AI can help threat assessment teams sort risk signals, but someone still has to answer for the call. This piece covers a practical approach: run more than one model and treat their disagreements as findings to examine, not noise to average away
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Plain-language guide to AI governance in threat assessment: log where models disagree, record the assumptions behind each call, name the human who signs off, and set a review date matched to the risk
AI governance for threat assessment: when models disagree, the gap gets logged. Every assumption is written down, a named person owns the final call, and each case gets a follow-up review date that fits it.
Our AI threat assessment workflow flags when models disagree, logs the assumptions behind each call, names the human who makes the final decision, and schedules a follow-up review. Plain process, no black box. *(210 characters
Our AI threat assessment workflow flags when models disagree, logs the assumptions behind each call, names the human who makes the final decision, and schedules a follow-up review. Plain process, no black box. *(210 characters
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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