Increasingly sophisticated data analytics paired with machine learning is changing the world, and workplace applications are already a thriving industry. Over the last five years or so, legal scholars have increasingly explored the legal implications of these new technologies. Most of that work has focused on concerns related to privacy or discrimination, and quite a bit focuses on use of this technology in hiring. This focus only reaches part of the “people analytics” industry–it leaves out the application of predictive analytics to first analyze and then shape worker behavior and the working environment.
In Preventing #MeToo: Artificial Intelligence, the Law and Prophylactics, James P. de Haan tackles this kind of application of AI in the workplace by looking at how predictive analytics could be used to prevent harassment. It’s a great time to be thinking of this potential application for at least three reasons. The effects of the #MeToo movement have caused employers to pay more attention to preventing harassment, the technology appears to be soon in reach, and thinking about this application might help us think carefully about other ways AI might be used to shape worker behavior and the working environment.
Reviewing this article for the Journal of Things We Like Lots posed a challenge because I do not like the kind of surveillance and AI-driven, behavior-prediction program described in this article. What I do like is that, knowing this is coming, de Haan has identified the outlines of how such a program would work, explained the appeal as a tool to prevent harm, and set up several preliminary concerns we should have, highlighting some challenges we need to continue to think through.
As de Haan notes, sexual harassment (as well as harassment on the basis of other identity characteristics) remains widespread, despite the #MeToo movement. Part of the reason harassment remains so widespread is that it is grossly underreported, and part of the reason it is unreported is a fear of retaliation. That fear is well founded. According to the EEOC, about 75% of employees who speak out about harassment report that they experienced some form of retaliation for doing so.
As de Haan further describes, employers have responded to their legal obligations by nearly universally adopting harassment policies and training. While the existence of policies and training may provide a defense to a harassment claim, in some instances, as the EEOC has noted, there is no evidence that they are effective at preventing harassment. de Haan chalks this up to human involvement, noting that “sexual harassment policies . . . are only as good as the managers who implement them and are responsible for making sure there is broad compliance.” Because the legal standard for determining when a working environment has become objectively hostile is ill defined, people are notoriously bad at recognizing it.
From that central observation, de Haan explores what it might mean to remove the human evaluator by employing AI. After summarizing sexual harassment law and the obligations imposed on employers to prevent or remedy it, de Haan summarizes the critiques that the law fails the harassed. The bulk of the article examines how AI might be trained to recognize sexual harassment and identifies a number of legal implications of such a system, namely expanding employer duties to monitor and prevent harassment, and the implications of that monitoring for privacy, reputation, and workplace comradery.
One of de Haan’s central premises is that harassment harms both employees and employers. Thus, when it comes to prevention of harassment, the interests of the employer and employee are not diametrically opposed. For this reason, de Haan notes, creating a cooperative system that recognizes the joint interests of the harassed employee and the employer would more likely correctly pinpoint the workplace problem as the harasser, rather than incorrectly labelling the harassed employee as the workplace problem. In this way, such a cooperative system could promote reporting.
AI is that kind of system. Generally, one of the key uses of AI is to extract patterns and then “map out extant and predicted relationships based on these patterns.” In de Haan’s view, this is exactly the kind of thing that is needed to prevent harassment. Such a program could recognize when interactions between employees might risk creating a hostile environment—and could be more accurate than a person at identifying it early, given the difficulty in defining when an environment becomes hostile.
And as he describes, socio-cultural studies show that harassment is predictable when social situations, personalities, and context clues are analyzed. In fact, businesses are already using software to identify and prevent harassing conduct in email communications. The existing programs, though, are essentially not sensitive enough. They require actionable harassment to occur or almost occur before they alert human resources. To really prevent harm, de Haan argues that the prediction and warning must come earlier in the process—before an actionable harassment claim arises.
de Haan next explains how the AI would be trained to gather the data that would allow such a prediction. He suggests that new hires might play a game that could “allow the program to assign a ‘sensitivity profile’ for each employee.” Based on the research he identifies, that game should also test for a person’s problem-solving skills, propensity for confrontation, and notions of justice. But this is only part of the data that would be needed. The program would also have to learn what conduct is likely to be perceived as harassment. For this, de Haan suggests that
Permitting the program to review internal HR files and complaints would help it understand what actually leads to low-level complaints. . . .Taking this a step further, the program could even reach out of network to comb the internet for all publicly available information about a company’s employees. It can use an employee’s photo to identify social networks and map out relationships with co-workers based on extant connections, photos, conversations, tags, and content interaction.
And this is where the potential gets particularly scary. The program de Haan describes
ranks people based on subjectivity to sexual harassment; categorizes them as potential victims and harassers; consolidates mounds of highly sensitive, private information into one central location; and, perhaps most worryingly, potentially punishes people for acts never committed.
To be effective, an AI harassment prevention program has to have an early warning system to prevent harm even before an official report is made and an accurate “map” of the organization’s employees (including their personalities, work functions, and power relative to each other). In order to achieve this, the program will have to consume “massive amounts of data.”
After painting this picture, de Haan warns of four main legal implications. The ability of an employer to monitor employees this way may create a duty to monitor them if in fact that monitoring is effective at preventing harassment. And the possibility of a system that creates red flags may also create a duty on employers to warn employees who might be targets of harassment. Additionally, the expanded capability and warnings will likely trigger a duty to investigate more employee conduct. And lastly, the collection of so much data—particularly data outside of the workplace—and its use to potentially label an employee a harasser, raises significant privacy and autonomy concerns.
In the end, de Haan notes that nothing he has explained solves the problem of what an employer should do with the information that a particular situation risks creating a hostile environment at some point in the future, although he raises the specter of what might happen and how employees at risk of harassment might react upon finding out if nothing is done in the face of that kind of warning. Notably, he does not do much to address the converse of these concerns—how to prevent protection of at-risk employees from resulting in limits to their work opportunities. As he briefly notes, one response to the #MeToo movement has been that men in positions of power have stopped mentoring women subordinates or engaging in social interactions with them. And because this program would assess all employees, we might worry that a rational employer would segregate those employees assessed “highly” or “over-sensitive” to harassment in career-limiting ways, or maybe not hire them in the first place.
As I said at the beginning, reviewing this article for the Journal of Things We Like Lots posed a challenge because I do not like the kind of program described in this article. But de Haan has provided an important first look at how this kind of program would work, explained the appeal as a tool to prevent harm, and set up an early warning of some concerns and challenges. It is a good step that highlights how many new challenges we need to continue to think through.
- Jason R. Bent, Is Algorithmic Affirmative Action Legal?, 108 Georgetown L. J. 803 (2020).
- Ifeoma Ajunwa, Race, Labor, and the Future of Work, The Oxford Handbook of Race and Law, (Emily S. Houh, Khiara M. Bridges, Devon W. Carbado, eds., December 12, 2020), available at SSRN.
Jason Bent and Ifeoma Ajunwa have authored recent papers I like a lot as they help to uncover and prescribe some solutions to the potential racist treatment of workers through technology as we advance into 2021. Their suggestions on how to address this form of employment discrimination come at a crucial time for workers of color. The nature of racial discord in our society reached a crescendo in 2020 and raised many questions for workers of color. The Covid-19 pandemic placed unusual health and economic burdens on black and brown workers as the insidious nature of the virus afflicted communities of color more harshly. So-called essential workers, many of whom are vulnerable people of color, were forced to risk exposure to the virus in order to perform their work duties in-person as most other workers scurried off to their homes to perform their work duties in a virtual manner. Meanwhile, militia and white supremacist groups have taken a more active role in our society as a response to the national and international protests calling for racial justice after the senseless killing of George Floyd by a police officer in Minnesota.
