# Authenticity vocabulary tic

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: authenticity-vocabulary-tic
- Category: Platform-specific (platform)
- Subcategory: vocabulary
- Also known as: authenticity and vulnerability in every post, community language without a community
- Status: Active. Currently signals low-effort writing.
- Severity: low
- Evidence grade: primary-doc (platform policy, vendor documentation, or a model card)
- Languages: en
- Added: 2026-08-15
- Updated: 2026-08-15
- Page: https://feedsquad.com/ai-tells/authenticity-vocabulary-tic

## Description

The pairing of authenticity with vulnerability, in post after post, by an account that demonstrates neither. The tell is the pairing and the frequency, never either word on its own. Both words have ordinary uses and one of them is a clinical term.

## Why it reads as machine-written

The vocabulary is what a post about connection reaches for when it has no incident to describe. An assistant asked for a thought-leadership post on LinkedIn produces the pair because the corpus pairs them. The reader-side version of this observation shows up in public comments on LinkedIn's own posts about automated engagement, where members list the pairing alongside instant reaction bursts as what they use to spot a farmed account.

## 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
\bauthenticit(?:y|ies)\b[^.!?\n]{0,60}\bvulnerabilit(?:y|ies)\b|\bvulnerabilit(?:y|ies)\b[^.!?\n]{0,60}\bauthenticit(?:y|ies)\b|\bbring(?:ing)? your whole self\b|\bshow(?:ing)? up authentically\b
```

Flags: gi

## Examples

Constructed specimens. Written for this index. Never quoted from anyone's posts.

### Specimen 1

Before, exhibiting the tell:

> Leadership in 2026 comes down to authenticity and vulnerability. The teams that win are the ones showing up authentically every day, and the leaders who win are the ones who let people see them.

After, repaired:

> I told my team in April that we had eleven weeks of runway left and that I did not know whether the Series A would close. Two people started interviewing elsewhere. One of them stayed and now runs support. I would do it again, and I would do it four weeks earlier.

Note: The repair replaces the vocabulary with the thing the vocabulary was standing in for. Figures in this repair are invented for the specimen.

## False positives

Who legitimately writes this way.

Coaches, community managers, therapists and people who run peer support groups write about these things constantly because they are the subject of the work, not a garnish on it. Recovery writing pairs the two words by necessity. The reviewer check is whether the post contains an instance: one moment where the writer was actually exposed, with a consequence attached. Vocabulary plus an instance is a subject. Vocabulary plus nothing is a costume.

## Model attribution

No family attribution. No vendor documents suppressing this pairing, and it appears across assistants asked for LinkedIn thought leadership.

## Platform notes

- linkedin: The vocabulary observation comes from public commenters on a LinkedIn employee's post about coordinated engagement, not from LinkedIn policy. That post, by Oscar Rodriguez in early 2026, confirms group removals and warnings sent to thousands of members. The March 2026 newsroom post defines automated comments and engagement pods and says nothing about wording. No LinkedIn document names any vocabulary at all.

## Sources

1. Oscar Rodriguez, LinkedIn post on authenticity signals
   https://www.linkedin.com/posts/orodriguez_earlier-this-fall-i-shared-an-article-about-share-7407561708262703105-l99B
   (tier: primary-doc; accessed 2026-08-14)
2. LinkedIn newsroom, authentic content and conversations (Mar 2026)
   https://news.linkedin.com/2026/authentic-content-and-conversations
   (tier: primary-doc; accessed 2026-08-14)

## Status history

Ids are permanent. A retired tell keeps its id and its page.

- 2026-08-15, Active: The observation is reader-side folk knowledge with two first-party LinkedIn documents attached, which is why it ships active at low severity. It is a vocabulary tic and vocabulary tics decay fastest, so expect this one to weaken.

## 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.

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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.