AI Watermarking and Detection
Understanding statistical watermarking, provenance metadata standards, and third-party detectors, including what they can and cannot establish.
Analogy Mental model
The security thread in a banknote and the machine that checks it. One leaves a trace by construction, the other guesses by measuring how surprising the wording is and how much sentence length varies.
In practice What you actually do
The largest search engine has stated that it does not use detector scores and assesses the content itself. Where detectors earn their place is managing freelance contributors: a two-hundred-dollar commission answered in ten seconds by a free tool is caught immediately.
Where people get burned Pitfalls
For readability, vary rhythm deliberately. Alternating a long sentence with several short ones, adding a first-person account and a specific named example, removes the metronomic quality faster than any list of banned words.
This entry was written in English from the Chinese original, not machine-translated. Read the Chinese version →