platform-guideline checked

AI Risk Management Framework

Framework for managing AI risk and trustworthiness, including measurement, monitoring, reliability, validity, transparency, accountability, and risk treatment.

Open source

Pattern Decisions This Source Supports

Pattern Supported decision Required contract Claim note
Confidence / uncertainty display Choose confidence / uncertainty display when users need to judge prediction reliability before acting on AI or automation output. The display names the task, prediction, source of the confidence estimate, calibration scope, and last calibration or update time when available. Supports measured AI reliability, validity, risk management, monitoring, transparency, and accountability.
Dangerous-action review Choose dangerous-action review when the user is about to execute a high-impact action and needs to inspect the exact payload, risk, evidence, and side effects before it leaves the safe preview state. The review is bound to a specific action ID, payload version, target, actor, permission scope, source context, evidence set, and policy trigger. Supports risk identification, measurement, management, monitoring, accountability, transparency, reliability, and risk treatment for AI-supported decisions.

Evidence Role

This source is treated as platform-guideline evidence. Use it to validate the decision rules above, not as a visual style reference.

Publisher: NIST. Last checked: .