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Full-Text Articles in Law
Bias In, Bias Out, Sandra G. Mason
Bias In, Bias Out, Sandra G. Mason
AI-DR Collection
Police, prosecutors, judges, and other criminal justice actors increasingly use algorithmic risk assessment to estimate the likelihood that a person will commit future crime. As many scholars have noted, these algorithms tend to have disparate racial impact. In response, critics advocate three strategies of resistance: (1) the exclusion of input factors that correlate closely with race, (2) adjustments to algorithmic design to equalize predictions across racial lines, and (3) rejection of algorithmic methods altogether.
This Article’s central claim is that these strategies are at best superficial and at worst counterproductive, because the source of racial inequality in risk assessment lies …
Antidiscriminatory Algorithms, Stephanie Bornstein
Antidiscriminatory Algorithms, Stephanie Bornstein
UF Law Faculty Publications
Can algorithms be used to advance equality goals in the workplace? A handful of legal scholars have raised concerns that the use of big data at work may lead to protected class discrimination that could fall outside the reach of current antidiscrimination law. Existing scholarship suggests that, because algorithms are “facially neutral,” they pose no problem of unequal treatment. As a result, algorithmic discrimination cannot be challenged using a disparate treatment theory of liability under Title VII of the Civil Rights Act of 1964 (Title VII). Instead, it presents a problem of unequal outcomes, subject to challenge using Title VII’s …