hip-0201

HIP-201: Model Risk Management. Status Draft. Hanzo's own standard — read this before implementing against it.

HIP-0201: Model Risk Management

Abstract

This HIP establishes the Model Risk Management (MRM) framework for Hanzo AI systems. It defines processes for identifying, assessing, monitoring, and mitigating risks throughout the AI model lifecycle, aligned with NIST AI RMF and SR 11-7 principles.

Scope

Covered Models

| Model Type | Risk Tier | MRM Requirements | |------------|-----------|------------------| | Foundation models | High | Full MRM | | Fine-tuned models | Medium-High | Standard MRM | | Customer-deployed models | Varies | Risk-based MRM | | Internal tools | Low | Simplified MRM |

Model Lifecycle Coverage

Design → Development → Validation → Deployment → Monitoring → Retirement
   ↑         ↑            ↑            ↑            ↑            ↑
  MRM       MRM          MRM          MRM          MRM          MRM

Risk Categories

Performance Risk

| Risk | Description | Impact | |------|-------------|--------| | Accuracy degradation | Model performance below thresholds | User harm, business impact | | Distribution shift | Training/production data mismatch | Unreliable outputs | | Capability limitations | Model cannot perform required tasks | Unmet expectations |

Safety Risk

| Risk | Description | Impact | |------|-------------|--------| | Harmful outputs | Generation of dangerous content | User harm, reputation | | Jailbreaking | Circumvention of safety measures | Policy violations | | Misuse potential | Use for malicious purposes | Societal harm |

Fairness Risk

| Risk | Description | Impact | |------|-------------|--------| | Demographic bias | Disparate performance across groups | Discrimination | | Representation bias | Underrepresentation in training data | Exclusion | | Outcome bias | Systematically unfair results | Legal, ethical issues |

Security Risk

| Risk | Description | Impact | |------|-------------|--------| | Adversarial attacks | Manipulated inputs causing errors | Reliability | | Data poisoning | Corrupted training data | Model integrity | | Model theft | Unauthorized model extraction | IP loss | | Privacy leakage | Training data exposure | Data breach |

Operational Risk

| Risk | Description | Impact | |------|-------------|--------| | Availability failures | Model downtime | Service disruption | | Latency issues | Response time degradation | User experience | | Scalability limits | Cannot handle load | Capacity constraints | | Integration failures | API/system incompatibility | Technical debt |

Risk Assessment

Risk Scoring

Likelihood Scale

| Score | Likelihood | Description | |-------|------------|-------------| | 1 | Rare | <5% probability | | 2 | Unlikely | 5-20% probability | | 3 | Possible | 20-50% probability | | 4 | Likely | 50-80% probability | | 5 | Almost certain | >80% probability |

Impact Scale

| Score | Impact | Description | |-------|--------|-------------| | 1 | Minimal | Negligible harm, easily corrected | | 2 | Minor | Limited harm, manageable impact | | 3 | Moderate | Significant harm, notable impact | | 4 | Major | Serious harm, substantial impact | | 5 | Severe | Catastrophic harm, irreversible |

Risk Matrix

| | Minimal | Minor | Moderate | Major | Severe | |--|---------|-------|----------|-------|--------| | Almost certain | Medium | High | High | Critical | Critical | | Likely | Low | Medium | High | High | Critical | | Possible | Low | Medium | Medium | High | High | | Unlikely | Low | Low | Medium | Medium | High | | Rare | Low | Low | Low | Medium | Medium |

Risk Tiering

| Tier | Criteria | Requirements | |------|----------|--------------| | Critical | Life-safety, large-scale harm | Board approval, external review | | High | Significant harm potential | ESG Committee review | | Medium | Moderate harm potential | MRM Team review | | Low | Limited harm potential | Standard processes |

MRM Processes

Pre-Development

Risk Assessment

Before model development:

  1. Define intended use cases
  2. Identify potential misuse scenarios
  3. Assess risk tier
  4. Document risk appetite
  5. Define success criteria

Documentation Requirements

| Document | Contents | |----------|----------| | Model proposal | Use case, architecture, data sources | | Risk assessment | Initial risk identification and scoring | | Validation plan | Testing approach and criteria | | Monitoring plan | Ongoing oversight requirements |

Development Phase

Risk Controls

| Control | Implementation | |---------|----------------| | Data governance | Quality checks, bias audits | | Training safeguards | Alignment techniques, guardrails | | Version control | Model versioning, reproducibility | | Access controls | Role-based development access |

Checkpoints

| Checkpoint | Timing | Requirements | |------------|--------|--------------| | Design review | Before training | Architecture approval | | Data review | Before training | Data quality sign-off | | Training review | During training | Progress monitoring | | Pre-validation | After training | Initial quality check |

Validation Phase

Independent Validation

Requirements:

Validation Scope: | Area | Tests | |------|-------| | Performance | Accuracy, robustness, calibration | | Safety | Red teaming, harm testing | | Fairness | Bias audits, demographic analysis | | Security | Adversarial testing, privacy checks |

Validation Report

Contents:

  1. Methodology description
  2. Test results by category
  3. Identified issues and severity
  4. Recommendations
  5. Approval decision

Deployment Phase

Pre-Deployment Checklist

| Item | Verification | |------|--------------| | ☐ Validation complete | Validation report approved | | ☐ Documentation complete | Model card, API docs | | ☐ Monitoring configured | Dashboards, alerts | | ☐ Rollback plan | Tested rollback procedure | | ☐ Approval obtained | Appropriate sign-off |

Staged Rollout

| Stage | Exposure | Duration | Exit Criteria | |-------|----------|----------|---------------| | Alpha | Internal only | 1 week | No critical issues | | Beta | 1% traffic | 1 week | Metrics stable | | Gradual | 10% → 50% → 100% | 2 weeks | Full monitoring |

Monitoring Phase

Continuous Monitoring

| Metric | Frequency | Threshold | |--------|-----------|-----------| | Performance | Real-time | <X% degradation | | Safety | Daily | <Y incidents | | Fairness | Weekly | <Z% disparity | | Availability | Real-time | >99.9% uptime |

Periodic Review

| Review | Frequency | Scope | |--------|-----------|-------| | Performance review | Monthly | Metrics, trends | | Risk review | Quarterly | Risk reassessment | | Full validation | Annual | Comprehensive revalidation |

Retirement Phase

Retirement Triggers

Retirement Process

  1. Notification to stakeholders
  2. Migration plan for users
  3. Grace period (typically 90 days)
  4. Archive model and documentation
  5. Update model inventory

Governance

MRM Organization

| Role | Responsibility | |------|----------------| | MRM Team | Day-to-day risk management | | Model Validators | Independent validation | | AI Safety Team | Safety-specific risks | | ESG Committee | Oversight, policy |

Approval Authority

| Risk Tier | Approver | |-----------|----------| | Critical | Board | | High | ESG Committee | | Medium | MRM Lead | | Low | Team Lead |

Model Inventory

Maintain comprehensive inventory:

Documentation Standards

Model Card (Required)

| Section | Contents | |---------|----------| | Model details | Architecture, training data | | Intended use | Use cases, out-of-scope uses | | Performance | Metrics, benchmarks | | Limitations | Known limitations, risks | | Ethical considerations | Bias, fairness, safety |

Risk Register

For each model:

Audit Trail

Maintain records of:

Related HIPs

Changelog

| Version | Date | Changes | |---------|------|---------| | 1.0 | 2025-12-17 | Initial draft |

Copyright

Copyright and related rights waived via CC0.