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The AUP prohibits users from scraping any content or data from Synthesia or its Services for the purpose of creating or training AI or machine learning models of any type.
This analysis describes what Synthesia's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology
This provision bars a specific category of data extraction activity that has become a contested area in AI development and intellectual property law, placing contractual restrictions on users who may seek to use platform-generated content as training data for competing or supplementary AI systems.
Interpretive note: The provision does not expressly clarify whether the prohibition extends to user-generated video outputs produced using the platform, or is limited to Synthesia's proprietary content and system data; this ambiguity may affect scope of application.
Under this clause, enterprise users engaged in internal AI development may not use content or data extracted from Synthesia's platform to train, fine-tune, or build AI models, including machine learning and generative models. This restriction applies regardless of whether the scraped content was generated by the user's own account.
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"Scraping any content or data from Synthesia or the Services for the creation or training of AI models or tools, including machine learning models, generative models, deep learning models, and artificial neural networks.Excerpt from Synthesia's Acceptable Use Policy
REGULATORY LANDSCAPE: This provision engages the Computer Fraud and Abuse Act in the US context, where unauthorized scraping of platform data may constitute unauthorized access to protected computers. In the EU, the Database Directive and the EU AI Act's provisions on training data transparency and rights clearance are relevant. Copyright law in the US, EU, and UK may independently govern whether AI-generated outputs are protectable, affecting the scope of the contractual restriction's practical reach. GOVERNANCE EXPOSURE: Medium. The enforceability of anti-scraping clauses has been the subject of ongoing legal proceedings in the US, and courts have reached differing conclusions on whether contractual prohibitions on scraping publicly accessible content are enforceable under the CFAA. The provision is clearly stated as a contractual obligation, but its practical enforceability may depend on jurisdiction and the nature of the scraped content. JURISDICTION FLAGS: EU organizations should assess whether this restriction interacts with the EU AI Act's requirements around documentation of training data sources. US-based enterprise customers with internal AI development programs should assess whether any existing data pipelines involving Synthesia-generated content fall within the scope of this prohibition. CONTRACT AND VENDOR IMPLICATIONS: Enterprise agreements should be reviewed to confirm whether this prohibition applies to all content generated through the platform, including customer-created videos using Synthesia's infrastructure, or only to Synthesia's proprietary content and system data. The provision does not expressly distinguish between Synthesia's proprietary assets and user-generated outputs produced using the platform. COMPLIANCE CONSIDERATIONS: Internal AI development teams and data engineering functions should audit existing content ingestion pipelines for any Synthesia-origin content. Legal teams should seek clarification from Synthesia on the scope of the prohibition as it applies to user-generated video outputs versus platform metadata and system content.
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This provision bars a specific category of data extraction activity that has become a contested area in AI development and intellectual property law, placing contractual restrictions on users who may seek to use platform-generated content as training data for competing or supplementary AI systems.
Under this clause, enterprise users engaged in internal AI development may not use content or data extracted from Synthesia's platform to train, fine-tune, or build AI models, including machine learning and generative models. This restriction applies regardless of whether the scraped content was generated by the user's own account.
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