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Algorithms At Work: Productivity Monitoring Applications And Wearable Technology As The New Data-Centric Research Agenda For Employment And Labor Law, Ifeoma Ajunwa Jul 2019

Algorithms At Work: Productivity Monitoring Applications And Wearable Technology As The New Data-Centric Research Agenda For Employment And Labor Law, Ifeoma Ajunwa

AI-DR Collection

Recent work technology advancements such as productivity monitoring platforms and wearable technology have given rise to new organizational behavior regarding the management of employees and also prompt new legal questions regarding the protection of workers’ privacy rights. In this Essay, I argue that the proliferation of productivity monitoring applications and wearable technologies will lead to new legal controversies for employment and labor law. In Part I, I assert that productivity monitoring applications will prompt a new reckoning of the balance between the employer’s pecuniary interests in monitoring productivity and the employees’ privacy interests. Ironically, such applications may also be both …


Bias In, Bias Out, Sandra G. Mason Jun 2019

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 Jan 2019

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 …