AI-Generated Content Labeling in the EU: What Article 50 Requires
AI-generated content labeling under the EU AI Act sounds like a simple rule — say it's AI-made — until a team actually tries to implement it consistently across every image, article, and clip they publish. Article 50 covers two related but distinct duties here: marking synthetic content in a machine-readable way (Article 50(2)), and visibly labeling AI-generated text published to the public (Article 50(4)). Most non-compliant content isn't the result of anyone deciding not to label something — it's what a missed caption looks like at scale.
Two separate requirements, often confused
Article 50(2) — machine-readable marking
Synthetic text, image, audio, or video output has to be marked so software — not just a human reading the page — can detect it was AI-generated. A visible label alone doesn't satisfy this; the marking has to be technically embedded in the content.
Article 50(4) — visible labeling of published text
AI-generated text published to inform the public on matters of public interest needs a human-visible label, unless a person took substantive editorial responsibility for it. This one is about what a reader sees, not just what a machine can detect.
Why a caption isn't a labeling system
The two requirements above need different implementations, because images and text don't behave the same way once they leave your system:
- An image gets downloaded, reposted, and screenshotted constantly. A caption on the page around it doesn't survive any of that. The only label that travels with an image is one baked directly into the pixels — a real watermark, not an overlay a crop can remove.
- Text can't be marked the same way without mangling the actual words, which defeats the point of publishing it. What works instead is a positioned badge generated alongside the content at creation time, so there's no separate manual step someone has to remember.
The exemption is narrower than it sounds
“Substantive editorial review” is doing a lot of work in Article 50(4)'s exemption for human-reviewed text. A quick skim or a spell-check pass is not what the exemption describes — it's meant for cases where a person genuinely took editorial responsibility for the content, and that responsibility should be something you can point to, not something assumed by default because a human technically opened the document once.
How Disclarion labels content by default
Disclarion's SDK returns a ready-made label the moment content is logged, rather than treating labeling as a separate step: a real watermark pixel-baked into images, and a positioned HTML badge for text, both produced by the same call that records the interaction for audit purposes. Neither requires designing anything or remembering to add it at publish time — the label is a byproduct of generating the content, not an afterthought bolted on before it ships.
Frequently asked questions
Does every piece of AI-generated content need a label?
Published AI-generated text needs a label unless a human took substantive editorial responsibility for it — a spell-check or quick skim doesn't qualify for that exemption. AI-generated images, audio, and video that are synthetic or manipulated (deepfakes) need to be marked regardless.
Is a caption under an image enough?
Not on its own. A caption only exists as long as the surrounding page does — the moment the image is downloaded, reposted, or screenshotted, the caption is gone. The label has to travel with the file itself.
What does 'machine-readable' marking actually mean?
It means the AI origin has to be technically detectable by software, not just visible to a human eye scanning the page. A watermark embedded in an image's pixel data satisfies this; a caption in the surrounding HTML does not.
Do all content types get labeled the same way?
No. Images need a marking baked into the file itself, since files travel independently of any page. Text can't be marked without altering the words, so it needs a positioned badge shown alongside the content instead.