With the racial consequences from Covid-19 and the George Floyd protests still looming, the country will attempt to recover from the events of 2020. As these recovery efforts proceed, we must not forget that workers of color also face another racial problem, the effects from increasing technological advances aimed at giving employers greater opportunities to capitalize on the use of big data. Both Bent and Ajunwa have authored papers that examine similar concerns related to racial problems caused by technological developments as employers attempt to use algorithms aimed at achieving greater operating efficiencies. Although their suggested resolutions to this problem offer different approaches, both authors, as discussed below, give their readers an interesting take on how workers of color may be subjected by their employers to racism through algorithms and how that form of workplace discrimination should be addressed.
As we advance into 2021 with the hope of stalling the virus and reclaiming or reinvesting in many of the advances that can expand the economy and restore any business growth delayed and stifled by the pandemic, Bent and Ajunwa keep us focused by providing insights about the use of technology that can result in discrimination against workers based on race. Their contributions add to some of the recent literature advancing the concerns about the broad racial implications arising within the growth of algorithms. In the midst of the Black Lives Matter movement and other indicators that highlight how pervasive discrimination exists in our society, the use of racist algorithms has started to generate some concern. Fallible humans operating in a society involving systemic discrimination provide the input for the algorithms. Then those inputs infected with the existing racism of the past and the present can lead to racist outputs even if unintended by those using an algorithm they perceive to be a neutral application.
With general concerns for workers of color subjected to racist algorithms and following the work of technology scholars suggesting that the best way to respond to this form of discrimination is to take affirmative action steps to identify and prevent any discriminatory results, Bent and Ajunwa recommend unique solutions to address this predicament. A few workplace law scholars have started to address the discriminatory problems presented by using emerging technologies to fortify racist treatment of employees. The recent papers of Bent and Ajunwa add to those prior contributions while also offering important considerations for workers of color at such a crucial time for employers to be aware of any actions they take that might create racial concerns for their employees.
On page 824, Bent asks: “Are race-aware algorithm fairness solutions permissible under U.S. anti-discrimination law?” By posing this question, Bent begins an inquiry as to whether employers can correct for racist effects from a neutrally-applied algorithm without violating employment discrimination laws when the correction operates as a form of affirmative action. Bent navigates Supreme Court precedent finding that corrections to or failures to certify test results to prevent disparate impact liability can operate as a form of disparate treatment discrimination against the workers who would have benefitted from the certified results.
In a thoughtful and thorough analysis of the Supreme Court’s jurisprudence on Title VII disparate impact theory and affirmative action law, as well as constitutional equal protection analysis based on race for public sector employers, Bent constructs a possible framework whereby employers may escape disparate treatment discrimination liability when pursuing race-conscious changes to algorithms. Bent turns to the Court’s affirmative action law analysis to distinguish the Court’s disparate impact law jurisprudence as a means for an employer to escape liability when correcting a racist algorithm. According to Bent, an employer’s race-conscious attempt to prevent racial disparities resulting from application of an algorithm could be viewed as part of an affirmative action plan instead of an attempt to correct a disparate impact result.
From Bent’s review of the cases, an ex ante consideration of actions intended to prevent racial disparities will find better traction in complying with the Supreme Court analysis as a proper and legal action under affirmative action law. (Pp. 836-37.) Under Bent’s reasoning, the Supreme Court’s disparate treatment concerns for those workers who would have achieved certain measures under the status quo would be averted by the employer being motivated to take affirmative action steps in designing the algorithm rather than seeking to correct a disparate impact liability resulting from the application of the algorithm. By pursuing changes in the design phase of the algorithm, this affirmative action approach differs from an employer attempting to nullify or change an algorithm’s result as an ex post correction of any discriminatory disparate impact results. (Id.)
Ajunwa has also written about the impacts of technology in the workplace. But, her forthcoming paper addresses more specifically technology’s racial consequences. Ajunwa provides an interesting history of the ebbs and flows of labor actions throughout our country with any growth in improving working conditions for workers of color subsequently being met with newer ways to suppress opportunities and economic benefits for those workers. In cataloguing the historical developments from slavery to Jim Crow codes to increased incarceration to immigrant worker legal restrictions to a current lack of educational and professional opportunities, Ajunwa clarifies the depth of the plight faced by many workers of color seeking equality in our society.
After the illuminating discussion of the historical characterization of racist treatment of workers of color, Ajunwa transitions to the modern-day concerns of racism presented through technological innovation. Ajunwa condemns the expansion of digital platforms to employ gig workers classified as independent contractors who lack many of the legal protections provided to employees. Ajunwa also criticizes the use of algorithms in hiring especially through video interviews. According to Ajunwa, the door to discrimination opens “when these algorithms are trained on white male voices and faces, [because] they put applicants of color at a disadvantage.” Similar to some of the general scholarly concerns about racist algorithms, Ajunwa captures so clearly how design decisions about which inputs to consider can produce a neutral algorithm with racially-discriminatory results.
Ajunwa also discusses the concern that newer developments in surveillance technology create added burdens for workers of color who already have to find ways to “manage stereotypes attached to their race” in an effort to combat racism. With increasing surveillance creating key problems for the experiences of workers of color and the use of automated job tasks resulting in eradicating jobs typically employing those same workers, especially women of color, Ajunwa proposes a solution to rectify the racism produced by technological advances through any algorithms.
Similar to others, Ajunwa calls, in general, for broader and globalized labor protections to address the effects of advancing technologies on vulnerable workers. Though more specifically, Ajunwa ties the proposal to the needed protections for certain precarious workers including prisoners, undocumented immigrants, and guest workers who all tend to be people of color. Ajunwa also asserts that legislatures should conduct racial impact studies before implementing legislation that may create racial disparities. Also, Ajunwa identifies the need for greater economic stability for communities of color as a means of protection.
As a bottom line, Ajunwa beseeches us to not accept the digital growth as a futile development that will create a further racial divide. In this respect, both Bent and Ajunwa raise our consciousness to not only be aware of the racial disparities presented by employer use of technology and algorithms, they offer some methods to prevent this result. As a consequence, Bent and Ajunwa present us with some interesting reads while providing workers of color a potential respite from another racial hurdle in the workplace in 2021. These works also arrive at a time when racial unrest in our society has reached a boiling point and workers of color and their employers need some prescriptions to avoid race discrimination while moving forward in a positive manner.
Michael Z. Green, Confronting Workplace Discrimination from Automated Algorithms in Times of Racial Unrest
, JOTWELL (March 12, 2021) (reviewing Jason R. Bent, Is Algorithmic Affirmative Action Legal?
, Jason R. Bent, Is Algorithmic Affirmative Action Legal?, 108 Geo. L. J. 803 (2020)
. (2020); Ifeoma Ajunwa, Race, Labor, and the Future of Work
, Ifeoma Ajunwa, Race, Labor, and the Future of Work, The Oxford Handbook of Race and Law, (Emily S. Houh, Khiara M. Bridges, Devon W. Carbado, eds., forthcoming 2021), available at SSRN.
