Risk Management System
Continuous identification, analysis, and mitigation of AI system risks
IMPLEMENTATION: Triple Redundant Coherence Protocol (TRCP)
Total Validations:
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Data Governance
Training, validation, and testing datasets must be relevant and representative
IMPLEMENTATION: Privacy-filtered Contextual Knowledge Graph Base (CKGB)
Record-Keeping
Automatic logging of system operations with 10-year retention
IMPLEMENTATION: Aethelred Chronicle (Immutable Audit Logs)
Total Records:
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Transparency & Information
Users must be informed about AI system capabilities and limitations
IMPLEMENTATION: Constitutional Mirror Framework (AI self-awareness)
Human Oversight
Measures to ensure effective human oversight of high-risk AI systems
IMPLEMENTATION: Auto-escalation on low Îș-scores or high drift
High-Risk Events:
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Accuracy, Robustness & Cybersecurity
High-risk AI systems must achieve appropriate levels of accuracy and security
IMPLEMENTATION: Îșâ„0.60 threshold, TLS 1.3, SOC 2 compliance
Average Îș-Score:
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Quality Management System
Continuous monitoring and improvement of AI system performance
IMPLEMENTATION: Corrective Alignment Loop with automatic retry
Success Rate:
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