When AI models disagree on a threat assessment, that gap is worth examining. Our approach logs each model's reasoning, documents the assumptions behind each call, names the person who makes the final decision, and sets a follow-up review date
Learn how threat assessment teams use AI governance: compare outputs when models disagree, record the assumptions behind each call, name the person who makes the final decision, and set a follow-up review on a date fixed for each case
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
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.
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