.
Second-order effects
- Editorial workflows may put more value on voice, sensory specificity and deliberate revision, because generic polish becomes less reliable as a marker of quality or authorship.
- Tools positioned as writing aids face pressure to reduce repetitive stylistic defaults; otherwise their output can impose a recognizable house style on users’ work.
Third-order effects
- If human and generated language continue to converge, provenance will matter less as a matter of detection alone and more as an editorial question of whether text carries distinct judgment and experience.
- This is an instance of generative editorial debt: scaling fluent text can create a later cleanup burden as organizations try to preserve differentiated voice.
The trend: Generative AI is moving from a content-production tool into a feedback loop that can standardize the language humans use around it.