CASRAI Dictionary

Tag: code of practice ai act

  • AI Act Code of Practice Timeline: 2026 Compliance Guide

    The AI Act code of practice covering transparency of AI-generated content moved from a draft published 8 May 2026, through a stakeholder consultation that closed 3 June 2026, to a final text published 10 June 2026 — all ahead of 2 August 2026, when Article 50’s transparency obligations become legally binding across the EU. The AI Act code of practice on transparency is a voluntary, European Commission-facilitated compliance tool, distinct from the earlier General-Purpose AI Code of Practice, that helps providers and deployers of generative AI systems meet the marking, detection and labelling duties set out in Regulation (EU) 2024/1689.

    For research offices, publishers and institutional communications teams, this is not an abstract EU process. Article 50 reaches any organisation whose AI-generated text, audio, image or video content reaches people in the EU — including AI-assisted research summaries and funder communications. This guide walks through the timeline as a compliance-planning tool.

    What is the AI Act code of practice on transparency?

    The Code of Practice on Transparency of AI-Generated Content is a non-binding framework drafted by independent experts, generative AI providers, deployer associations, civil society bodies and academics, facilitated by the EU AI Office. It gives organisations a recognised way to demonstrate compliance with Article 50 of the AI Act without waiting for harmonised technical standards to be finalised.

    This is a separate instrument from the General-Purpose AI (GPAI) Code of Practice under Article 56, published in final form on 10 July 2025 and applying to GPAI model providers since 2 August 2025. Confusing the two is a common error in searches for “AI Act code of practice” — the table below sets out the difference.

    Feature GPAI Code of Practice (Article 56) Transparency Code of Practice (Article 50)
    Legal basis Article 56, Regulation (EU) 2024/1689 Article 50, Regulation (EU) 2024/1689
    Audience Providers of general-purpose AI models Providers and deployers of generative AI systems
    Final text published 10 July 2025 10 June 2026
    Obligations apply from 2 August 2025 2 August 2026
    Core focus Safety, copyright, transparency documentation for models Marking, detection and labelling of AI-generated content

    The transparency code is organised around two working groups mirroring Article 50’s structure: Working Group 1 covers providers’ obligations to mark AI-generated audio, image, video and text in a machine-readable, detectable format; Working Group 2 covers deployers’ obligations to label deepfakes and AI-generated text on matters of public interest.

    What changed in the May 2026 draft guidelines?

    On 8 May 2026, the European Commission published draft implementation guidelines on Article 50 alongside the near-final Code of Practice text. These guidelines are the Commission’s own interpretive document — distinct from the stakeholder-drafted Code — clarifying how the transparency obligations apply in practice.

    The May draft addressed several points that had been ambiguous through the drafting rounds that ran from November 2025 to March 2026:

    • How “AI system” is scoped for the purposes of the human-interaction disclosure duty in Article 50(1);
    • The deepfake definition, including where content depicting real persons, places or events would falsely appear authentic;
    • The editorial-responsibility carve-out, under which AI-generated text on matters of public interest need not be labelled if it has undergone human review and is subject to editorial responsibility;
    • Expectations that marking techniques be interoperable, robust and reflect the “generally acknowledged state of the art” rather than a single mandated technology.

    What did the consultation closing 3 June 2026 cover?

    The Commission’s consultation on the May draft guidelines closed on 3 June 2026, giving providers, deployers, standards bodies and civil society a final window to flag practical gaps before the text was locked. In parallel, the multi-stakeholder drafting process for the Code of Practice itself held its closing plenary, and the AI Office published the final Code of Practice on Transparency of AI-Generated Content on 10 June 2026.

    This timing is deliberate: the guidelines interpret what Article 50 legally requires, while the Code offers voluntary methods — marking formats, labelling icons, detection mechanisms — for meeting those requirements. Signing the Code is optional; complying with Article 50 by 2 August 2026 is not.

    What applies from 2 August 2026 — and where is there a grace period?

    From 2 August 2026, Article 50 becomes legally applicable across all EU member states. Providers must ensure outputs of generative AI systems are marked in a machine-readable format detectable as artificially generated or manipulated. Deployers must disclose deepfakes and label AI-generated or manipulated text published on matters of public interest, unless a human has reviewed the content and taken editorial responsibility for it.

    One practical relief applies to systems already in the market. Legal trackers monitoring the rollout report that generative AI systems placed on the market before 2 August 2026 have until 2 December 2026 to retrofit the machine-readable marking requirement under Article 50(2) — a four-month bridge for legacy tooling rather than a change to the core application date.

    How should research offices prepare?

    Research administration, publisher and funder-communications teams should treat 2 August 2026 as a hard planning date, not a distant EU milestone. The obligations bite wherever AI-generated text, images or audio reach an EU audience — including institutional websites, funder newsletters, and AI-assisted drafting workflows.

