Section 04 of 06
AI content, provenance and authorship on shared links
A shared link used to raise one question: does the preview look right? It now raises a second one: who made this, and was it a person? Feeds carry a growing share of generated images and text, platforms label some of it, and readers look for signs that someone is accountable for what they are reading.
The guides in this section apply the same plugin-neutral method as the rest of the handbook to that second question. They cover what publishers can control on their own pages: provenance data on images, authorship tags in the page head, byline structured data, and an honest disclosure policy, plus how platforms decide when to add a label.
Every other section is listed guide by guide in the numbered index on the homepage.
The guides in this section
- AI-generated content in social feeds: what publishers should doHow AI-generated images and text change what happens when your posts are shared, and the practical steps publishers can take: disclosure, provenance, bylines.7 min read
- Content Credentials on shared images: what survives a shareWhat C2PA Content Credentials are, why WordPress image sizes and social uploads often strip them, and how to keep provenance on the images you share.6 min read
- Authorship tags for shared links: author, article:author and fediverse:creatorAdd authorship signals to link previews: the author meta tag, article:author, twitter:creator and fediverse:creator, with WordPress code and testing steps.6 min read
- Byline schema in WordPress: marking up a human authorMark up article authors with schema.org Person data in WordPress: the fields search engines read, author pages, sameAs profiles and common mistakes.6 min read
- How platforms label AI content, and what triggers the labelHow major platforms decide to label AI-generated or altered media: creator disclosure, provenance metadata, detection, and how publishers avoid mistakes.6 min read
- Labelling AI-generated images in link previewsHow to label an AI-generated og:image honestly: captions, alt text, digital source type metadata and what networks show when the card is shared.6 min read
- AI disclosure lines that survive a shareWhere to put an AI assistance disclosure so it reaches readers who only see the share card: titles, descriptions, bylines and the first lines of a post.5 min read
- Checking Content Credentials before you share an imageHow to check an image's Content Credentials before you share or publish it: what a C2PA manifest shows, what a missing one means, and what to record.5 min read
- Where image metadata gets stripped: WordPress, CDNs and uploadsWhere IPTC, EXIF and Content Credentials metadata is lost between your camera and a reader's feed: WordPress resizing, optimisers, CDNs and social uploads.5 min read
- Can an AI detector judge a social post?Why AI text detectors are least reliable on the short, informal text of social posts and captions, what published tests found, and what to rely on instead.5 min read
- Invisible watermarks on AI images: what they can proveHow invisible watermarks on AI-generated images work, how they differ from Content Credentials, what a detected watermark proves and what it cannot.5 min read
- Spotting AI images in your feed: checks that hold upWhich checks for AI-generated images in a social feed actually hold up: platform labels, provenance data, earlier copies and the source, and which tells fail.5 min read
- Accused of posting AI content: how to show your workWhat to do when readers, a client or a platform say your post or article was written by AI: the evidence that settles it and what does not help.5 min read
- Share preview integrity: does the card match the page?A test routine for share preview integrity: what a link card is built from, the four ways it drifts from the page, per-network checks and a share test log.7 min read
- What platforms strip from shared images: EXIF, XMP and C2PAWhat platforms strip from shared images: how EXIF, XMP and IPTC fields and C2PA manifests die on upload or preview fetch, plus a probe method and a table.7 min read
How this section connects to the rest of the handbook
Everything here builds on link previews. Authorship tags sit beside the Open Graph tags you already output, provenance data lives in the same image your og:image tag names, and the byline markup follows the one-source rule that prevents duplicate tags. If your previews are not yet reliable, fix them first with the Open Graph section.
What we do not cover
We do not review AI writing tools or detectors, and we do not recommend any product. Detection of generated text is unreliable, so the guides focus on signals a publisher can state and stand behind rather than on tools that guess.
Where to start, by situation
You publish images and want your authorship to survive a share. Read content credentials on shared images first, then where image metadata gets stripped, because the second explains why the first so often fails. Someone has said your writing or your images were generated. what to do when you are accused of posting AI content gives the evidence of process that answers the claim, and whether an AI detector can judge a social post explains why a score is not that evidence. You are a reader trying to judge something in your feed. checks for AI images that hold up and checking content credentials before you share are written for that position, with no tools to install.
Reading order
The fifteen guides build on each other in this order. Begin with the overview of AI-generated content in social feeds, which sets out what a publisher controls. The next four cover the page you publish: author meta and fediverse:creator tags, marking up a human author with byline schema, disclosure lines that survive a share and share preview integrity: what to check before publishing. The next four cover images: what survives a share of a signed image, the points where WordPress, CDNs and uploads strip metadata, what each platform strips from a shared image and labelling AI-generated images in link previews. Two cover the platforms' side: how platforms decide when to label AI content and invisible watermarks on AI images. The last four are for readers and for the day something goes wrong: checking content credentials, spotting AI images in your feed, can an AI detector judge a social post? and being accused of posting AI content.
What this section does not claim
No detector, watermark or credential is treated here as proof. A detector score is a guess about statistical patterns and the cited studies show it fails on short texts and on non-native writers. An invisible watermark proves at most that one generator marked one file, and is silent about every file it does not mark. A signed credential proves that a file was signed by a key at a time, and stops proving anything the moment a platform re-encodes the image. The guides therefore describe each signal with the conditions under which it holds, show how to add the ones a publisher controls, and leave the judgement to the reader. Where a guide gives a worked example, the numbers are invented and say so.
Questions
What is content provenance?
A record of where a piece of media came from and how it was changed, such as a signed C2PA manifest inside an image file.
Can I prove my article was written by a person?
Not with certainty. You can make a person accountable: a named byline, an author page, author tags, byline schema and a disclosure policy.
Do share plugins handle any of this?
Rarely. Author tags and byline schema usually come from an SEO plugin or theme code; provenance data comes from your image tools.
Which provenance guide should a reader start with?
The overview of AI content in social feeds, then the reading order above. Readers who only want to check one image can go straight to the two guides written for that position.
Hannah Voss, Editor. Checks every guide against a working WordPress install and the networks' current documentation. Last reviewed September 2026.