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Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination

, and . Working Paper, 9873. National Bureau of Economic Research, (July 2003)

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Bugbears or legitimate threats?: (social) scientists' criticisms of machine learning?. KDD, page 4. ACM, (2014)A Bayesian Framework for Modeling Human Evaluations., , , and . SDM, page 181-189. SIAM, (2015)The Theory is Predictive, but is it Complete?: An Application to Human Perception of Randomness., , and . EC, page 125-126. ACM, (2017)Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination, and . Working Paper, 9873. National Bureau of Economic Research, (July 2003)Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability., and . EC, page 807-808. ACM, (2019)Dissecting Racial Bias in an Algorithm that Guides Health Decisions for 70 Million People., and . FAT, page 89. ACM, (2019)Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function., , and . ICML, OpenReview.net, (2024)Algorithmic Fairness and the Social Welfare Function.. EC, page 1. ACM, (2018)Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4585-4594. PMLR, (2019)Simplicity creates inequity: implications for fairness, stereotypes, and interpretability (invited paper)., and . STOC, page 7. ACM, (2021)