Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy

Research article (arXiv (Cornell University), 2020) · cited 89× · AI/ML
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Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy

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Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy. Retrieved May 24, 2026, from https://4ort.xyz/entity/empirical-observation-of-negligible-fairness-accuracy-trade-offs-in-machine-learning-for-public-policy
MLA “Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/empirical-observation-of-negligible-fairness-accuracy-trade-offs-in-machine-learning-for-public-policy.
BibTeX @misc{4ortxyz_empirical-observation-of-negligible-fairness-accuracy-trade-offs-in-machine-learning-for-public-policy_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy}}, year = {2026}, url = {https://4ort.xyz/entity/empirical-observation-of-negligible-fairness-accuracy-trade-offs-in-machine-learning-for-public-policy}, note = {Accessed: 2026-05-24}}
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