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A practical look at governing AI in threat assessment work. When several models disagree on a risk rating, the disagreement gets logged rather than averaged away. Every assumption behind a score is written down where a reviewer can challenge it
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A plain-language look at AI governance for threat assessment: when models disagree, record the assumptions behind each call, name the person who makes the final decision, and set a follow-up review date that fits the case. *(224 characters
A practical guide to governing AI in threat assessment: log where models disagree, write down every assumption, name the person who makes the final call, and schedule a follow-up review on a set date
This guide covers how to handle disagreement between AI models in threat assessments. Record the assumptions behind each assessment, name the person who makes the final call, and schedule a follow-up review
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**Short description (under 255 characters):** Running several AI models on threat assessments? Log where they disagree, write down the assumptions behind each call, name the person who makes the final decision, and set a dated follow-up review
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AI can flag threats faster, but it shouldn't decide alone. Learn how to compare outputs across multiple models, record the assumptions behind each call, name the person accountable for the outcome, and set a follow-up review that fits your risk.