Watermarking Without Standards Is Not AI Governance

Watermarking alone is insufficient for AI accountability: Current watermarking implementations risk becoming "symbolic compliance" rather than genuine oversight tools, meaning companies may deploy them to appear responsible without actually enabling effective content attribution or verification.

There's a dangerous gap between what regulators expect and what technology can deliver: Global governance frameworks increasingly cite watermarking as a solution, but existing technical schemes have significant limitations that policymakers may not fully understand, creating a false sense of security.

Industry incentives work against robust watermarking: The paper identifies that current incentive structures actively discourage companies from deploying watermarking in ways that would be truly auditable and effective, suggesting voluntary adoption alone won't solve the problem.

Three-layer framework is needed for watermarking to work: Technical standards alone are insufficient—effective AI governance requires enforceable requirements, independent audit infrastructure to verify watermarks, and enforcement mechanisms to ensure compliance.

Without independent verification, watermarking undermines broader AI safety efforts: Relying on unverified watermarking as a governance tool could actually harm responsible AI development by creating a false impression that the problem of AI content attribution has been solved.