NIST AI Risk Management Framework
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  • NIST AI Risk Management Framework
  • GRN 1: Risk Management Documentation
    • GRN 1.1 - AI Legal and Regulatory Requirements
    • GRN 1.2 - Trustworthy AI Characteristics
    • GRN 1.3 - Transparent Risk Management
    • GRN 1.4 - Risk Management Monitoring
  • GRN 2: AI Organisation Structure
    • GRN 2.1 - Roles and Responsibilities
    • GRN 2.2 - AI Risk Management Training
    • GRN 2.3 - Executive Responsibility
  • GRN 3: AI Internal Stakeholders
    • GRN 3.1 - AI Risk Decisions Making
  • GRN 4: Organisational Commitments
    • GRN 4.1 - AI Risk Organisational Practices
    • GRN 4.2 - AI Organisational Documentation
    • GRN 4.3 - Organisational Information Sharing Mechnism
  • GRN 5: Stakeholder Engagement
    • GRN 5.1 - External Stakeholder Policies
    • GRN 5.2 - Stakeholder Feedback Integration
  • GRN 6: Managing 3rd-Party Risk
    • GRN 6.1 - 3rd Party Risk Policies
    • GRN 6.2 - 3rd Party Contingency
  • MAP 1: AI Application Context
    • MAP 1.1 - Intended Purpose of AI Use
    • MAP 1.2 - Inter-disciplinary AI Stakeholders
    • MAP 1.3 - AI's Business Value
    • MAP 1.4 - Organisations AI Mission
    • MAP 1.5 - Organisations Risk Tolerance
    • MAP 1.6 - Stakeholder Engagements
    • MAP 1.7 - AI System Requirements
  • MAP 2: AI Application Classification
    • MAP 2.1 - AI Classification
    • MAP 2.2 - AI Usage by Humans
    • MAP 2.3 - TEVV Documentation
  • MAP 3: AI Benefits and Costs
    • MAP 3.1 - AI System Benefits
    • MAP 3.2 - AI Potential Costs
    • MAP 3.3 - AI Application Scope
  • MAP 4: 3rd-Party Risks and Benefits
    • MAP 4.1 - Mapping 3rd-Party Risk
    • MAP 4.2 - Internal Risk Controls for 3rd Party Risk
  • MAP 5: AI Impacts
    • MAP 5.1 - AI Positive or Negative Impacts
    • MAP 5.2 - Likelihood and Magnitude of Each Impact
    • MAP 5.3 - Benefits vs Impacts
  • MRE 1: Appropriate Methods and Metrics
    • MRE 1.1 - Approaches and Metrics
    • MRE 1.2 - Metrics Appropriateness and Effectiveness
    • MRE 1.3 - Stakeholder Assessment Consultation
  • MRE 2: Trustworthy Evaluation
    • MRE 2.1 - Tools for TEVV
    • MRE 2.2 - Evaluations of Human Subjects
    • MRE 2.3 - System Performance
    • MRE 2.4 - Deployment Valid and Reliable
    • MRE 2.5 - Regular Evaluation of AI Systems
    • MRE 2.6 - Evaluation of Computational Bias
    • MRE 2.7 - Evaluation of Security and Resilience
    • MRE 2.8 - Evaluation of AI Models
    • MRE 2.9 - Evaluation of AI Privacy Risks
    • MRE 2.10 - Environmental Impact
  • MRE 3: Risk Tracking Mechanism
    • MRE 3.1 - Risk Tracking and Management
    • MRE 3.2 - Risk Tracking Assessments
  • MRE 4: Measurement Feedback
    • MRE 4.1 - Measurement Approaches for Identifying Risk
    • MRE 4.2 - Measurement Approaches for Trustworthiness
    • MRE 4.3 - Measurable Performance Improvements
  • MGE 1: Managing AI Risk
    • MGE 1.1 - Development and Deployment Decision
    • MGE 1.2 - Risk Mitigation Activities
    • MGE 1.3 - Risk Management of Mapped Risks
  • MGE 2: Managing AI Benefits and Impacts
    • MGE 2.1 - Allocated Resources for Risk Management
    • MGE 2.2 - Sustained Value Mechanism
    • MGE 2.3 - AI Deactivation Mechanism
  • MGE 3: Managing 3rd-Party Risk
    • MGE 3.1 - 3rd Party Risk are Managed
  • MGE 4: Reporting Risk Management
    • MGE 4.1 - Post-Deployment Risk Management
    • MGE 4.2 - Measurable Continuous Improvements
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  1. MRE 4: Measurement Feedback

MRE 4.2 - Measurement Approaches for Trustworthiness

Measurement results regarding system trustworthiness in deployment context(s) are informed by domain expert and other stakeholder feedback to validate whether the system is performing consistently as intended. Results are documented.

NIST AI RMF (in the playbook companion) has not defined MRE 4.2; however, Seclea Platform defines the relevant checks to this control requiring:

  • Detailed documentation of the organisation's trustworthiness measurement approaches.

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Last updated 2 years ago