# Confident misattribution 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: confident-misattribution - Category: Semantic (semantic) - Subcategory: attribution - Also known as: plausible false credit, attribution that propagates unchecked - Status: Active. Currently signals low-effort writing. - Severity: medium - Evidence grade: community-observed (named by practitioners, no formal measurement exists) - Languages: en - Added: 2026-08-15 - Updated: 2026-08-17 - Page: https://feedsquad.com/ai-tells/confident-misattribution ## Description A credit that sounds right and travels because nobody opens the primary. The named person is real, the quote or the coinage is nearly theirs, and the correction is one click away and never made. ## Why it reads as machine-written Attribution is a slot, and the most probable filler for it is whoever is most associated with the topic, which is often not whoever did the thing. The worked example sits inside this index's own subject: it is widely claimed that a particular developer coined the term slop for unwanted machine output. His own widely cited post from May 2024 credits an earlier user and says the term was already in circulation. The post is short, it is public, and the claim it contradicts is still repeated in marketing copy. ## Detection Type: judge (a rubric for a lightweight model judge) Rubric for a lightweight model judge: ```text Task: check attributions against their primaries. Step 1. List every attribution of a coinage, quotation, finding, invention, prediction or position to a named person or body. Step 2. Open the primary. Not a summary of it, not a news write-up: the thing itself. Step 3. Ask three questions. Did this person say it? In the place cited? In this sense? Step 4. Where the attribution is a coinage, check specifically whether the named person claims it themselves. Popularisers are routinely credited with coinage they disclaim. Escape hatches: contested attributions where sources genuinely disagree and the text acknowledges the dispute; attributions inside a quotation, which belong to the speaker; claims of popularisation rather than origination, which are a different claim; paraphrase marked as paraphrase; primaries that cannot be reached, which return UNKNOWN. Decision. FLAG when the primary is reachable and contradicts the attribution. WEAK when no primary is cited at all. PASS when the primary supports it or the dispute is acknowledged. Output: the attribution, what the primary says in one sentence, and the verdict. ``` ## Examples Constructed specimens. Written for this index. Never quoted from anyone's posts. ### Specimen 1 Before, exhibiting the tell: > The term was coined in 2024 by the developer who wrote the definitive post about it. The name stuck because it captured something the industry had been circling for a while without having a word for it. That is usually how vocabulary works: someone says the obvious thing at the right moment and everyone else recognises it immediately. After, repaired: > The developer who wrote the widely cited 2024 post says in that post that he did not coin the term, and credits an earlier user. No dated first use has been produced by anyone, so this piece does not give one. Note: The developer in the specimen is deliberately unnamed. The two sentences after the claim explain why the credit felt right and check nothing, which is how a misattribution travels. The repair is not gentler wording. It is what the primary says, and the primary took a minute to read. ## False positives Who legitimately writes this way. Attribution is contested more often than people assume. Independent invention happens, quotations migrate to more famous mouths over a century, and scholarly priority disputes run for decades without resolution. Popularisation is also a real contribution, and crediting the person who made an idea travel is defensible so long as the sentence says that is what it means. Oral traditions and collaborative work resist single attribution altogether. The check is not whether the credit is contested but whether a reachable primary contradicts it, and where the primary cannot be reached the honest verdict is that the claim is unverified rather than wrong. ## Model attribution No vendor can be named. The misattribution catalogued here spread through human marketing writing, and the pattern predates any assistant by a long way. ## Sources 1. Simon Willison, slop is the new name for unwanted AI content https://simonwillison.net/2024/May/8/slop/ (tier: community; accessed 2026-08-14) ## Status history Ids are permanent. A retired tell keeps its id and its page. - 2026-08-15, Active: One reachable primary that contradicts a widely repeated claim about its own author. Single source, so the grade is community-observed, and the worked example is chosen because a reader can check it in a minute. ## 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.