Labor, Discrimination, and Algorithmic Bias

With the forthcoming Supreme Court ruling on Students for Fair Admissions Inc. v. President and Fellows of Harvard College et al. and Students for Fair Admissions Inc. v. University of North Carolina et al., institutions of higher education may soon be facing a different legal environment regarding the use of race in their admissions. Cornerstone Research can help institutions navigate this changing environment. We work extensively with admission data across a variety of graduate and undergraduate admissions programs. Leveraging our expert network and this expertise, our teams conduct econometric analysis to help institutions better understand their current admission policies and explore alternative approaches. We can help to quantify the impact of race in existing admissions regimes as well as simulate alternative regimes where race is not directly considered but where the increased emphasis is put on other characteristics.

Cornerstone Research’s experience in admissions analysis includes its support for David Card in Students for Fair Admissions Inc. v. President and Fellows of Harvard College et al., and Caroline Hoxby in Students for Fair Admissions Inc. v. University of North Carolina et al. In each case, the judges favorably and extensively cited the experts supported by Cornerstone and issued a favorable verdict for our clients. Our work in these high profile matters gives Cornerstone unparalleled experience in building admission models and assessing the role of race in admission.

Discrimination cases—whether in hiring, compensation, promotion, or other selective processes like college admissions—typically hinge on empirical analyses designed to measure the impact, if any, of the alleged conduct on the relevant protected group. Our staff and experts are well-versed in the statistical and econometric techniques used to evaluate alleged discrimination in a variety of contexts, including promotion and pay, pre-litigation consulting on pay equity issues, and the use of race in college admissions and employment decisions.

The widespread use of big data and algorithmic decision-making raises new concerns about bias and discrimination in many business contexts, including advertising, consumer finance, employment, and healthcare. Cornerstone Research’s understanding of the economics of discrimination and the science of algorithms and big data provides insightful analyses of algorithmic bias and claims of discrimination.

Regulatory bodies and policy makers are increasingly focused on antitrust concerns in labor markets. We have worked on a variety of high-profile labor antitrust matters in both litigation and regulatory contexts, including no-poach (both vertical and horizontal) and monopsony cartel matters. Through our expert network, we work with leading academics to capture the unique economics of labor markets when assessing allegations of anticompetitive conduct.

A rapidly growing body of litigation focuses on fundamental questions about the nature of employment, including whether workers are independent contractors or employees. Cornerstone Research staff and experts have worked on multiple, complex worker classification matters involving the gig economy and leading tech platforms, as well as more traditional worker classification matters.

Our expertise in class certification is a common thread across high-profile employment matters. Together with academic experts, Cornerstone Research applies rigorous statistical methods to assess whether common impact can be established using common class-wide evidence and methodologies. Our experience spans a variety of labor market contexts, including high-skill professions (such as finance or healthcare), retail and manufacturing, and tech platforms.

Addressing executive compensation issues requires understanding the market for executive talent and the determinants of appropriate compensation, such as performance, risk taking, firm viability, and shareholder rights. Analysis and testimony in these cases may also call for accurate valuation of all components of compensation, including noncash compensation such as stock options or nonmonetary benefits, and an understanding of the incentives inherent in the compensation structure.

We have worked with leading economists to evaluate allegations that firms have violated labor laws. For example, we have determined whether a proposed class of workers falls into a relevant job description and therefore has standing to bring an underlying claim. Compliance cases can include statistical analysis of documents such as time cards and pay checks, survey analysis, or studying the workers’ day-to-day tasks.