The AIast Disclosure Standard
Where a credential buys trust in advance,
transparency can earn it afterward.
Earned Trust is a disclosure standard for AI-assisted work. Its instrument is the AIast mark — a compact, checkable record of which AI services were used, what each did, and how the work was checked — backed by an evidence commitment: the working records are retained and producible on request.
Three letters of roles — i ideation · d drafting · c critique · v verification · s source retrieval — and a count of the services used. Not a score. Not a confession. A credit roll: every record and every film ships with credits naming who did what. This is that, for thinking work.
The full specification — the mark, the threshold, the evidence package, conformance, failure modes, and its limits. Openly licensed, permanently archived, version-controlled.
Read on Zenodo →Everything an author needs: a protocol you paste into any AI so it holds you to the method, the evidence-folder scaffold, a session manifest that updates as you work, and a sealing tool that makes your records tamper-evident with published fingerprints. Free, offline, no accounts.
Get the kit →Drop a file, get its fingerprint, compare it against what was published. Runs entirely in your browser — nothing is uploaded, ever. Verification is free forever, because trust you must pay to verify is not earned trust.
Open the reader →Institutional credentials work as pre-paid trust: a reader extends the benefit of the doubt because an institution already vouched for the author. People without credentials have had no comparable way to earn a hearing. Earned Trust proposes the alternative: make exactly how a work was produced open to inspection — what the AI did, what the human directed and checked, and the records to prove it. It offers a hearing, not a verdict; checkability, not a warm reception. The work still has to survive scrutiny. The point is that it finally gets some.