GoKawiilHow AI text watermarking works .
A gentle, visual walk through how a statistical mark hides inside generated text, and what erases it.
A watermark in plain text sounds impossible. Text has no pixels to hide data in, and no metadata survives copy-and-paste; every character is right there in front of you. Where could a mark possibly go?
And yet the marks are real. Google has watermarked text from the Gemini app and web experience since 2024 (its API is, at the time of writing, a documented exception), and as of August 2026, new Claude models mark text at the model level, with earlier models being brought in behind them. They're invisible, they survive copying, and they work because they don't live in the characters at all. They live in the choices between them.
Five short steps, each with something to poke at. Nothing harder than counting.
Writing is a series of small choices A secret key leans on those choices Whoever holds the key can count What editing does to the mark What this means in practice
1. Writing is a series of small choices
The one idea in this step: a model writes by rolling weighted dice between several words that would each be fine.
When a model is mid-sentence, it doesn't know "the next word." It has a shortlist, like autocomplete, with preferences. Here's a real kind of moment, one word from the end of a sentence:
the sentence being written The results of the study were quite 🎲 roll the dice 🎲 roll ×20 Each roll sweeps the shortlist, lands on one word (odds matching the bars) and drops it into the sentence above. The dots tally where the rolls land: try ×20 and watch the pile take the shape of the odds. Notice what never changes: every landing makes a perfectly good sentence.
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