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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOpenAI announced on October 5, 2026, that it is beginning a phased rollout of text provenance signals. The plan combines a global, opt-in API feature for select models with planned watermarking of eligible ChatGPT and Codex text output in the European Union. The watermark is an invisible statistical pattern in word choices—not a visible label—and OpenAI says its detector is not definitive proof of who wrote a passage.
What is changing, and who gets it?
The rollout has three separate parts. OpenAI’s October 5 announcement does not give a precise date for each EU account or list every eligible model and account, so the planned product rollout should not be read as already complete or as applying globally by default.
| Audience or product | What OpenAI announced | Availability and limits |
|---|---|---|
| API customers | Text watermarking for select models | Customers worldwide can opt in. OpenAI says it is off by default. |
| ChatGPT and Codex users in the EU | Invisible watermarks on eligible text output | OpenAI plans to add them over the coming weeks. It has not specified the exact timing, full model list, or all eligible accounts. |
| Researchers and expert organizations | Access to an OpenAI text detector | Applications are being accepted, but access is initially limited to approved applicants. |
These are different controls: an API customer’s opt-in setting is not the same thing as the planned EU product rollout, and access to the detector is separately restricted. OpenAI’s Help Center guidance, “EU AI Act: OpenAI Resources and Customer Guidance,” provides further product context.
How OpenAI’s textGrain watermark works
OpenAI calls its method textGrain. As a model generates text, it subtly adjusts the statistical selection of possible words or word pieces. That creates a pattern a detector can look for in the wording itself. OpenAI says the signal is not visible to a reader and does not rely on hidden characters, invisible spaces, or unusual punctuation. Its Help Center article “Provenance signals in OpenAI-generated content” describes the method.
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Because the signal is encoded in word selection, it is not equivalent to a visible “AI-generated” notice attached to a passage. Nor should it be confused with every other provenance system. OpenAI describes a broader, layered approach that includes Content Credentials (C2PA) and invisible watermarks for supported media. Those media signals and the text detector are not one universal verification system: OpenAI describes public verification tools for supported image and audio signals, while text-detector access is initially restricted.
How reliable is the text detector?
The figures below are OpenAI-reported evaluation results from 2026, not independent confirmation or a guarantee for other writing, subjects, or real-world use.
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| OpenAI evaluation | Reported result | Qualification |
|---|---|---|
| Psychology passages | About 80% detection for 200-token passages; about 95% for 400-token passages | OpenAI reported these rates at a target false-positive rate of 1%. It said detection was substantially lower for mathematics, where word choice is less flexible. |
| Edited 400-token passages | About 92% detection before synonym changes; 66% after replacing 10% of words; 17% after replacing 25% | These results come from OpenAI’s evaluation of passages with the specified degree of synonym replacement. |
OpenAI cautions that ideal evaluation performance does not ensure reliable detection in everyday use. Short passages and text with constrained wording are harder to assess, while editing can weaken the signal. False positives and false negatives are possible. OpenAI also reported no meaningful performance difference with and without watermarking across its benchmarks for Astra; that is the company’s benchmark comparison, not an independent study of real-world effects.
What a positive or negative result means
According to OpenAI’s detector guidance, a detected watermark can indicate that an OpenAI system generated or processed some of a passage. It cannot establish how much a person contributed, who used the system, who is responsible for the text, who owns it, or whether its claims are accurate.
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A negative result is inconclusive. A watermark may be absent from detectable text because the passage is too short, has been edited or translated, came from an unsupported model or another provider, or predates watermarking. Neither result is, by itself, an authorship verdict, plagiarism finding, identity check, or fact check. OpenAI’s own announcement describes text watermarking and detection as early technologies with significant limitations.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What Article 50 of the EU AI Act requires
Article 50 separates a provider’s duty to mark generated output from a deployer’s duty to disclose certain AI-generated content to the public. The European Commission’s AI Act Service Desk text for Article 50 sets out the legal obligations; OpenAI’s rollout is one company’s approach to provenance, not the text of the law itself.
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| Who has the duty? | Article 50 requirement | Important qualification |
|---|---|---|
| Providers of systems that generate synthetic audio, images, video, or text | Under Article 50(2), ensure outputs are marked in a machine-readable format and detectable as artificially generated or manipulated. | Technical solutions should be effective, interoperable, robust, and reliable as far as technically feasible, taking account of content-specific limitations, implementation costs, and the state of the art. |
| Deployers publishing AI-generated or manipulated text to inform the public on matters of public interest | Under Article 50(4), disclose that the text was artificially generated or manipulated. | The text-disclosure exception applies where the text has undergone human review or editorial control and a natural or legal person holds editorial responsibility. The law also provides an exception for law-enforcement-authorized use. |
The Commission says Article 50 applies from August 2, 2026. A limited grace period applies only to the provider-side marking and detection duty in Article 50(2): providers of systems placed on the market before that date must comply from December 2, 2026. Content generated before August 2 does not need retroactive labeling, according to the Commission’s Article 50 FAQ and Code of Practice guidance.
The Commission’s Code of Practice is a voluntary way to demonstrate compliance, not a replacement for the statutory obligations. The Commission says signatories can rely on the code’s measures; providers or deployers choosing other means must demonstrate that those measures are adequate.
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