Practical guide to AI governance in threat assessment: when models disagree, record your assumptions, name the person who makes the final call, and set a follow-up review date that fits each case
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AI governance for threat assessment, in plain terms: where models disagree, which assumptions get written down, who signs off as the human decision-maker, and when the call gets revisited. A 30-day review is common, not universal
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Threat assessment teams using AI need a clear paper trail. This guide covers running multiple models and logging where they disagree, writing down assumptions before scoring, naming the person who makes the final call, and setting a follow-up review date
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Running several AI models on threat assessments? Log where they disagree, record the assumptions behind each call, name the person who makes the final decision, and set a follow-up review date
This piece walks through how a threat assessment team can use AI models without letting them make the call. When two models disagree about a case, the disagreement gets logged rather than averaged away
Threat assessment teams are starting to use AI models to help sort reports, but no single model's output should drive a decision on its own. This piece walks through a governance setup that runs several models side by side and records where they disagree