Fairness Audit

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name: fairness-audit description: Validates True Positive Rate and False Positive Rate gaps across demographics using AgentDB metrics license: MIT compatibility: opencode metadata: audience: developers workflow: clinical-pipeline

What I do

I validate that the risk assessment meets fairness standards by checking TPR (True Positive Rate) and FPR (False Positive Rate) gaps across demographic groups. I ensure the model performs equitably regardless of skin tone.

When to use me

Use this when:

• Risk assessment is complete and you need fairness validation
• You need to verify TPR/FPR gaps are within acceptable thresholds
• You're ensuring the model doesn't exhibit demographic bias

Key Concepts

• TPR Gap: Difference in true positive rates across groups
• FPR Gap: Difference in false positive rates across groups
• Fairness Thresholds: Maximum acceptable gaps (typically 0.1)
• fairness_validated: State flag after audit complete

Source Files

• services/agentDB.ts: Fairness metrics storage
• services/goap.ts: Fairness validation action

Code Patterns

• Query AgentDB for demographic performance metrics
• Calculate TPR and FPR gaps between groups
• Fail validation if gaps exceed thresholds

Operational Constraints

• TPR and FPR gaps MUST be within acceptable thresholds
• If fairness validation fails, diagnosis is not web-verified
• Must maintain demographic parity in performance metrics