--- hip: 201 title: Model Risk Management tags: [ai-ethics, risk, governance, compliance] description: Framework for managing risks associated with AI model development and deployment. author: Hanzo AI Team (@hanzoai) discussions-to: https://github.com/hanzoai/hips/discussions status: Draft type: Meta created: 2025-12-17 requires: [200] --- # 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 team independent from development - Documented test methodology - Representative test data - Clear pass/fail criteria **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 | 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 - Performance below acceptable thresholds - Superseded by better model - Unmitigable risk identified - Business decision #### 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: - Model identifier and version - Risk tier and assessment - Deployment status - Validation status - Owner and contacts ## 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: - Identified risks - Risk scores (likelihood × impact) - Control measures - Residual risk - Risk owner ### Audit Trail Maintain records of: - All risk assessments - Validation results - Approval decisions - Incidents and responses - Changes and rationale ## Related HIPs - **HIP-200**: Responsible AI Principles - **HIP-210**: Safety Evaluation Framework - **HIP-220**: Bias Detection & Mitigation - **HIP-230**: AI Transparency & Explainability - **HIP-240**: AI Incident Response - **HIP-250**: Sustainability Standards Alignment ## Changelog | Version | Date | Changes | |---------|------|---------| | 1.0 | 2025-12-17 | Initial draft | ## Copyright Copyright and related rights waived via [CC0](https://creativecommons.org/publicdomain/zero/1.0/).