# Institutional abstraction verbs 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: institutional-abstraction-verb - Category: Lexical (lexical) - Subcategory: abstraction-verbs - Also known as: enhance, foster, fostering, facilitate, leverage, utilize, streamline, optimize - Status: Active. Currently signals low-effort writing. - Severity: medium - 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/institutional-abstraction-verb ## Description Institutional verbs standing in for the specific verb for what was done. Enhance, foster, facilitate, leverage, utilize, streamline and optimize describe an improvement in the abstract, and the abstraction is the problem: the sentence survives without the writer knowing what happened. These verbs sit in the released excess-word set from Kobak and colleagues and in the LexA per-language data. The pattern matches verb plus abstract object, so facilitating a meeting and a machine that utilizes a counterweight both escape it. ## Why it reads as machine-written Each of these verbs takes almost any object, which makes them the safest possible choice when the object is unknown. A writer who watched the thing happen usually has a narrower verb available and uses it. ## Detection Type: deterministic (a regular expression, run as written) Scope: sentence ECMAScript regular expression. The build validator compiles it and tests it against this entry's own specimens. ```regex \b(?:foster(?:s|ed|ing)?|facilitat(?:e|es|ed|ing))\s+(?:an?\s+|the\s+)?(?:culture|environment|collaboration|innovation|engagement|dialogue|growth|community)\b|\bleverag(?:e|es|ed|ing)\s+(?:our|their|your|its)\s+\w+\s+(?:to|for)\b|\butiliz(?:e|es|ed|ing)\s+(?:an?\s+|the\s+)?(?:variety|range|approach|framework|strategy|tools?|resources)\b ``` Flags: gi ## Examples Constructed specimens. Written for this index. Never quoted from anyone's posts. ### Specimen 1 Before, exhibiting the tell: > The new workspace fosters collaboration and helps teams utilize a variety of tools more effectively. Work gets easier to see when it lives in one place, which is usually the thing that was missing. After, repaired: > The workspace has one shared calendar. Before it existed, two people published to the same channel twenty minutes apart on 12 May and neither knew the other had scheduled anything. Note: Figures in this repair are invented for the specimen. The repair names the failure the change was made against. ## False positives Who legitimately writes this way. Education, development and grant writing use foster and facilitate as the standard terms, and a funder who asked for a proposal about fostering literacy will expect the proposal to say fostering literacy. Facilitation is a named profession with its own certification, so a facilitator facilitating is not a euphemism. Consulting and finance adopted leverage decades before any model existed and use it with a precise meaning about borrowed capital. Optimize is a mathematical term. The pattern therefore requires an abstract object, which lets the concrete uses through: the crane that utilizes a counterweight and the meeting that was facilitated on 3 March both escape. A reviewer should ask what the narrower verb would have been, and whether the writer could have supplied it. ## Model attribution No vendor attribution. Membership in the Kobak released excess-word set is a corpus-level fact about biomedical abstracts, and the paper assigns nothing to any model family. ## Platform notes - wikipedia: The maintained list keeps these verbs in its current set and pairs them with the corroboration rule that governs every word on it. ## Sources 1. Kobak et al., Delving into LLM-assisted writing in biomedical publications, Science Advances 11(27) https://www.science.org/doi/10.1126/sciadv.adt3813 (tier: peer-reviewed; accessed 2026-08-14) 2. LexA-Index, CC0 per-language overuse dataset https://github.com/fsu-nlp/lexa-index (tier: primary-doc; accessed 2026-08-14) 3. Wikipedia: Signs of AI writing https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing (tier: community; accessed 2026-08-14) 4. 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. The verbs are in the Kobak excess-word set and carry current rules in vale-ai-tells, and nothing in the evidence base reports them declining. Severity is medium because the abstraction hides content rather than merely decorating it. ## 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.