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AIMA
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BSIMM 15
CIS Critical Security Controls
Cloud Controls Matrix
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DSOMM
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OpenSAMM1.5
SAMM
Secure Controls Framework
Responsible AI Principles
Ethical and Societal Impact
Transparency and Explainability
Fairness and Bias
Governance
Strategy and Metrics
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Education and Awareness
Data Management
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Design
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Implementation
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Defect Management
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Operational Management
I-DM-A: Stream A
I-DM-B: Stream B
Maturity Level 1
Maturity Level 2
Maturity Level 3
I-DM-B-1
I-DM-B-1: Are technical methods consistently applied and regularly reviewed to manage defects?
User Feedback Monitoring:
Deploy basic systems to capture user-reported issues.
Regression Testing:
Perform regression tests after model updates.
Alerting for Failures:
Create simple alerting for obvious or repeated model errors.
0
1
2
3
Description
User Feedback Monitoring:
Deploy basic systems to capture user-reported issues.
Regression Testing:
Perform regression tests after model updates.
Alerting for Failures:
Create simple alerting for obvious or repeated model errors.
I-DM-B-2
I-DM-B-2: Are defect tracking processes fully integrated, proactively managed, and continuously refined?
Advanced Testing:
Implement targeted tests for edge cases, fairness, and bias.
Scheduled Reevaluation:
Routinely test model behavior in varied deployment contexts.
Controlled Experiments:
Use A/B testing to validate model improvements.
0
1
2
3
Description
Advanced Testing:
Implement targeted tests for edge cases, fairness, and bias.
Scheduled Reevaluation:
Routinely test model behavior in varied deployment contexts.
Controlled Experiments:
Use A/B testing to validate model improvements.
I-DM-B-3
I-DM-B-3: Are advanced technical controls fully embedded and continuously enhanced in defect management?
Automated Pipelines:
Deploy retraining and rollback pipelines for rapid response.
Real-Time Monitoring:
Implement anomaly detection for live model performance.
Closed-Loop Learning:
Enable self-correcting systems that learn from defect signals.
0
1
2
3
Description
Automated Pipelines:
Deploy retraining and rollback pipelines for rapid response.
Real-Time Monitoring:
Implement anomaly detection for live model performance.
Closed-Loop Learning:
Enable self-correcting systems that learn from defect signals.