    • Inventory every generative AI tool used to produce public-facing text, images, audio or video, and confirm whether outputs are already machine-readably marked;
    • Map authorship and editorial-review workflows against the human-review carve-out, so genuinely human-edited content is not mislabelled as AI-generated;
    • Align AI-use disclosure practices in manuscripts and grant narratives with existing publisher policies (for example, ICMJE and COPE guidance on declaring generative AI assistance), since Article 50 labelling and authorship disclosure are converging expectations;
    • Confirm with vendors supplying AI writing, transcription or media tools whether their systems will meet the marking requirement by 2 August 2026 or fall under the 2 December 2026 legacy window;
    • Assign clear internal ownership — communications, legal/compliance, and research integrity offices each hold part of this obligation and need a shared owner before August.

    Answer-first questions on the AI Act code of practice

    What is the EU AI Act code of practice?

    The EU AI Act code of practice on transparency is a voluntary framework, facilitated by the AI Office, that helps providers and deployers of generative AI systems meet Article 50’s marking, detection and labelling duties. It was finalised on 10 June 2026, ahead of the 2 August 2026 application date, and sits alongside a separate GPAI Code of Practice covering model-level obligations under Article 56.

    Is there a UK equivalent to the AI Act code of practice?

    No. The UK has no AI-specific legislation equivalent to the EU AI Act; AI is instead regulated through existing sector frameworks. UK research institutions, publishers and vendors that publish AI-generated content reaching EU audiences, or that operate EU subsidiaries, must still meet Article 50’s transparency obligations from 2 August 2026.

    How does the transparency code relate to the AI Act’s risk categories?

    The AI Act classifies systems into four risk tiers — unacceptable, high, limited and minimal risk. Article 50’s transparency duties sit within the “limited risk” tier and apply horizontally to generative and interactive systems regardless of their risk classification elsewhere, which is why the transparency code applies more broadly than the high-risk rules.

    Implications and outlook

    The 2 August 2026 application date closes a year-long drafting process that began in September 2025 and ran through three formal drafting rounds before the May 2026 draft and June 2026 consultation. For research-adjacent organisations, the practical implication is less about the Code of Practice itself — which remains voluntary — and more about Article 50, which is not. Institutions that already maintain authorship-disclosure and editorial-review workflows for generative AI have a head start.

    Expect further guidance around the 2 December 2026 legacy-marking deadline, and continued convergence between AI Act transparency labelling and research-integrity disclosure norms from bodies such as ICMJE and COPE. Organisations tracking both processes together, rather than as separate compliance tracks, will be better placed for the obligations that follow.

    See CASRAI’s related coverage of research administration compliance workflows and authorship transparency disclosures for how generative AI disclosure expectations intersect with existing research-integrity practice.

  • AI-Generated Content Code of Practice: What It Means for Journals and Preprint Servers

    The AI-Generated Content Code of Practice is the European Commission’s voluntary framework, published 10 June 2026, that helps providers and deployers of generative AI systems meet the labelling and disclosure duties in Article 50 of the EU AI Act. For journals and preprint servers, the Code’s “editorial responsibility” carve-out is the single most consequential clause: it determines whether peer-reviewed articles, preprints, and AI-assisted manuscript text trigger a public AI-disclosure requirement.

    The Code of Practice on Transparency of AI-Generated Content is a non-binding compliance instrument: it is a voluntary set of practical measures that signatories can use as evidence of compliance with the legally binding transparency obligations set out in Article 50 of Regulation (EU) 2024/1689, the EU AI Act.

    What is the AI-Generated Content Code of Practice?

    The Code of Practice on Transparency of AI-Generated Content was closed out at a plenary session on 10 June 2026, following a drafting process that ran from November 2025 through three drafting rounds, the last concluding on 8 May 2026. It was produced by the European Commission’s AI Office through two working groups: one covering obligations for providers of generative AI systems, the other covering obligations for deployers — the organisations that actually publish AI-generated or AI-assisted output.

    Providers must ensure that generated audio, image, video, and text outputs are marked in a machine-readable format detectable as artificial, using layered technical measures such as metadata and watermarking. Deployers must clearly label deepfakes and must disclose AI-generated text on matters of public interest unless that text has undergone human review and is subject to editorial responsibility. That single exemption clause is what makes the Code directly relevant to scholarly publishing.

    Article 50 vs Article 56: two different codes, not one

    Publishers should not confuse this Code with the earlier General-Purpose AI Code of Practice, finalised on 10 July 2025 under Article 56 of the AI Act. That code addresses safety, security, and copyright compliance for developers of foundation models such as GPT- and Gemini-class systems — it is not about labelling published content.

    The June 2026 Code sits under Article 50 instead, and governs transparency obligations that apply from 2 August 2026, when the wider AI Act’s transparency provisions take effect. Confusing the two codes is the most common error in early legal commentary on this development, and it matters for publishers: it is Article 50 — not Article 56 — that determines whether an AI-assisted peer-review report, cover letter, or manuscript summary requires a visible “AI” label.

