A practical look at governing AI in threat assessment work. When two models disagree on a risk rating, the disagreement gets logged instead of averaged away. Each assumption behind a finding is written down so a reviewer can challenge it later
Threat assessment teams using AI need a paper trail. This guide covers logging where models disagree, recording the assumptions behind each call, naming the person who signs off, and setting a dated follow-up review
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
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
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