AI misinformation risk checklist
AI writes fluently, which is exactly what makes its mistakes dangerous — a confident, well-structured paragraph can contain an invented statistic, a fake citation, or a fact that was true two years ago and isn’t now. This checklist forces the verification steps people skip when content “looks finished,” and gives you a clear risk level before you hit publish.
How it works
You choose the publication channel, because the stakes scale the bar — a social post and a health-advice article are not held to the same standard. Then you work through twelve checks grouped into five areas: factual claims, currency, citations, framing, and accountability. Critical checks (verifying claims, checking stats and quotes, removing hallucinated citations) are weighted heavily. The tool computes a weighted score, applies a stricter threshold for high-stakes channels, and — crucially — blocks a “low risk” verdict if any critical step is still incomplete, listing exactly what to finish first.
Tips and notes
- Open every citation. The single highest-yield check: confirm the source exists and actually says what the text claims.
- Mind the cutoff. For anything recent — prices, laws, leaders, software versions — the model may be confidently out of date.
- Watch the framing, not just the facts. Cherry-picked true facts can still mislead. Check for false balance and implied causation.
- Human sign-off for high stakes. Health, legal, financial, and news content should clear this checklist and get qualified human review.