G-SM-B-1: Are defined metrics regularly reviewed and communicated within the organization?
No Formal Metrics: AI security and RAI outcomes (e.g., incident counts, bias incidents, model validation) are not measured or measured informally.
Incident-Driven Insights: Data is gathered primarily after security or ethical incidents with no routine analysis.
Lack of Standardization: Reporting varies widely, making organization-wide comparisons difficult.
Description
No Formal Metrics: AI security and RAI outcomes (e.g., incident counts, bias incidents, model validation) are not measured or measured informally.
Incident-Driven Insights: Data is gathered primarily after security or ethical incidents with no routine analysis.
Lack of Standardization: Reporting varies widely, making organization-wide comparisons difficult.
G-SM-B-2
G-SM-B-2: Is the AI strategy integrated into the organization's broader business strategy and continuously improved?
Established Metric Set: KPIs/KRIs (e.g., fairness metrics, model risk classification, explainability standards) tracked over time.
Regular Collection and Reporting: Metrics gathered at intervals and shared with stakeholders through dashboards/reports.
Action-Oriented Insights: Metrics drive resource allocation, ethical policies, fairness improvements, and actions for regulatory compliance.
Description
Established Metric Set: KPIs/KRIs (e.g., fairness metrics, model risk classification, explainability standards) tracked over time.
Regular Collection and Reporting: Metrics gathered at intervals and shared with stakeholders through dashboards/reports.
Action-Oriented Insights: Metrics drive resource allocation, ethical policies, fairness improvements, and actions for regulatory compliance.
G-SM-B-3
G-SM-B-3: Are metrics systematically analyzed to drive improvements and decision-making processes?
Advanced Analytics and Monitoring: Real-time monitoring of AI systems (data drift, adversarial attack detection, bias detection), automated alerts, and comprehensive audit trails.
Culture of Data-Driven and Ethical Governance: Metrics feed strategic decision-making; clear processes for continuous feedback, fairness enhancements, transparency improvements, and regulatory compliance.
Description
Advanced Analytics and Monitoring: Real-time monitoring of AI systems (data drift, adversarial attack detection, bias detection), automated alerts, and comprehensive audit trails.