Lesson Summary

This lesson introduces a practical decision framework—the 2×2 Trust Calibration Matrix—that maps every AI output to the right verification depth based on stakes (impact if wrong) and reversibility (how hard to undo). High-stakes, hard-to-undo outputs like policy training or legal guidance demand full audits and SME sign-off, while low-stakes, easy-to-correct drafts need only light review. You'll use this model in the lab to categorize claims and allocate your verification effort efficiently, ensuring you protect against real risk without wasting time over-verifying trivial content.