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Practical AI governance for threat assessment: when models disagree, document the assumptions behind each call, name the human who makes the final decision, and set a follow-up review that fits the case, not a fixed 30 days

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Learn how AI-assisted threat assessment teams can log where their models disagree, record the assumptions behind each call, name the person who makes the final decision, and set a follow-up review date for each case

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Practical AI governance for threat assessment: when models disagree, the disagreement gets logged. Assumptions are written down, a named person owns the final call, and a follow-up review is scheduled before anyone acts on the output.

This guide covers how to handle disagreement between AI models in threat assessments. Record the assumptions behind each assessment, name the person who makes the final call, and schedule a follow-up review

A practical guide to governing AI tools used in threat assessment. Learn how teams handle it when two models disagree on a risk rating, why each working assumption needs to be written down before a decision is made, and how to name who owns the final call