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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 …
Reckless Discrimination, Stephanie Bornstein
Reckless Discrimination, Stephanie Bornstein
UF Law Faculty Publications
If there are known, easily adopted ways to reduce bias in employment decisions, should an employer be held liable for discriminatory results when it fails to adopt such measures? Given the vast amount we now know about implicit bias and the ways to reduce it, to what extent is an employer who knowingly fails to do so engaging in intentional discrimination? This Article theorizes a “recklessness” model of discrimination under Title VII, arguing for liability where an employer acts with reckless disregard for the consequences of implicit bias and stereotyping in employment decisions. Legal scholars have argued that Title VII …