1 minute readReference note
Which factual errors in AI answers should be corrected first?
In brief
Accuracy errors should be prioritized by the decision they can distort, the audience exposed, and their observed recurrence. A false serious allegation, wrong executive identity, or incorrect procurement capability can require faster action than a minor date discrepancy. The framework should make those differences explicit.
Each finding needs the exact claim, factual reference, entity, period, and observed conditions. Severity is a judgment about consequence; recurrence is a count within the sample. They should remain separate so a low-frequency but serious problem is not hidden by an average, and a frequent harmless wording difference is not escalated solely because it is easy to count.
Match the response to the error: correct an owned page, repair a profile, supply a missing public record, or report an unsupported generated statement through the available route. Coordinate the response to serious allegations before amplifying them publicly. Retest the original issue, checking the false claim and its consequential implication. Record the reason for the priority and the specific consequences assessed.