AI trust question
When you need an immediate correctness check, start with the claims users will act on first. Accuracy decisions should be claim-based, not tone-based.
To check if an AI answer is correct, break it into actionable claims, verify key claims against trusted sources, and route uncertain output before use.
Extract the concrete instructions, numbers, dates, and policy statements from the answer. Those are the parts that can cause real-world errors.
Prioritize high-impact claims first so review effort maps to risk instead of treating every sentence as equally important.
Verify whether each priority claim has evidence, and confirm that the answer stays aligned with your prompt and context constraints.
If support is missing or context is contradicted, treat the response as untrusted until corrected.
Use allow for well-supported low-risk answers, review for uncertain or partially supported responses, and block for high-impact unsupported claims.
A clear routing rule keeps correctness checks fast and repeatable under production pressure.
The response says workspace deletion is immediate, but the provided policy states a 7-day grace period before permanent removal.
Next step: Block and rewrite the answer directly from the policy text before exposing it to users.
AI response verification means comparing material claims with the approved source of truth and routing unsupported or contradicted output before release.
Block AI output when the response is unsupported and the user impact of being wrong is high.