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title: "Model QA Specialist"
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type: entity
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tags: [agent, the-agency, ml-ops, model-audit]
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last_updated: 2026-04-20
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---
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## Aliases
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- Model QA Specialist
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## Summary
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独立模型审计专家智能体,对机器学习和统计模型进行端到端质量评估。核心原则是将每个模型视为" guilty until proven sound"(在证明合理之前都是有罪的)。
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## Core Mission
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对 ML 和统计模型执行 10 阶段审计流程,覆盖文档治理、数据重建、特征分析、模型复制、校准测试、可解释性分析和公平性审计。
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## Key Characteristics
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- **Role**:独立审计者,不审计自建模型
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- **Personality**:怀疑但协作,用证据而非意见说话
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- **Domain Expertise**:金融、医疗、电商、广告、保险、制造等行业
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## 10-Stage Audit Process
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1. 文档与治理审查
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2. 数据重建与质量
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3. 目标/标签分析
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4. 分段与队列评估
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5. 特征分析与工程
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6. 模型复制与构建
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7. 校准测试
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8. 性能与监控
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9. 可解释性与公平性
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10. 业务影响与沟通
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## Technical Deliverables
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- Population Stability Index(PSI)计算
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- Discrimination Metrics(Gini、KS、AUC)
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- Hosmer-Lemeshow 校准检验
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- SHAP 全局/局部解释分析
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- Partial Dependence Plots(PDP)
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- Fairness Audit 报告
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## Connections
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- 属于:[[The Agency]]
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- 使用技术:[[SHAP Analysis]]、[[Population Stability Index (PSI)]]、[[Calibration Testing]]
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- 应用领域:[[ML Ops]]
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- 审计对象:[[Responsible AI]]
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## Evidence Standard
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每个发现必须包含:
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1. 观察(Observation)
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2. 证据(Evidence)
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3. 影响评估(Impact Assessment)
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4. 建议(Recommendation)
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严重程度分级:High / Medium / Low / Info
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