Research map / Probabilistic and scientific modeling / Treatment effects
Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Assume monotone treatment response | Identifying responder-conditional fairness metrics · Personalized intervention policies | TPR and TNR identifiability | Helped |
| Relax monotone treatment response by allowing anti-responders up to B | Fairness auditing of personalized intervention policies · Unconfounded data | TPR and TNR identification | Helped |
| Use robust ROC and xROC regions instead of point-identified curves | Personalized intervention score rankings · French job training | Disparity visibility | Helped |
| Personalize job training using heterogeneous treatment effect scores | French job training · Nationality and gender groups | TPR disparity | No clear effect |
| Personalize job training using heterogeneous treatment effect scores | French job training · Nationality, gender, and age groups | TNR disparity | Mixed |
| Personalize job training using heterogeneous treatment effect scores | French job training · Age groups | TPR disparity: -0.1 | Hurt |
| Rank individuals by treatment-effect score | French job training · Older responders versus younger non-responders | xAUC ranking error | Hurt |
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