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
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Learn how threat assessment teams use AI with governance: flag where models disagree, record the assumptions behind each call, name the person who decides, and schedule a follow-up review. Review timing is set per case, not by a fixed calendar
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Plain-spoken guide to AI governance in threat assessment: log where models disagree, record the assumptions behind each call, name the human who makes the final decision, and set a follow-up review date that fits the case
Using several AI models to assess threats? Log where they disagree, write down the assumptions behind each call, name the person who makes the final decision, and set a follow-up review date that fits the risk
A practical look at governing AI in threat assessment work. We cover how to run multiple models side by side and treat their disagreements as a signal to investigate, not a tie to break
When AI models disagree on a threat assessment, the disagreement gets logged. Each review records its assumptions, names the human who owns the final call, and schedules a follow-up check. The review interval is set per case, not fixed at 30 days