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Verify AI Output: Treat Answers as Checkable Drafts

Verification separates supported claims, interpretations, and unknowns. It covers omissions, logic, and scope as well as obvious mistakes.

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Created: Oct 19, 2026Updated: Oct 19, 2026

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Verification separates supported claims, interpretations, and unknowns. It covers omissions, logic, and scope as well as obvious mistakes.

Use a three-column check

For each important claim, record its wording, evidence location, and your judgment: supported, partly supported, or unconfirmed. A second explanation generated by the model is not independent evidence.

Check high-impact details first

Prioritize names, dates, numbers, quotations, and instructions. For important decisions, consult suitable professional or primary sources. Open cited links and check that the pages actually support the claim.

Look for common failure patterns

Watch for examples presented as universal rules, correlation presented as causation, missing information presented as certainty, and constraints dropped from the source. Asking a model to mark uncertainty can help, but it does not replace your own checks.

Try it

Generate five summary points from familiar material. Locate evidence for each and remove one unsupported statement. You are done when every retained claim is traceable and every unresolved point is marked clearly.

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参考 / Source: OpenAI — Why language models hallucinate