Privacy's Rights Trap

By: Ari Ezra Waldman

Big Data Affirmative Action

By: Peter N. Salib

Independent Contractors in Law and in Fact

By: Eleanor Wilking

Reimagining Public Safety

By: Brandon Hasbrouck

Moral Nuisance Abatement Statutes

By: Scott W. Stern

2022 Symposium: Fraud and the Erosion of Trust (Oct. 28)

Big Data Affirmative Action

By: Salib, Peter N | November 13, 2022

As a vast and ever-growing body of social-scientific research shows, discrimination remains pervasive in the United States. In education, work, consumer markets, healthcare, criminal justice, and more, Black people fare worse than whites, women worse than men, and so on. Moreover, the evidence now convincingly demonstrates that this inequality is driven by discrimination. Yet solutions are scarce. The best empirical studies find that popular interventions—like diversity seminars and antibias trainings—have little or no effect. And more muscular solutions—like hiring quotas or school busing—are now regularly struck down as illegal. Indeed, in the last thirty years, the Supreme Court has invalidated every such ambitious affirmative action plan that it has reviewed.

This Article proposes a novel solution: Big Data Affirmative Action. Like old-fashioned affirmative action, Big Data Affirmative Action would award benefits to individuals because of their membership in protected groups. Since Black defendants are discriminatorily incarcerated for longer than whites, Big Data Affirmative Action would intervene to reduce their sentences. Since women are paid less than men, it would step in to raise their salaries. But unlike old-fashioned affirmative action, Big Data Affirmative Action would be automated, algorithmic, and precise. Circa 2021, data scientists are already analyzing rich datasets to identify and quantify discriminatory harm. Armed with such quantitative measures, Big Data Affirmative Action algorithms would intervene to automatically adjust flawed human decisions—correcting discriminatory harm but going no further.

Big Data Affirmative Action has two advantages over the alternatives. First, it would actually work. Unlike, say, antibias trainings, Big Data Affirmative Action would operate directly on unfair outcomes, immediately remedying discriminatory harm. Second, Big Data Affirmative Action would be legal, notwithstanding the Supreme Court’s recent case law. As argued here, the Court has not, in fact, recently turned against affirmative action. Rather, it has consistently demanded that affirmative action policies both stand on solid empirical ground and be well tailored to remedying only particularized instances of actual discrimination. The policies that the Court recently rejected have failed to do either. Big Data Affirmative Action can easily do both.

Independent Contractors in Law and in Fact: Evidence from U.S. Tax Returns

By: Wilking, Eleanor | November 13, 2022

Federal tax law divides workers into two categories depending on the degree of control exercised over them by the service purchaser (i.e., the firm): employees, who are subject to direct supervision; and independent contractors, who operate autonomously. Such worker classification determines the administration of income tax and what it subsidizes, as well as which nontax regulations pertain, such as workplace safety and antidiscrimination protections. The Internal Revenue Service and other federal agencies have codified common law agency doctrine into multifactor balancing tests used to legally distinguish employees from independent contractors. These tests have proved challenging to apply and costly to enforce. Yet we know almost nothing about how firms actually classify workers systemically and how such classification relates to the control firms exercise over workers.

To bridge this gap between legal principles and legal practice, this Article introduces a novel empirical analysis using a comprehensive data source—all digitized U.S. income tax filings between 2001 and 2016. This analysis establishes several new facts. First, using six measures of firms’ control over workers, I show that employees and contractors have grown increasingly similar over the past two decades. I found this convergence to be particularly pronounced among lower earning workers. I then develop a novel theoretical framework to interpret these findings. Second, I provide empirical evidence that the presence of financial incentives created by government policy increases the likelihood that employees are reclassified as contractors.

These results suggest a growing misalignment between how workers are classified and the substance of firm–worker relationships. Put another way, two otherwise identical workers, with relationships that feature a similar degree of control, may end up being classified differently due to, among other factors, their firms’ financial incentives. I conclude by discussing the key normative questions raised by the apparent erosion of the legal boundary delimiting contractors and employees.

Reimagining Public Safety

By: Hasbrouck, Brandon | November 15, 2022

In the aftermath of George Floyd’s murder, abolitionists were repeatedly asked to explain what they meant by “abolish the police”—the idea so seemingly foreign that its literal meaning evaded interviewers. The narrative rapidly turned to the abolitionists’ secondary proposals, as interviewers quickly jettisoned the idea of literally abolishing the police. What the incredulous journalists failed to see was that abolishing police and prisons is not aimed merely at eliminating the collateral consequences of other social ills. Abolitionists seek to build a society in which policing and incarceration are unnecessary. Rather than a society without a means of protecting public safety, abolitionists desire a society where the entire public is safe. That safety requires security in all our material needs, not merely protection from private violence.

Abolition democracy challenges us to envision a society where all people have the respect, education, economic resources, civil rights, and franchise necessary to participate fully in all significant aspects of public life—a society in which we are both safe and free. This challenge to our worldview is further compounded by the prevalence of inequality and a culture of violence in American society. In this Article, I meet that challenge with a groundbreaking look at how such a vision requires us to look at public safety not as a zero-sum game between liberty and security, but as a collaborative promotion of life, liberty, and pursuit of happiness for all.

Nw. U. L. Rᴇᴠ.