# Emphatic italics Part of [The AI Tells Index](https://feedsquad.com/ai-tells). A tell signals low effort. It does not identify an author. Skilled writers produce every shape listed here, some of them daily, and automated detectors misread those writers for it at rates measured above 60 percent on non-native English prose. Nothing in this index proves that a machine wrote anything. Read an entry as one piece of evidence to weigh against the false-positive notes printed beside it. ## Facts - Id: emphatic-italics - Category: Formatting (formatting) - Subcategory: emphasis - Also known as: italicised stress, italics-heavy emphasis - Status: Active. Currently signals low-effort writing. - Severity: low - Evidence grade: peer-reviewed (a published study measures the pattern) - Languages: en - Added: 2026-08-15 - Updated: 2026-08-17 - Page: https://feedsquad.com/ai-tells/emphatic-italics ## Description Italics used for spoken stress across running prose. The mark does the job a sharper sentence would have done. ## Why it reads as machine-written The ICML 2025 idiosyncrasies work classifies five model families from text alone at high accuracy and reports that they differ in how they use bold, headers, enumerations and italics. That is an aggregate classifier result on a dated API snapshot, and it does not license calling a single document. Per-model italic rates could not be confirmed at page level by this project, so the ranking here stays qualitative. Two candidate entries were merged into this one during the build, because one measured finding had been minted twice. ## Detection Type: statistical (a measured metric against a threshold with a stated basis) Metric: italic-spans-per-1000-words Threshold: 8 (fires when above) Threshold basis: > No human baseline for italic density in prose has been published in anything this project read. The ICML 2025 work reports formatting differences between chat and instruct variants and notes that italics vary less than bold and headers, without per-model rates this project could confirm at page level. Eight italic spans per 1,000 words is a FeedSquad review trigger and not a published cutoff. A reading above it means read the paragraph, nothing more. ## Examples Constructed specimens. Written for this index. Never quoted from anyone's posts. ### Specimen 1 Before, exhibiting the tell: > The migration *did* run clean. What surprised us was that it ran clean for the *right* reasons, which is the kind of thing you only see clearly afterwards. Most teams never stop to ask *why* something worked, and that is usually the difference between a good quarter and a good year. After, repaired: > The migration ran clean on all 340 accounts, including the two that had needed a manual fix in every previous run. The difference was one ordering change in the batch job, which we found by replaying the June failure against a copy of production. Note: Figures in this repair are invented for the specimen. The tell is the italic stress landing on words the sentence never earned, not the emptiness. The earlier specimen carried a well-observed incident, which made the italics look like ordinary voice. ## False positives Who legitimately writes this way. Conversational essayists stress with italics as a house habit, and the practice has a magazine tradition much older than any of this. Fiction writers italicise interior thought by convention. Academic and technical writing italicises terms on first use, foreign words and titles of works, none of which is emphasis at all. A reviewer separates the two by checking what the italics mark: a convention marks the same category of word every time it appears, while the habit marks whichever word the sentence failed to stress on its own. ## Model attribution Reported at family level and not usable per document. The ICML 2025 study classifies five families from text alone and describes distinct formatting habits including italics, from a dated API snapshot that no longer corresponds to shipping models. An association between italics and one family circulates from the same paper; this project could not confirm the per-model figures at page level and does not print them. ## Platform notes - linkedin: The composer has no italics, so asterisks publish as asterisks and this signal is unobservable there without a rich-text source. - x: Plain-text bodies again. Italic stress can only reach the timeline as Unicode substitution characters, which is a different habit with a different base rate. ## Sources 1. Sun et al., Idiosyncrasies in Large Language Models, ICML 2025 (arXiv:2502.12150) https://arxiv.org/abs/2502.12150 (tier: peer-reviewed; accessed 2026-08-14) 2. vale-ai-tells, 111 machine-checkable rules https://github.com/tbhb/vale-ai-tells (tier: community; accessed 2026-08-14) ## Status history Ids are permanent. A retired tell keeps its id and its page. - 2026-08-15, Active: Active and deliberately weak. The peer-reviewed support is a classifier study showing that model families differ in formatting habits, which is aggregate evidence from a dated snapshot rather than a per-document test. A second candidate entry naming one family by its italics was merged in here, because both rested on that one finding. The threshold is ours and says so. ## License CC BY 4.0. https://creativecommons.org/licenses/by/4.0/ Attribution: The AI Tells Index, feedsquad.com/ai-tells Reuse the data, including commercially. Keep the attribution line. --- Dataset version 1.0.0. Schema version 1. Part of [FeedSquad](https://feedsquad.com). Built by [Herman Foundry](https://hermanfoundry.com) from Levi, Finnish Lapland.