Much has been written and said about police unions lately, most of it justifiably impassioned but not all of it well-informed by public-sector labor law rules and practices. This article is both. And while the question of the effect of police unions on police reform has been a hot topic in 2020, it is worth noting that Professor Hardaway identified this as a significant issue before it was as much in the limelight as it is now.
The article begins by recounting a series of tragic killings by police and calls for reform via the Violent Crime Control and Law Enforcement Act of 1994. The article then carefully describes a long history of racism in policing. Moving to modern times, the article catalogues the inadequacies of private litigation in achieving police reform.
It then moves to Justice Department investigations into police misconduct, which have led to settlements and court-monitored reforms such as use of deadly force policies and ways in which to hold officers accountable for misconduct. Police unions, in reaction, insisted that at least some of those reforms involved areas that were mandatory subjects of bargaining under relevant labor laws, and thus could not be made without bargaining with the police union. The article provides a very useful survey of all consent decrees since 1997, discussing their interaction with union contracts. Courts, Professor Hardaway shows, have liberally granted unions the right to intervene in these settlements. Notably, unions argue that they cannot be bound by these settlements because they were not parties to them. This, Professor Hardaway persuasively argues, has hampered enforcement and court oversight.
The article correctly notes that use of force polices are not mandatory subjects of bargaining. The article suggests limiting collective bargaining rights such that unions could not claim that other issues that might be covered by consent decrees, generally labeled “police accountability” and “public interest” matters, are mandatory subjects of bargaining. Unlike some discussions of this issue, Professor Hardaway does a nice job of specifying what specific changes she would like to see in terms of rules about negotiability.
Professor Hardaway understands relevant and critical legal rules. For example, not all states permit police to bargain collectively, and in general, in states that do, some topics are not mandatory subjects of bargaining because the issue impinges too much on the public interest. She traces the history of police and public-sector bargaining rights effectively and accurately. Overall, her discussion of these issues is more sophisticated and nuanced than much of what one sees in popular and even scholarly debates on this topic.
I personally would have talked a bit more about how police management fits into this picture, both in negotiating and enforcing collective bargaining agreements, and also about the political role of both police management and unions. Perhaps these topics could be next in a series. But this article takes on a wealth of complex material, both as to law and policy, and does really well with it. And I strongly agree with her main conclusion: as far as labor law reforms go, this issue is best dealt with by excluding, in a surgical manner, certain topics of bargaining that may intersect with reform efforts.
This is an especially impressive piece given that Professor Hardaway was appointed as an Assistant Professor in 2016, and thus wrote this while still quite early in her career. I liked it a lot.
Cite as: Joseph Slater, Smart Thinking about Police Unions and Labor Law
(February 17, 2021) (reviewing Ayesha Hardaway, Time is Not On Our Side: Why Specious Claims of Collective Bargaining Rights Should Not be Allowed to Delay Police Reform Efforts
, 15 Stan. J. Civ. Rts. & Civ. Liberties
137 (2019)), https://worklaw.jotwell.com/smart-thinking-about-police-unions-and-labor-law/
In their article, The Invisible Web at Work: Artificial Intelligence and Electronic Surveillance in the Workplace, Professors Bales and Stone argue that illegitimate employer uses of artificial intelligence (“AI”) in the workplace may largely outweigh legitimate uses, creating a potentially problematic, but not necessarily unlawful, encroachment on human workers’ rights. The article is divided into three main sections. First, it comprehensively describes the numerous ways in which employers are utilizing AI to transform traditional managerial prerogatives. Second, it analyzes possible workers’ rights violations, concluding that existing law is unlikely fully to protect those rights. Third, it presents areas for future reform. The article concludes with an ominous observation: “companies are collecting unfathomable quantities of data on workers that will significantly tilt the balance of workplace power in favor of employers at workers’ expense.” (P. 62.)
Section I comprehensively surveys employers’ ubiquitous use of AI to transform traditional managerial prerogatives. The authors note that employers “utilize a dizzying array of electronic mechanisms—including trackers, listening devices, surveillance cameras, metabolism monitors, and wearable technology—to watch their workers, measure their performance, avoid disruption, and identify shirking, theft, or waste.” (P. 4.) While these mechanisms may serve legitimate employer goals, they often allow managers to “observe each worker’s every movement, both inside and outside the workplace, and during and after working hours.” (Id.) Moreover, AI algorithms can transform collected data “into a permanent electronic resume that companies are using to track and assess current workers,” and which “could potentially be shared among companies as workers move around the boundaryless workplace from job to job.” (Id.) This “invisible electronic web threatens to invade worker privacy, deter unionization, enable subtle forms of employer blackballing, exacerbate employment discrimination, render unions ineffective, and obliterate the protections of the labor laws.” (Id.)
Section I is itself divided into three parts: Part A (Pp. 5–9) briefly traces AI’s development in production processes. Innovations such as computerized robotic arms, machine learning, computer vision, AI-amplification of human capability, and voice recognition—initially introduced to the workplace to enhance productivity—are now being turned into surveillance instruments. Part B (Pp. 9–15) introduces the concept of People Analytics or data-driven human resources. The authors explain that the People Analytics field uses AI “to guide HR decisions for many areas, including making hiring decisions, monitoring performance, predicting an individual’s work trajectory, evaluating workers to set compensation, and determining an employee’s likelihood of terminating the employment relationship.” (P. 9.) Part C (Pp. 15–22) traces creative uses of electronic surveillance devices to monitor workers. For example, firms are now using electronic badges not only to access buildings but also to record employee conversations, track employee movements, and monitor employees’ vital signs. (Pp. 17–20.) The Section ends with a discussion of how the development of these technologies can be used to monitor workers’ off-duty activities, which “not only creates the potential for highly intrusive monitoring, but also raises questions about how employers will use the data they collect about employees’ performance, with whom they will share it, and how long they will keep it. AI-enhanced data collection, retention, and analytic capabilities threaten to create a permanent record of employee productivity, activity, and medical and physiological attributes.” (Pp. 20–22.)
Part II, which focuses on potential employer liability, picks up where Part I.C. leaves off. After all, that employers can retrain AI-enhanced data to create worker profiles raises two questions about which every worker should be concerned: How can employers use these data collections to harm workers and does the existing legal framework provide sufficient protection to workers? Like so many questions that have arisen during the technological revolution, the authors show that the law is often woefully inadequate to protect workers’ rights. (Pp. 22–59.)
Part II is divided into four parts, each taking a deep dive into a different area of law. Take employment discrimination. AI can amplify bias, by replicating past employment decisions that generated profitable results for the company but themselves were laced with bias. For example, “a hiring algorithm based on current workplace demographics” in Silicon Valley, which “has long been criticized for its white-male-dominated workplaces … likely will replicate and entrench [those] past hiring practices.” (Pp. 22–23.) While the authors recognize that AI could also reduce bias, it can also augment AI, which may reduce the “salutary effect of AI.” (P. 29.) Part II.B. showcases the legal limitations of workplace privacy laws, providing as one example the use of pre-hire videos to evaluate job candidates. Those interviews can “collect data from an applicant’s own devices or from cookies or other technological tracking devices.” (p. 34.) Part II.C. shows how antitrust laws might be used to sue employers who “use shared employee information amassed through AI and electronic surveillance to set compensation, engage in a no-raiding agreement, or blacklist an employee.” (P. 36.) However, this area of law is currently untested. Finally, there are labor law implications, primarily concerning surveillance, bargaining over privacy and surveillances issues, and representation, all of which are discussed in Parts II.D. and II.E. (Pp. 48–59.) But there are limitations here as well. Although the NLRA has historically protected concerted activity from surveillance, for example, the Trump Board has vastly cut back on those protections in recent cases. (Pp. 53–55.)
