Law Commons^™

The Auditing Imperative For Automated Hiring, Ifeoma Ajunwa

AI-DR Collection

The high bar of proof to demonstrate either a disparate treatment or disparate impact cause of action under Title VII of the Civil Rights Act, coupled with the “black box” nature of many automated hiring systems, renders the detection and redress of bias in such algorithmic systems difficult. This Article, with contributions at the intersection of administrative law, employment & labor law, and law & technology, makes the central claim that the automation of hiring both facilitates and obfuscates employment discrimination. That phenomenon and the deployment of intellectual property law as a shield against the scrutiny of automated systems combine …

The Invisible Web At Work: Artificial Intelligence And Electronic Surveillance In The Workplace, Richard A. Bales, Katherine Vw Stone

AI-DR Collection

Employers and others who hire or engage workers to perform services use a dizzying array of electronic mechanisms to make personnel decisions about hiring, worker evaluation, compensation, discipline, and retention. These electronic mechanisms include electronic trackers, surveillance cameras, metabolism monitors, wearable biological measuring devices, and implantable technology. These tools enable employers to record their workers’ every movement, listen in on their conversations, measure minute aspects of performance, and detect oppositional organizing activities. The data collected is transformed by means of artificial intelligence (A-I) algorithms into a permanent electronic resume that can identify and predict an individual’s performance as well as …

The Paradox Of Automation As Anti-Bias Intervention, Ifeoma Ajunwa

AI-DR Collection

A received wisdom is that automated decision-making serves as an anti-bias intervention. The conceit is that removing humans from the decision-making process will also eliminate human bias. The paradox, however, is that in some instances, automated decision-making has served to replicate and amplify bias. With a case study of the algorithmic capture of hiring as heuristic device, this Article provides a taxonomy of problematic features associated with algorithmic decision-making as anti-bias intervention and argues that those features are at odds with the fundamental principle of equal opportunity in employment. To examine these problematic features within the context of algorithmic hiring …

Is Algorithmic Affirmative Action Legal?, Jason R. Bent

AI-DR Collection

This Article is the first to comprehensively explore whether algorithmic affirmative action is lawful. It concludes that both statutory and constitutional antidiscrimination law leave room for race-aware affirmative action in the design of fair algorithms. Along the way, the Article recommends some clarifications of current doctrine and proposes the pursuit of formally race-neutral methods to achieve the admittedly race-conscious goals of algorithmic affirmative action.

The Article proceeds as follows. Part I introduces algorithmic affirmative action. It begins with a brief review of the bias problem in machine learning and then identifies multiple design options for algorithmic fairness. These designs are …

Future Work, Jeffrey M. Hirsch

AI-DR Collection

The Industrial Revolution. The Digital Age. These revolutions radically altered the workplace and society. We may be on the cusp of a new era—one that will rival or even surpass these historic disruptions. Technology such as artificial intelligence, robotics, virtual reality, and cutting-edge monitoring devices are developing at a rapid pace. These technologies have already begun to infiltrate the workplace and will continue to do so at ever increasing speed and breadth.

This Article addresses the impact of these emerging technologies on the workplace of the present and the future. Drawing upon interviews with leading technologists, the Article explains the …

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

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 …

Brief To The National Labor Relations Board By Amicus Curiae Professor Jeffrey M. Hirsch, Jeffrey M. Hirsch

Faculty Publications

In Purple Communications, Inc., 361 N.L.R.B. 1050 (2014), the NLRB set forth a new analysis covering employees’ use of employer-provided email. Under this analysis, which is based on the Supreme Court’s seminal decision in Republic Aviation Corp. v. NLRB, 324 U.S. 793 (1945), the Board presumes that employees who have access to their employer’s email as part of their work duties can use that email for Section 7 purposes during nonwork time. Purple Communications, 361 N.L.R.B. at 1063. The employer can rebut this presumption by showing that special business circumstances justify additional restrictions on employees’ email use. …

What Should We Do After Work? Automation And Employment Law, Cynthia L. Estlund

AI-DR Collection

Will advances in robotics, artificial intelligence, and machine learning put vast swaths of the labor force out of work or into fierce competition for the jobs that remain? Or, as in the past, will new jobs absorb workers displaced by automation? These hotly debated questions have profound implications for the fortress of rights and benefits that the law of work has constructed on the foundation of the employment relationship. This Article charts a path for reforming the law of work in the face of both justified anxiety and uncertainty about the future impact of automation on jobs.

Automation is driven …

A Modern Union For The Modern Economy, Jeffrey M. Hirsch, Joseph A. Seiner

Faculty Publications

No abstract provided.

Data-Driven Discrimination At Work, Pauline T. Kim

AI-DR Collection

A data revolution is transforming the workplace. Employers are increasingly relying on algorithms to decide who gets interviewed, hired, or promoted. Although data algorithms can help to avoid biased human decision-making, they also risk introducing new sources of bias. Algorithms built on inaccurate, biased, or unrepresentative data can produce outcomes biased along lines of race, sex, or other protected characteristics. Data mining techniques may cause employment decisions to be based on correlations rather than causal relationships; they may obscure the basis on which employment decisions are made; and they may further exacerbate inequality because error detection is limited and feedback …

The Law And Policy Of People Analytics, Matthew T. Bodie, Miriam A. Cherry, Marcia L. Mcormick, Jintong Tang

AI-DR Collection

Leading technology companies such as Google and Facebook have been experimenting with people analytics, a new data-driven approach to human resources management. People analytics is just one example of the new phenomenon of “big data,” in which analyses of huge sets of quantitative information are used to guide decisions. Applying big data to the workplace could lead to more effective outcomes, as in the Moneyball example, where the Oakland Athletics baseball franchise used statistics to assemble a winning team on a shoestring budget. Data may help firms determine which candidates to hire, how to help workers improve job performance, and …

The Gamification Of Work, Miriam A. Cherry

AI-DR Collection

In the language of cyberspace, introducing elements of fun or game-playing into everyday tasks or through simulations is known as the process of “gamification.” The idea that people could be working while they play a video game – in some instances without even knowing that they are working – is becoming part of our reality. Gamification is an important element of what in previous writing I have termed “virtual work,” that is, work that is taking place wholly online, in crowdsourcing arrangements, or in virtual worlds. The gamification of work is an important trend with important implications for employment law. …