When an AI system flags someone as a possible threat, the output alone isn't enough to act on. This guide covers a practical governance workflow for threat assessment teams
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**Primary (200-255 characters):** A plain-language guide to governing AI in threat assessment: when models disagree, record why, write down the assumptions behind each call, name the person who makes the final decision
Practical AI governance for threat assessment: log where models disagree, write down each assumption, name the person who makes the final call, and set a follow-up review date before anything ships.
A practical look at governing AI in threat assessment. When two or more models disagree on a risk rating, the disagreement gets logged, not averaged away
Using AI in threat assessment? Keep the process defensible. Compare outputs from several models and treat disagreement as a signal to investigate, not a number to average. Write down every assumption behind a score so reviewers can challenge it later
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Using AI to help assess threats only works if someone can explain the result later. Our approach logs every case where two or more models disagree on a risk rating, instead of averaging the answers away