Part III establishes a compact agenda for future research and reform. (pp. 59–62.) This section cogently explains that while “gathering and using such data have enormous implications for the application of existing workplace laws,” such activities “are occurring with no legal or regulatory oversight.” The authors opine that “[p]erhaps existing laws will be sufficiently adaptable to respond to these new conditions, but there is significant risk they will not.” Accordingly, the authors identify the need to clarify “the law of disparate impact … to ensure that plaintiffs need to show, in their prima facie case, only that an algorithm as a whole caused a disparate impact; plaintiffs should not be expected to show precisely how the algorithm produced the bias.” (P. 60.) The authors also suggest that Congress amend electronic surveillance laws along the lines of “the European General Data Protection Regulation … as a starting point but augmenting it to specifically address data collection in the employment context.” (P. 61.) Such amendments would give workers greater control over their own personal data collected by their employers. The authors further suggest that the Federal Trade Commission clarify that data collected and shared by several employers about workers are in fact antitrust violations. Finally, the authors suggest the Board affirm the following: electronic surveillance violates Section 7; employers must bargain over such “the existence and scope of electronic monitoring and the use of algorithms in decisions involving discipline, job assignment, promotion, or pay;” and that “the existing duty on employers to provide unions with information necessary for meaningful bargaining and grievance-resolution should be extended to information about an employer’s practices and plans regarding the use of AI in personnel management decisions, and to information about algorithms or data collected by AI that an employer has used in personnel decisions affecting individual grievants.” (Pp. 61–62.)
Were this article limited to Section I, alone, Professors Bales and Stone would have made a significant contribution to work law literature. While descriptive, those accounts are the necessary initial step for understanding the social problem presented—employer data collection jeopardizes workers’ rights. But the article is impactful because it goes beyond the descriptive. For example, Section II explains how technological advances in AI are connected to modern HR decisions. Drawing those connections must have been painstaking and tedious for the authors, yet they read as the most interesting part of the article. Moreover, that Section makes an original contribution because the problems the authors expose have not yet arisen in the caselaw.
In closing, the article’s in-depth analysis of possible workplace violations and conclusion that existing law is likely insufficient to protect workers’ rights expose an uncomfortable truth. Namely, technological progress is currently progressing at such a rapid pace that existing law is unlikely to catch up in time to protect workers. As Professors Bales and Stone explain: “given the blinding pace at which companies currently are collecting data on workers, a legal response may quickly become a moot point. Once sufficient data are collected, it likely will be difficult to put the genie back in the bottle.” (P. 59.) Welcome to the brave new workplace.
When enacted in 2008 at the end of the Bush Administration, the Genetic Information Nondiscrimination Act (GINA) seemed like it had come from the future. Although the hard-won result of over a decade of advocacy by Rep. Louise Slaughter of New York, GINA addressed a problem that seemed more hypothetical than real. Genetic testing had been around for a while, introduced to the public in part through the O.J. Simpson trial. It seemed unlikely, though, that employers or insurers would not only secure DNA testing but then use it to discriminate on the basis of genetic difference. Yes, it made sense as a plot for a science-fiction movie like Gattaca, but not as a depiction of current reality.
This assessment is largely borne out in the empirical results in GINA, Big Data, and the Future of Employment Privacy by Bradley Areheart and Jessica Roberts. Examining GINA cases from federal courts during the statute’s first decade of existence, Areheart and Roberts found a mere 48 unique GINA cases, only 26 of which involved terminations. Moreover, most plaintiffs failed to find relief, often losing because of fundamental flaws: they had voluntarily disclosed their genetic information; they could not prove the employer possessed the genetic information; or their information was not considered “genetic.” In fact, the authors “uncovered no cases alleging discrimination based on genetic-test results.” (P. 744.) The article makes a plausible case that GINA has been a failure—or, perhaps more charitably, addressed a nonexistent problem.
Most law review articles would stop there, having provided a solid sense of the litigation picture for a relatively new statute. But Areheart and Roberts flip the script by illuminating a completely alternative justification: namely, GINA as information privacy regulation. Rather than simply a nonentity as an antidiscrimination statute, GINA is instead a powerful deterrent against employer snooping into an employee’s genetic background. Areheart and Roberts persuasively argue that the absence of GINA litigation is in fact evidence of GINA’s success in staking out genetic information as a no-fly zone, and that the Act can be a model for other employee privacy protections. A statutory phoenix rises from the ashes!
It wasn’t intended this way. Areheart and Roberts chronicle the history of the Act, one that was rooted in the ability of health insurers to identify and fence out riskier patients. When insurers were able to hike rates or deny coverage because of pre-existing conditions, exploring one’s own genetics became a financially hazardous endeavor. People were passing up the opportunity to find out genetic predispositions to certain conditions and illnesses to avoid being labeled as a poor risk. And since employers were the source of health insurance coverage for a vast swath of Americans, they too might decide to terminate an employee or pass on hiring someone due to genetic danger signs. Congress stepped in to prevent this type of discrimination, even though the feared phenomenon had not really manifested itself in significant numbers.
Two years after the passage of GINA, the Affordable Care Act prohibited consideration of pre-existing conditions as part of health insurance coverage and rate-setting decisions. So one of GINA’s big rationales was no longer in play. Predictably, the courts have not seen much in the way of GINA-related litigation based on employment discrimination. However, Areheart and Roberts have unearthed a hidden set of imperatives that GINA has placed on employers. The Act prohibits employers from seeking, obtaining, or possessing their employees’ genetic information. That narrow but complete prohibition has carved out genetic information from the panoply of data that employers are otherwise free to collect. As Areheart and Roberts report, the few GINA cases that have been litigated “show that employers are seeking information about their employees, and employees are pushing back.” (P. 734.)
GINA’s “unexpected second life as a privacy statute” (P. 755) is especially important in the employment context. The current state of privacy law has left workers largely exposed. Many assume that the Health Insurance Portability and Accountability Act (HIPAA) protects all health information, but the statute is much narrower in focus. It only applies to health care providers, health care clearinghouses, and health plans, and specifically exempts information within employee personnel files. The Americans with Disabilities Act (ADA) places restrictions on required medical examinations but has a number of exceptions. Although GINA’s scope is also narrow, it is comprehensive in its protection of this information. Moreover, the definition of “genetic information” goes beyond the paradigmatic DNA test to include family medical history. This routine part of employee health fitness forms is now protected by GINA.
Beyond the ramifications for employee genetic privacy, Areheart and Roberts pull out larger implications from GINA’s unexpected impact. They note that GINA’s privacy provisions have a two-pronged effect: they protect the information itself and also prevent the employer from discriminating based on that information. In contrast, the Pregnancy Discrimination Act (PDA) does not prohibit employers from asking about an employee’s pregnancy status—which leaves pregnant workers more vulnerable to discrimination. (P. 770.) The article acknowledges that there may be benefits from the sharing of genetic data between worker and firm that GINA forecloses. (Pp. 773-76.) But this loss may be the necessary expense to preserve the confidentiality of employees’ genetic makeup in such an effective manner.
