11 research outputs found

    More Intelligent Design: Testing Measures of Merit

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    Liberty Bound: Obergefell\u27s Eclipse of Power to Limit Sexual Autonomy

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    50 Years of Test (Un)fairness: Lessons for Machine Learning

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    Quantitative definitions of what is unfair and what is fair have been introduced in multiple disciplines for well over 50 years, including in education, hiring, and machine learning. We trace how the notion of fairness has been defined within the testing communities of education and hiring over the past half century, exploring the cultural and social context in which different fairness definitions have emerged. In some cases, earlier definitions of fairness are similar or identical to definitions of fairness in current machine learning research, and foreshadow current formal work. In other cases, insights into what fairness means and how to measure it have largely gone overlooked. We compare past and current notions of fairness along several dimensions, including the fairness criteria, the focus of the criteria (e.g., a test, a model, or its use), the relationship of fairness to individuals, groups, and subgroups, and the mathematical method for measuring fairness (e.g., classification, regression). This work points the way towards future research and measurement of (un)fairness that builds from our modern understanding of fairness while incorporating insights from the past.Comment: FAT* '19: Conference on Fairness, Accountability, and Transparency (FAT* '19), January 29--31, 2019, Atlanta, GA, US

    The SFFA v. Harvard Trojan Horse Admissions Lawsuit

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    Affirmative-action-hostile admissions lawsuits are modern Trojan horses. The SFFA v. Harvard/UNC case—Students for Fair Admissions, Inc. v. President & Fellows of Harvard College and Students for Fair Admissions, Inc. v. University of North Carolina, et. al., decided jointly—is the most effective Trojan horse admissions lawsuit to date. Constructed to have the distractingly appealing exterior façade of a lawsuit seeking greater fairness in college admissions, the SFFA v. Harvard/UNC case is best understood as a deception-driven battle tactic used by forces waging a multi-decade war against the major legislative victories of America’s Civil Rights Movement, specifically Title VI and Title VII of the Civil Rights Act of 1964. Although the Court’s ruling in SFFA v. Harvard/UNC did not accomplish the legal goal of making race affirmative action categorically unconstitutional, the case conceals and perpetuates a moral falsehood with the ideological power to destroy race-inclusion-focused civil rights laws

    Exposing the Deceit About Disparate Impact

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    More Intelligent Design: Testing Measures of Merit

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    Testing the Master Tools

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