testland/fairlearn-fairness
Compute group fairness metrics (selection rate, demographic parity, equalized odds) per sensitive feature with `MetricFrame`, then mitigate disparities using Reductions algorithms (`ExponentiatedGradient` with constraint = `DemographicParity`/`EqualizedOdds`). Wire group-disaggregated assertions into the model-evaluation gate. Use when a model's decisions affect people and a stakeholder, auditor, or regulation (ECOA, GDPR Art. 22, EU AI Act high-risk) requires evidence of per-group outcomes, or when someone reports the model treats a specific group worse.
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tile.json
{
"name": "testland/fairlearn-fairness",
"version": "1.3.4",
"summary": "Compute group fairness metrics (selection rate, demographic parity, equalized odds) per sensitive feature with `MetricFrame`, then mitigate disparities using Reductions algorithms (`ExponentiatedGradient` with constraint = `DemographicParity`/`EqualizedOdds`). Wire group-disaggregated assertions into the model-evaluation gate. Use when a model's decisions affect people and a stakeholder, auditor, or regulation (ECOA, GDPR Art. 22, EU AI Act high-risk) requires evidence of per-group outcomes, or when someone reports the model treats a specific group worse.",
"private": false,
"skills": {
"fairlearn-fairness": {
"path": "SKILL.md"
}
}
}