Can Europe watermark AI? What the AI Act really asks for
Europe's AI Act says makers of general-purpose AI must mark and detect AI-generated content - and those marks must be reliable, interoperable, effective, and robust. But what does that mean in practice?
A new paper by Thomas Souverain maps today's watermarking tech for large language models (LLMs) to the law's demands.
- Clear taxonomy: Classifies watermarking by when it's applied: before/during/after training, and at next-token distribution vs. sampling.
- Evaluation guide: Translates the Act's criteria into tests for robustness, detectability, and model quality; proposes three dimensions to assess interoperability.
- Reality check: No current method meets all four standards; promising direction is watermarking embedded deep in model architecture.
Why it matters: Policymakers, developers, and auditors get a shared language and test plan to judge watermarking claims under the EU AI Act.
Paper: http://arxiv.org/abs/2511.03641v1
Paper: http://arxiv.org/abs/2511.03641v1
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