GINA’s future remains to be written; Areheart and Roberts’ empirical investigation shows only a small number of current cases, whatever the underlying theory. But their article tells an important story of how the original Congressional plan went awry—and nevertheless led to a surprising and potentially influential new way of protecting employee information. Given the dizzying accumulation of innovative and disturbing encroachments—from RFID chips to round-the-clock health and location monitoring—protecting workers from ever-mounting surveillance and dissection has become an imperative. Areheart and Roberts have staked a claim for GINA as a model for how employee privacy might be protected in other areas of their lives. Their article is a terrific contribution to our understanding of the future of employment.
David Horton, The Arbitration Rules: Procedural Rulemaking by Arbitration Providers
, 105 Minn. L. Rev.
__ (forthcoming), available at SSRN
In the ongoing discussion over so-called mandatory arbitration “agreements” imposed on consumers and employees, many have focused on questions of fairness and justice, on the potential of such privatization of adjudication to stifle development of the law, on whether mandatory arbitration amounts to suppression of low-dollar-value claims, and on whether arbitrators are overtly or implicitly biased in favor of businesses and employers who as repeat players are the sources for future work for the arbitrators. Largely missing from the discussion are the arbitration services organizations, such as the American Arbitration Association and JAMS. In The Arbitration Rules: Procedural Rulemaking by Arbitration Providers, David Horton goes a long way to filling that void.
Horton begins with a useful report on the history and evolution of arbitration services organization rules. The heart of the article is his analysis of the rules on three grounds, based on a comparison of the arbitration rules to the Federal Rules of Civil Procedure.
First, he observes, that the Federal Rules involve drafting and review by two committees with opportunity for public testimony and written comments before the ultimate product is approved by the Supreme Court. Even then, Congress may veto the rules within seven months of their approval by the Court. In contrast, arbitration services organizations enact their rules by fiat without much, if any, transparency. He notes the major exception of the adoption of the due process protocols for employment and consumer arbitration which were developed by broad committees of industry and consumer and employee representatives as well as representatives of the neutral adjudicator communities. However, he discounts this as a one-time occurrence.
Horton finds that the key regulator of arbitration services organization rules is the market, and cautions that the market makers are the businesses that impose the rules on their employees and customers. He concludes that the evidence of whether the market is an effective regulator is mixed. He points to the notorious National Arbitration Forum, which was forced to cease doing consumer arbitration because its processes were so biased against consumers, and to JAMS’s withdrawal of its policy opposing class action waivers as caving in to the market. On the other hand, he acknowledges that AAA is the dominant player and calls its rules “plaintiff-friendly.” He attributes this to AAA’s marketing its product as having a high degree of likelihood to withstand court challenge and concludes that the market could protect consumers and employees if it values the probability that awards will be upheld.
Second, Horton contrasts the Federal Rules which are generic and apply to all types of cases with arbitration service organizations that have discreet rules for different kinds of cases, such as employment, consumer, construction, insurance and so on. He recognizes advantages in avoiding the one size fits all approach of the Federal Rules but cautions that the approach of the Federal Rules acts as a brake against tilting the rules toward one side or another. What might favor defendants in one type of case might favor plaintiffs in another. In contrast, Horton urges, the proliferation of many different sets of rules favors repeat players who have greater familiarity with the differences among rules. It also leads to businesses choosing the rules that favor them the most, such as by classifying workers as independent contractors rather than employees and placing them under AAA’s Commercial Rules instead of its more claimant-protective Employment Rules.
Third, Horton observes that the Federal Rules strike a balance between accuracy in adjudication and efficiency, whereas the arbitration service organizations prioritize efficiency. He finds fault with two features of many providers’ rules that prioritize efficiency. One is a strict waiver doctrine, with the rules providing that a party who fails to state an objection to a violation of the rules and proceeds with the arbitration has waived the violation. He maintains that this has led to judicial confirmation of flawed awards, including cases where the arbitrator engaged in private conversations with one party. The second is the tendency among provider rules to clothe the arbitrator with authority to rule on questions of arbitrability, questions that would otherwise fall to a court. Horton correctly points out that this approach conflicts with a basic principle of due process, that an adjudicator may not have a personal financial stake in the case. An arbitrator has a personal financial stake in finding a matter arbitrable because that will result in more work and more revenue for the arbitrator.
Finally, Horton turns to doctrinal issues raised by his analysis. He critiques courts that have implied from the adoption of a particular arbitration service organization’s rules which empower the arbitrator to rule on questions of arbitrability an intent by the parties to delegate to the arbitrator exclusive authority to rule on such matters. He urges that rules empowering arbitrators to rule on their jurisdiction do not mandate that they do so and leave open the option of a judicial ruling. Moreover, he maintains, these rules are designed to save time and money when a matter already is in arbitration and, therefore, should not be read to reflect an intent to cut out judicial resolution of arbitrability disputes that arise at the outset of a case. The problem of the arbitrator’s financial interest in finding the matter arbitrable is exacerbated where the arbitration agreement is adhesive and the product of large disparities in bargaining power. He urges courts to reject this approach.
Horton turns next to what he calls weaponizing rules. He observes that businesses have classified workers as independent contractors and specified that commercial rather than employment rules will apply or have recognized workers as employees but nevertheless adopted the commercial rules. Horton highlights two major differences between AAA’s commercial and employment rules. Under the commercial rules, parties are equally responsible for the forum costs, including the arbitrator’s fee, whereas under the employment rules, the employer is responsible for all forum costs and arbitrator fees except for a $300 filing fee paid by the claimant (an amount less than the filing fee in federal district court). The AAA employment rules empower the arbitrator to award any remedy that a court could award, whereas the commercial rules limit the arbitrator’s remedial authority to what is within the scope of the parties’ agreement. Horton calls to task courts for not policing such abuse at all, or for responding to it merely by severing the offending provision and directing arbitration anyway. He properly calls for courts to strike the entire arbitration agreement in such cases of over-reaching.
Horton lastly turns to the recent tactic of plaintiff employment lawyers of filing mass claims, sometimes thousands of identical individual claims and demanding arbitration of each of them. He observes that at one level the tactic amounts to a shakedown of the business respondent but at another level it is simply following the very rules that that respondent imposed on its employees. He also observes that when the respondents have refused to pay the millions of dollars in arbitration fees, the arbitration service providers consider it a material breach and cancel the arbitrations. He observes that what happens next is unclear; do the claimants then have to refile their claims in court? Unfortunately, Horton does not offer any prescriptions for dealing with these situations. In my view the answer is clear. A court should order specific performance of the agreement to arbitrate and require the employer to pay the millions of dollars in filing fees. Any other approach undermines the ability of the market to police against employers’ abusive uses of arbitration mandates.
