AI Text Watermarking Is Free And Good

Scott Aaronson, while working at OpenAI, largely solved AI text watermarking together with Hendrik Kirchner. Here is how his solution works, or see Tenobrus’s version. AI outputs are not deterministic. The AI’s job is to pick the probability of each potential next token. The token is then chosen at random. By default you use a source of pseudo-randomness for each choice, since actual true randomness is annoying. To apply the watermark, you use an otherwise identical private source of pseudo-randomness derived from a secret key. Then, given enough text, a score is derived for howe well the choices fit with that particular pseudo-randomness source, versus a different source. You provide an API that lets anyone check for the watermark. If you want to dig deeper, here is a full paper. The method has very nice properties: This has no practical impact on outputs. Humans cannot tell the difference, at all. The marginal cost of doing this is very close to zero. The watermark can be removed by…