Statistical Watermarking for LLM Output: How Token Logit Bias Creates Detectable Signatures
Google has been watermarking Gemini output for every user since October 2024 — 20 million users, no perceptible quality degradation, algorithmically detectable. OpenAI has a working prototype that requires only a few hundred tokens to produce a reliable signal. Anthropic says it's on the roadmap. The EU AI Act's Article 50 mandates machine-readable marking of AI-generated content for covered providers. And yet: a $0.88-per-million-token attack achieves ~100% evasion success against seven recent watermarking schemes simultaneously.
This is the actual state of LLM text watermarking. The gap between what's deployed, what the papers claim, and what adversaries can do is wider than most teams realize — and the engineering decisions you make about watermarking depend heavily on which side of that gap you're standing on.