In the 1990s, when the Supreme Court first endorsed employment arbitration mandates imposed by employers, it reasoned that the employee was not waiving substantive rights but only agreeing to resolve them in an arbitral forum as long as the forum allowed the employee to effectively vindicate those statutory rights. But in more recent cases such as Concepcion, Italian Colors Restaurant, and Epic Systems, the Court has labeled the effective vindication requirement dicta and instead focused on a supposed federal policy of enforcing arbitration agreements in accordance with their terms. I would have liked to have seen Horton engage with this evolving Court approach to arbitration mandates and its implications for the doctrinal solutions he has advocated. Despite these nits that I have picked, I applaud Horton for focusing attention on the role of arbitration service organizations, a neglected piece of the puzzle of arbitration mandates. I hope his article leads to further discussion of service organizations’ roles in the continuing dialogue about mandatory arbitration.
Blair Druhan Bullock, Uncovering Harassment Retaliation
, __ Ala. L. Rev.
__ (forthcoming, 2020), available at SSRN
Articles sometimes do an important service by exposing what seems obvious, but only in retrospect. Blair Druhan Bullock’s Uncovering Harassment Retaliation, forthcoming in the Alabama Law Review, does a great job of surfacing an issue that had previously received little attention in the law journals.
It’s not news that women have been, at least before #MeToo and probably still, reluctant to report harassment. Neither is it news that one reason is their fears of retaliation for invoking the employer remedial processes that have been put in place in the wake of the Faragher/Ellerth structure for employer liability. And it will come as no surprise that the courts have been remarkably unreceptive to claims of victims of sex harassment that delaying a report until the situation became unbearable was reasonable because of fears of retaliation. What is needed, and what Professor Bullock provides in Uncovering Harassment Retaliation, is an empirical basis for believing such fears are well grounded and not (as one might think from reading court opinions) paranoiac.
Although it is challenging to get more than anecdotal data on an issue as complicated as the extent of retaliation against those who report harassment, the author offers two main bases for concluding that such retaliation is common, especially when the alleged harasser is a supervisor (although it seems likely that respondents to a survey that she analyzes were using a more common-sense definition of “supervisor” than the Supreme Court’s stringent definition). The article notes the Catch-22 created by the intersection of the requirement of § 704(a) (a reasonable belief in the illegality of the conduct reported) and the requirement of early reporting of harassment (perhaps before it is sufficiently severe or pervasive to be reasonably viewed as illegal), but it has bigger empirical fish to fry.
Looking to a dataset the author created of 1990-2013 filings with the EEOC obtained by an FOIA request, the article reports that “[U]pwards of 70% of harassment claims filed with the EEOC include a retaliation charge, and . . . harassment charges are more than 90% more likely to include a retaliation charge than any other type of discrimination claim.” (P. 1.) The latter finding is striking. While a skeptic might dismiss any employee charges as self-serving evidence of the reality they supposedly reflect, it’s hard to see any reason harassment should manifest more false positives than other charges of discrimination.
While recognizing that liability standards in theory should discourage retaliation against reporting victims, the article then analyzes a 2016 Merit Systems Protection Board harassment survey of federal employees to conclude that such deterrence too often fails. While this Jot is not the place to summarize all of Professor Bullock’s findings, she makes a persuasive case that reporting harassment by supervisors “greatly increases the likelihood that a victim experiences an adverse employment action as a result of the harassment.” (P. 1.) She writes, for example, that “female sexual harassment victims who reported the harassment were 11.4 percentage points more likely to experience an adverse employment action compared to those that did not report the harassment,” (P. 33) and those “who are harassed by their supervisor are 22.7 percentage points more likely to experience an adverse action.” (P. 34.)
The takeaways from these and similar findings are twofold. First, “courts must move away from treating the failure to report as an end all be all to the Faragher/Ellerth affirmative defense or even to negligence liability for coworker harassment—especially under the current regime where not all victims who report are protected under retaliation law.” (P. 39.) Rather, she urges courts to “consider the reasonability of failing to report.” (P. 39.) There are, in fact, a handful of cases taking this something like this approach, and Professor Bullock’s article offers a strong basis for more to follow.
Second, and more sweepingly, the author questions the current incentive structure for employer response to harassment. She argues that separating a supervisor harasser from the victim is typically the optimal solution for the employer facing a complaint, and the one transferred is too often the victim. The article has a nuanced assessment of the cross-cutting operational, legal, reputational, and cost incentives involved in such decisions, but Professor Bullock’s empirical work suggests that all too often the employer calculus nets out by moving the victim. The thumb on the scale in such cases is the operational efficiencies of keeping a supervisor in place.
There is much to chew on here, and both the empirical work and the author’s theoretical explanations leave room for debate. But there is no doubt that Professor Bullock has raised an important reality that needs careful consideration in a #MeToo world. Uncovering Harassment Retaliation suggests modifications that could rejigger the incentives created by Title VII’s current liability structure, but, recognizing the difficulty of achieving meaningful change in this arena, it urges state legislatures to address the issue. There is already significant legislative reform dealing with sexual harassment in that arena, particularly with respect to nondisclosure agreements, but Professor Bullock urges legislation that would “remove the reporting requirement for supervisor harassment, broadly define supervisor, codify a mixed-motive standard for retaliation, or expand retaliation protections to cover all forms of opposition” (Pp. 43-44), noting some limited successes to date. More are needed.
- Hiba Hafiz, Labor’s Antitrust Paradox, 87 U. Chi. L. Rev. 381 (2019).
- Sanjukta Paul, Antitrust as Allocator of Coordination Rights, 67 UCLA L. Rev. ___ (forthcoming 2020), available at SSRN.
The political economy of work in the United States is on the skids. In April 2020, unemployment skyrocketed,reaching a level not seen since the worst days of the Depression in the 1930s. Many who are still going to work — so-called “essential workers” — are in low-wage jobs without basic legal protections (think of independent contractor delivery and truck drivers, home care workers), as a matter of policy choice, not as a matter of some irresistible law of economics . Many farmworkers and other food sector workers are undocumented – meaning that government deems their work both essential and illegal. People of color and immigrants are hardest hit by coronavirus deaths and unemployment.
Now is the time to rethink how antitrust weakens collective action by workers while allowing massive concentration and enhancing the power of capital. Hiba Hafiz and Sanjukta Paul are doing exactly that. Both Hafiz and Paul challenge the dominance of a particular school of economic thought in antitrust analysis. They reflect an exciting push back against what Sandeep Vaheesan has called the economism of antitrust law. Their work helps scholars of labor and judges to discuss when, whether, or why collective action by labor is legal rather than an anti-competitive restraint on trade, and to understand why law has failed to curb the economic concentration that has suppressed wages.
The public is getting a crash course in what low wage workers have known for years – the law isn’t protecting workers. Huge companies have the ability to flout the law simply because they are huge. In California, app-based delivery and ride companies announced their refusal to comply with the California Supreme Court’s Dynamex decision and AB-5, a state statute requiring them to classify their workers as employees. Finally, California’s attorney general and a group of city attorneys filed suit to force Uber and Lyft to comply with the law. In May, Tesla announced it was re-opening its factory in defiance of a public health order, threatened to fire any worker who obeyed the public health order and failed to return to work, and the public health officials ultimately backed down and allowed the company to re-open even while the shelter-in-place order continued. App-based workers like Instacart shoppers have struck to protest the lack of safety protections and their low-wages. An Amazon warehouse worker got fired for protesting a lack of safety protections, and worker advocates filed a lawsuit over whether time spent handwashing would be held against workers at the same warehouse. But still the problems continue.
