Pandora's Regret is a closed-form pairwise scoring rule derived from expected optimal search costs that elicits true probabilities and outperforms log loss, accuracy, and F1 at predicting diagnostic costs on MedMNIST models.
InProceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17
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The paper defines five AI system categories for public administration and reports that 55% of 91 recent papers leave the system type underspecified while 31% study one type but motivate with another.
Standard OLS fairness tests for deterministic pricing algorithms use invalid standard errors; corrected estimators reveal that all 34 tested Illinois auto insurers discriminate against minority zip codes.
The Pareto frontier of fair algorithmic decisions consists of deterministic group-specific threshold rules on predicted success probabilities, which can include upper bounds for some fairness metrics and holds independently of model training approach.
A gradient-based algorithm learns feature representations to enable efficient post-hoc fairness-accuracy trade-offs in classification without retraining.
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Prioritization algorithms in public services generate relative disparities among intersectional groups as resources become scarce, intensifying perceptions of inequality.
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