Цю сторінку ще не перекладено українською. Нижче — англійський оригінал; усі показники й дати однакові в обох мовах.
Mission
To make it measurable — and therefore fixable — when AI systems repeat state disinformation to the people who trust them.
The gap we exist to close
Fact-checking was built for a world of posts and articles: things with a URL, a timestamp, a share count and a moderator. A chatbot answer has none of that. It is generated once, for one person, and it disappears. If a model repeats a Kremlin fabrication to a voter in Germany at nine in the evening, there is no artefact to check, no platform report to file, and no record that it happened.
We create that record.
What we are trying to change
- Make it visible. A permanent, public, machine-readable page for every documented claim an assistant has repeated.
- Make it addressable. Findings go to the platform that can fix them, and to the registrars and hosts that carry the source.
- Make it accountable. We re-measure and publish the change — including when nothing changed.
- Make it reusable. Open data, an open method, and no requirement to trust us over the numbers.
Why from Ukraine
Ukraine is where these narratives are aimed first and tested hardest, and where the ground truth is closest to hand. That is an unusual observation post, and we think it produces better data than the same work would produce anywhere else. It also means we are not neutral about the harm — but we are strict about the method, because a finding that does not survive scrutiny is worth nothing to anyone.
What success looks like
Not a headline. A repeat-rate that falls and stays down, on claims we can name, on assistants we can name, verified by a measurement anyone can reproduce.