Workers need, and lack, the power to negotiate effectively for protections. Concentration of business has caused wage stagnation and has made it harder for workers to wrest wage increases and improved working conditions from business. The power of concentrated capital as compared to the power of workers demands action. Yet efforts of states to enable collective negotiation to balance the power of concentrated capital with a collective voice of workers have been stymied by antitrust litigation. As Hiba Hafiz explains the state of antitrust law today, “workers seeking to use antitrust law to challenge employer buyer power in the new era of labor antitrust will face difficulties. At the same time, they will expose themselves to potential antitrust liability if they seek to coordinate to counter that power.” (Pp. 402-03.)
In some ways, we are back to where the country was between 1929 and 1931 – massive unemployment, unprecedented economic inequality, and yet many workers are unable to unionize because of the threat of antitrust litigation. As Lenin said in criticizing economists for condemning unionization and worker political agitation, what is to be done?
Paul argues that business, aided by a particular school of economic thought, deployed antitrust law to attack disfavored forms of economic coordination, including collective action by workers both through labor unions and through other forms. “Meanwhile,” Paul says, “a very specific exception to the competitive order has been written into the law for one type of coordination, and one type only: that embodied by the traditionally organized, top-down business firm.” (P. 42.) The result is that collective action by for-hire car drivers has been attacked as an antitrust violation even as Uber’s own price-fixing survives challenge. Paul goes to the source of the problem and challenges the regnant regime of economic analysis and the notion that intra-firm arrangements (what Paul calls coordination) are immune from scrutiny.
Hafiz explains and critiques the antitrust law relevant to labor, showing why it fails to protect workers from the monopsony and collusive power of employers while preventing workers collective action as countervailing power. She proposes “regulatory sharing” as a way that antitrust enforcement and labor rights enforcement can protect consumers and workers, rather than seeing worker protection necessarily coming at the expense of consumer welfare.
Together, Hafiz and Paul help us go back to first principles in antitrust and labor to think about how to reconcile robust worker protection with robust protection for consumers.
Being neither a scholar of antitrust nor an economist myself, I want to suggest why it benefits scholars of labor and employment to consider their work. Chief among them is the growth of organizing among workers who do not presently enjoy the status of employee under the National Labor Relations Act and, therefore, the labor exemption from antitrust liability for collective action. Lawyers have faced antitrust enforcement for going on strike to protest the abysmally low rates paid to handle criminal defense of indigent people. Even playwrights face antitrust litigation when they try to improve labor standards by acting collectively. As more and more companies have realized they can lower labor costs and increase share price by classifying their workforce as independent contractors, the scope of the labor exemption to antitrust shrinks. The relevance of antitrust to labor grows correspondingly.
Hafiz and, especially, Paul (in this and other works) shed light on the intellectual history of the particular form of economic analysis that came to dominate antitrust theories. Looking back at the history of antitrust’s evolution, particularly in its engagement with labor, illuminates the significance of rethinking antitrust now. Use of antitrust to formulate labor policy rarely turned out well for either antitrust law and policy or labor. This is a familiar story in the period between 1890 and 1932, when – as Herbert Hovenkamp notes – the majority of antitrust actions were filed against unions rather than against business combinations. Herbert Hovenkamp, Principles of Antitrust, Chapter 16.b.3 (West 2017).
But even at the height of the New Deal, and even with the progressive Thurman Arnold in charge, antitrust proved to be a threat to worker collective action. In 1937 – the very year the Supreme Court upheld the constitutionality of the National Labor Relations Act and it seemed that worker collective action would finally, for the first time in American history, be safe from criminal and civil litigation aimed at suppressing it — Thurman Arnold’s division of the Department of Justice filed half a dozen enforcement actions against labor unions nationwide, including unions in the construction trades, the American Federation of Musicians, and others. Targeted by either DOJ or companies in those years were activities that some considered illegitimate, such as sit-down strikes, secondary boycotts and jurisdictional strikes, picketing for recognition, or collective action by independent contractor fishermen and drivers.
As Harvard labor law professor (and later Attorney General) Archibald Cox tartly observed of this campaign, although Arnold “gave assurance that there would be no interference with legitimate organizational techniques or collective bargaining,” the Antitrust Division was quite vague about “how it proposed to distinguish the legitimate from the restrictive,” and the antitrust lawyers’ own “views on labor policy were highly influential.” (P. 261.)
Cox rightly spotted the hazards of Arnold’s campaign against unions. Opening the door to lawyers in the Antitrust Division, and federal judges, to decide which expressions of worker solidarity were desirable would revive the very problems that the National Labor Relations Act and the Norris-LaGuardia Act had been enacted to eliminate. Although the Antitrust Division lost its suits, and the Supreme Court ruled that antitrust would have no role to play in regulating union activity, some of the conduct that the Antitrust Division branded as illegitimate – notably, picketing for recognition, secondary activity, and jurisdictional strikes — were later banned by the Taft-Hartley Act and thus brought back into federal courts’ purview. And the sit-down strike tactic that was targeted in Apex was declared unprotected by federal law and prohibited by state criminal law. Federal judges and federal juries still grant injunctions and damages judgments, sometimes crushing ones, against expressions of worker activism that they deem illegitimate. Some secondary activity is speech protected by the First Amendment under NAACP v. Claiborne Hardware Co. But some – like the lawyers’ protest about the low rates paid for indigent criminal defense — might not be.
Hafiz and Paul explain the dominance of a certain kind economic analysis in antitrust law, and show how it has been used to reduce worker power while allowing massive economic concentration and inequalities of wealth. It is also worth noting the historical controversy over which styles of economics have been considered acceptable in analyzing labor collective action. As Hafiz explains in other work, in 1940 and 1947, Congress amended the NLRA to specifically prohibit the NLRB from hiring “individuals for the purpose of conciliation or mediation, or for economic analysis.” Congress’ target – the Division of Economic Research – was thought (wrongly, as it happens) to be a hotbed of communism. The economists at the NLRB in those days were, in Congress’ view, the wrong kind of economists — the kind who used the empirical and mathematical skills of the discipline to document, understand, and combat labor exploitation.
If a new political economy of labor is to emerge from the present crisis, it will be important to avoid repeating the mistakes of the mid-twentieth century, when the upsurge of labor organizing failed to produce a durable legal regime to protect workers against the power of capital. As we think about that, reading Hiba Hafiz and Sanjukta Paul’s work (along with that of many other progressive antitrust scholars) will help those thinking about a new start for labor.
Cite as: Catherine Fisk, Taking Business Law Back from the Economists: Building Worker Power Through Antitrust Reform
, JOTWELL (August 26, 2020) (reviewing Hiba Hafiz, Labor’s Antitrust Paradox
, 87 U. Chi. L. Rev.
381 (2019) and Sanjukta Paul, Antitrust as Allocator of Coordination Rights
, 67 UCLA L. Rev
. ___ (forthcoming 2020), available at SSRN
I haven’t taught the basic Employment Law survey course in a few years, so I was updating my class notes relating to the kinds of pre-employment screening measures that many employers use. The casebook had a note about so-called ban-the-box measures—state laws that require employers to remove questions about criminal histories from a job application. I decided to do a little research into the subject when – lo and behold – I stumbled across one of those articles that helps an instructor add some value to the class while simultaneously making a practical contribution to the scholarship in the field.
