Is AI training data protected by copyright?

Yes. Copyright attaches automatically at creation under the Berne Convention (Art. 5) in all 181 member countries. Scraping copyrighted works to build a training dataset creates copies of protected material. Whether it constitutes infringement depends on jurisdiction and whether applicable exceptions, such as the EU CDSM Directive Art. 4 TDM exception, apply and have not been opted out of by the rights holder.

Can I use scraped web data to train an AI model?

Only if the source material is explicitly licensed for that purpose or the applicable TDM exception covers it. In the EU, rights holders may opt out of TDM exceptions via machine-readable signals such as robots.txt. In Switzerland, no general TDM exception exists. Scraping for commercial AI training without a licence is legally risky. Always audit your dataset sources and document licensing status before training.

What does the EU AI Act require about training data documentation?

Under EU AI Act Article 53, providers of general-purpose AI models must maintain technical documentation of training data sources, keep a sufficiently detailed public summary, and comply with EU copyright law including TDM opt-outs. For high-capability models above the 10^25 FLOPs threshold, additional adversarial testing and incident-reporting obligations apply. Non-compliance exposes providers to fines up to 3% of global turnover.

How can a cryptographic timestamp prove training data provenance?

A qualified electronic timestamp under eIDAS or ZertES embeds a cryptographic hash of your dataset at a specific point in time, anchored to a trusted time source. This creates an immutable, court-admissible record proving the dataset existed in that exact form on that date. It is the primary technical mechanism for demonstrating legitimate, pre-existing sourcing when rights holders or regulators audit your data pipeline.

Which jurisdictions have the strictest AI training data copyright rules?

The EU has the most comprehensive framework, combining CDSM Directive TDM exceptions with opt-out rights and the EU AI Act documentation requirements. Switzerland has no TDM exception, making unlicensed scraping riskier than in the EU. The US applies fair use analysis, which is less predictable. Japan has the broadest TDM exception, permitting scraping for AI training even of commercial works without opt-out mechanisms.

How do I protect my content from AI scraping under EU law?

Under EU CDSM Directive Article 4(3), rights holders may opt out of text and data mining exceptions by publishing a machine-readable reservation, such as X-Robots-Tag: noai or a robots.txt disallow directive. To prove your content existed before an AI model was trained, obtain a qualified electronic timestamp under eIDAS Article 41(2). A qualified timestamp from a QTSP like Swisscom Trust Services creates a legal presumption of accuracy that is admissible across all 27 EU member states. If an AI model reproduces your timestamped content, the timestamp becomes your primary exhibit in an infringement claim. It cannot be backdated and is cryptographically verifiable.

KI-Trainingsdaten und Urheberrecht: Was Entwickler 2026 wissen müssen

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KI-Trainingsdaten und Urheberrecht: Was Entwickler 2026 wissen müssen

KI-Trainingsdaten unterliegen dem Urheberrecht — aus dem Web gescrapte Inhalte werden nicht automatisch gemeinfrei. Erfahren Sie, was EU-KI-Gesetz-Compliance, Lizenzierung und eIDAS-Zeitstempel für KI-Entwickler im Jahr 2026 bedeuten.

Swiss Trust Layer Editorial Team· Legal Content

·June 12, 2026·Last updated June 12, 2026· 8 Min. Lesen

Im Oktober 2024 schloss ein Berliner KI-Startup eine Series-A-Finanzierungsrunde ab und begann die Due-Diligence-Prüfung mit einem Tier-1-Enterprise-Kunden. Das Rechtsteam des Kunden stellte eine Frage: Wann wurde der jeweilige Datensatz zusammengestellt, und kann das vor dem Opt-out-Compliance-Datum nachgewiesen werden? Der CTO des Startups hatte keinen qualifizierten Zeitstempel auf einem einzigen Datensatz. Zwei Wochen später stockte der Deal. Dieselben Datensatze wurden anschliessend von einem Medienverlag angefochten, dessen robots.txt-Opt-out seit Marz 2024 aktiv war.

Da die Durchsetzung des EU AI Act ab 2026 beginnt, ist die Dokumentation der Datenprovenienz eine gesetzliche Anforderung fur Anbieter von KI-Modellen mit allgemeinem Verwendungszweck. Das Fehlen von Zeitstempeln auf Trainingsdatensatzen ist die bei Regulierungsprufungen am haufigsten festgestellte Lucke.

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