    What this means for journal editorial workflows

    Peer-reviewed journal articles are the clearest case for the editorial-responsibility exemption. A manuscript that has passed through peer review, editorial decision-making, and copyediting has, by definition, undergone the “human review… subject to editorial responsibility” that Article 50(4) requires to avoid the public-disclosure trigger for AI-generated text.

    This does not remove the underlying disclosure obligation that scholarly publishing already imposes through its own ethics infrastructure. ICMJE’s Recommendations state that AI tools cannot be credited as authors because they cannot take responsibility for the submitted work, and that any generative AI use in manuscript preparation must be disclosed to editors and readers. COPE’s position statement on AI tools reaches the same conclusion: AI cannot be an author, and authors remain fully accountable for content it helped produce. The EU Code’s editorial-responsibility test and the ICMJE/COPE disclosure rule are therefore complementary, not duplicative — a journal that already enforces ICMJE-COPE disclosure norms is well placed to document compliance with the EU Code if it chooses to sign.

    • Editorial policy: confirm the AI-use disclosure clause in author guidelines references generative AI text, not only images or data.
    • Peer review reports: reviewers using AI drafting tools should disclose this to editors, mirroring the deployer disclosure logic in the Code.
    • Editorial metadata: retain records evidencing human review, since this is the documentation that supports the Article 50(4) exemption claim.

    Preprint servers: a narrower exemption path

    Preprints are structurally different. A preprint is, by design, posted before formal peer review and before an editorial board takes responsibility for its content. That means the “editorial responsibility” exemption that shelters a published journal article is much harder for a preprint server to claim at the point of posting.

    Preprint servers such as arXiv, bioRxiv, and medRxiv already run moderation screening, but screening for scope and plagiarism is not the same as the substantive editorial review Article 50(4) contemplates. Where a preprint contains AI-generated text on a matter of public interest — a policy-relevant synthesis, a public-health claim — a strict reading of the Code suggests deployer-side disclosure obligations may apply at the preprint stage, even though the same text would likely be exempt once it clears peer review and is published in a journal. Preprint operators serving EU users should treat this as a genuine compliance gap to close, not an afterthought.

    Content type Human review / editorial responsibility present? Likely Article 50 disclosure trigger
    Peer-reviewed journal article Yes — editorial board, peer review, copyediting Exempt (if AI use is disclosed per ICMJE/COPE norms)
    Preprint (pre-review) Limited — screening only, no substantive editorial review Disclosure obligation more likely to apply
    AI-generated figure or image (deepfake-style) Not applicable — separate deployer rule Labelling required regardless of review stage
    AI-assisted literature-review drafting Depends on subsequent editorial handling Case-by-case; disclose per journal policy

    Answer-first Q&A

    Is the AI-Generated Content Code of Practice mandatory?

    No. The Code of Practice is voluntary; signing it is optional. What is legally binding is Article 50 of the EU AI Act itself, which applies from 2 August 2026. Signing the Code simply gives providers and deployers, including publishers, a recognised route to demonstrate compliance with those binding obligations.

    Does the Code of Practice apply to preprints?

    The Code applies to any deployer publishing AI-generated text on matters of public interest to EU audiences, which can include preprint servers. Because preprints have not undergone substantive editorial review at posting, the editorial-responsibility exemption is harder to claim than for peer-reviewed journal articles, making preprint-stage disclosure more likely to be required.

    Can AI-generated text be listed as an author contribution?

    No. ICMJE and COPE both hold that generative AI tools cannot qualify as authors because they cannot be held accountable for the work or approve the final version. Human authors must disclose AI use and retain full responsibility for accuracy, originality, and integrity of the resulting manuscript text.

    How does this Code differ from the GPAI Code of Practice?

    The GPAI Code of Practice (Article 56, July 2025) governs foundation-model developers’ safety, security, and copyright duties. The AI-Generated Content Code of Practice (Article 50, June 2026) instead governs labelling and disclosure of AI-generated outputs by the organisations that publish them — the code directly relevant to journals and preprint servers.

    Implications and a compliance checklist

    For the publisher segment of CASRAI’s audience, the practical task is narrow but time-sensitive: journals should audit whether their existing ICMJE/COPE-aligned AI-disclosure clauses reference the Code’s editorial-responsibility test, and preprint operators serving EU readers should assess whether pre-review screening is sufficient to avoid a deployer-side disclosure obligation once Article 50 takes effect on 2 August 2026.

    • Map current author-guideline AI-disclosure language against Article 50(4)’s “human review and editorial responsibility” wording.
    • Confirm peer review and editorial sign-off records are retained as exemption evidence.
    • Assess whether preprint-stage moderation constitutes “editorial responsibility” under a plain reading of the Code, or whether additional review is needed.
    • Track AI Office guidance and signatory lists, since the Code’s practical measures may evolve as more publishers sign.

    Institutions coordinating research-integrity policy across editorial offices and research administration functions should treat this as a live compliance item for the second half of 2026, and align it with existing authorship disclosure norms rather than treating it as a separate, parallel rulebook.