Do Ban-the-Box-Laws Really Work? by Dallen Flake takes a look at the practical effect of ban-the-box laws. The article begins with an overview of the rise in these types of measures in recent years and the different approaches that the measures take. The ban-the-box laws reflect a recognition of the difficulties that those with arrest and conviction records often face in seeking to find employment. Much like the Americans with Disabilities Act’s prohibition on disability-related inquiries at the pre-offer stage, ban-the-box measures delay the ability of employers to inquire about an applicant’s criminal history. As Flake explains, “The hope is that an employer will be more likely to hire an ex-offender if it evaluates a candidate’s qualifications for the position before discovering the applicant’s criminal record.” (P. 1084.)
But as more states (now up to approximately 33) have adopted these types of measures, there have remained questions as to how effective they actually are in practice. Others have raised concerns that the measures may actually adversely impact minority applicants by prompting employers to eliminate these candidates from consideration on the assumption that all minority applicants have a criminal record in light of their higher arrest and incarceration rates. While there have been other studies of ban-the-box measures by economists, Flake’s is (I believe) the first empirical study of the issue from the perspective of legal academic. The article is also one of the first to conduct an experiment, rather than relying on employment data, to measure the effectiveness of ban-the-box measures.
Without giving too much of the game away, in an effort to test some of the competing arguments concerning these measures, Flake submitted fictitious job applications in a ban-the-box locality (Chicago) and a non-ban-the-box locality (Dallas) and then compared callback rates between the two groups. The fictitious Chicago candidates had a 27% higher callback rate than the Dallas candidates. Moreover, the callback rates were higher regardless of the perceived race of the fictious applicant, thus undercutting the argument that ban-the-box measures might adversely minority applicants. Indeed, the fictitious black applicants had the highest increase in callbacks. However, “the black applicants had much lower callback rates than the white and Latino applicants in both Chicago and Dallas, indicating race remains a formidable barrier to employment, regardless of whether an employer is aware of a candidate’s criminal record.” (P. 1080.)
All of the usual disclaimers that go along with empirical studies apply here – the sample size was relatively small (2,006 applications in two cities), the study only measures callbacks, not whether an applicant received a job, etc. But like any good empirical work, the article gives the reader plenty to chew on and dissect. Beyond that, the article adds an important piece to part of a renewed discussion of employer screening practices. In the 1980s and 90s, there was considerable concern about employers’ use of polygraph testing, personality testing, and similar measures during the hiring process. At the same time, there was the concern on the back end of the hiring process that an employer who failed to adequately screen its employees might hire inefficient workers or face liability in the form of negligent hiring or retention lawsuits. While the concerns on the back end largely remain the same in 2020, technology has changed so dramatically in the ensuing years that there are new concerns about the front end. These include fears about employers’ use of face-scanning algorithms, data mining, and similar screening devices during the hiring process, particularly their impact on individual privacy and potential for discriminatory outcomes. Flake’s article focuses on a decidedly low-tech screening method – questions about criminal history – but one that fits within the broader ongoing discussion. For anyone interested in these types of issues, Do Ban-the-Box-Laws Really Work? is a thought-provoking contribution to the scholarship in the area.
Perhaps one of the biggest drawbacks in the current legal academic literature is its disconnect with the scientific community. Social science and scientific research have so much to offer the legal academy, but too often this wealth of valuable information goes overlooked and unnoticed. This information can be particularly instructive to workplace law, as scholars continue to explore the driving forces behind discriminatory bias, employer motivations and other related issues.
In her fascinating piece, Acting Differently: How Science on the Social Brain Can Inform Antidiscrimination Law, Professor Susan Carle (American University) helps bridge this gap between the legal workplace literature and the academic sciences. The article is the last in a wonderful trilogy Professor Carle has written on discrimination and human behavior. I highly recommend the other two articles as well, which are available here and here.
This final piece in the trilogy is particularly valuable in its deep exploration of the existing scientific research, and its potential impact on workplace doctrine. In this paper, Professor Carle examines the experimental sciences, looking specifically at the inter-disciplinary field of social neuroscience. Much has been written over the years on the topic of unconscious bias, as we have generally seen less overt acts of discrimination in the workplace over the years since the enactment of Title VII in 1964. As a society, we are now much more aware of the illegalities of discrimination than we were decades ago, and employers have enacted policies, training, and other tools to help prevent such unlawful conduct. The research examined by Professor Carle looks specifically at unconscious bias— and how we may unknowingly treat others who express behavioral differences.
In this paper, Professor Carle takes on the issue of implicit bias by mining the rich social neuroscience research on the topic. This research goes beyond the often more superficial conclusion that unlawful bias unconsciously occurs in the workplace and examines more precisely how implicit discrimination occurs in the brain, and why it takes place. This research explores how we “automatically and non-volitionally process cues” with respect to behavioral differences between groups. (P. 662.) Professor Carle finds that what typically “matters to the brain is not status or identity per se, but what the brain perceives about how a person’s behavior reflects identity.” (P. 662.)
Most impressively, Professor Carle takes the next important step in connecting these findings to anti-discrimination law doctrine. She reasons that the findings in the social neuroscience research suggest that workplace law must look more closely to the connection that exists between how the behavior of an employee is perceived and the effectuation of a discriminatory employment decision. Put more simply, discrimination law should more fully examine the link between an employer’s perception of worker conduct and discrimination. As Professor Carle explains, the real question in many discrimination cases is whether the negative treatment of individuals is the result of their “acting differently.” (P. 706.)
By exploring the existing neuroscience research in supporting these conclusions, Professor Carle discusses the scientific research which shows empirically how we react to those that act differently from ourselves. She also raises specific proposals on workplace law reform that go along with her findings, perhaps modestly referring to them as “immediate pragmatic tweaks” to existing doctrine. (P. 717.) While this discussion itself is illuminating, Professor Carle’s more groundbreaking proposal is what she characterizes as the “recognition of a general human right to act differently,” as long as those actions do not interfere with the rights of others. (P. 717.) Professor Carle discusses in great detail this novel approach and explains exactly how the establishment of such a right could be effectuated under existing frameworks. As she concludes, “[i]t thus has become increasingly imperative that antidiscrimination advocates, using evidence-based research, promote appreciation for individuals’ “acting differently” (within the bounds of others’ rights) as a foundational value in anti-discrimination law.” (P. 730.) Professor Carle does a superb job of balancing her proposals against any potential objections and takes a well-rounded approach in the paper. Given the novel nature of what she suggests here, this type of cautious approach is particularly well warranted.
The descriptive value of Professor Carle’s analysis of social neuroscience research in this paper alone is invaluable. From her work, I learned a tremendous amount about the nature of implicit bias and how the brain works in making seemingly unconscious decisions. But this paper is so much more, as it uses this existing research to identify a new right for workers to act differently (within certain bounds). The research she discusses, and the new right she identifies, caused me to take a step back and reflect upon my own analysis and research of workplace law and anti-discrimination doctrine.
Simply put, this paper is a must read for anyone exploring implicit bias, or anyone studying the broader connection between scientific research and workplace law. I anticipate (and hope) that Professor Carle’s work here will encourage a deeper dive by others into the connection between the social sciences and other areas of employment law. And, I look forward to the robust debate which is sure to follow over the appropriateness and parameters of the new right— the right to act differently— that she sets forth in this work.