How do you verify and fact-check AI answers?
Isolate each factual claim, cross-check it against an authoritative source, be wary of oddly specific figures, and confirm any dates. A useful first pass is to ask several AI models independently: divergence helps prioritise what to inspect, while shared claims still need source verification when the stakes are material.
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Why do AI answers need checking at all?
Because a model generates the most probable wording, not a guaranteed truth — so it can state something false with the same confidence as something correct. That is true of every model, including the strongest. Verification is about catching the rare confident error before it costs you.
What is the quickest way to spot a likely error?
Cross-model divergence. If five models say one thing and one says another, inspect the outlier and the shared claim rather than deciding by vote. A claim made by only one model is a useful priority for verification, while a repeated claim can still come from shared training data or the same stale premise.
How does Satcove help verify?
It runs six models on your question and shows their agreement and their contradictions in one place, with a score. Instead of fact-checking one answer from scratch, you start from where the models already disagree — the spots most worth your attention.
What's the exact verification protocol?
Four steps, repeatable for any claim that matters: (1) State the claim as one checkable sentence, not the whole answer. (2) Find the primary source — the original filing, the regulation text, the study itself, not a summary of it. (3) Match it against an exact quote and a date; a claim without a locatable quote and date is not yet verified, no matter how confidently it was stated. (4) Record one of two outcomes: a sourced verdict (the exact quote that confirms or contradicts the claim) or "unverified" — and treat unanimity between models as a reason to check more carefully, not less, since a shared blind spot produces the same wrong answer from every model at once.
FAQ
How do I fact-check an AI answer?
Break it into separate factual claims and check each against a reliable source. To find which claims to prioritise, ask several AIs the same question first — the points where they disagree are the ones most likely to be wrong.
Are AI answers reliable?
Any model can be confidently wrong. Comparing independent answers reveals alignment and divergence, but reliability comes from checking the claim against relevant, current sources and applying domain judgment.
What is a fast cross-check method?
Run the same question through several models independently, use divergence to prioritise checks, then verify consequential claims against authoritative sources. A unanimous panel can still repeat the same error.
What does a verified claim actually look like?
Claim stated as one sentence, a primary source named, an exact quote and date from that source, and a verdict: confirmed, contradicted, or unverified if no locatable primary source settles it. Anything short of that is a summary, not a verification.
Can I try this for free?
Yes — Satcove's free plan includes 3 cross-check queries a week on iPhone and the web, no card required.
How do I check if ChatGPT is wrong?
Break the answer into factual claims, compare it with independent AI models, open the cited sources and verify important points against current primary evidence. A confident answer or unanimous panel is not proof of accuracy.
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