Organizations are increasingly using algorithmic processes to help make business decisions regarding hiring and marketing, for example. Artificial intelligence is also being used to determine consumers’ access to education, healthcare, credit, or housing. At the same time, technology and data are changing the nature of employment, as more workers enter the gig economy. These changes have important implications for legal issues related to employment and discrimination.

High-stakes employment and discrimination cases require rigorous economic and statistical analysis. Cornerstone Research works with clients at all stages of the litigation process, combining cutting-edge data analytic techniques with decades of experience.

Algorithmic Bias and Big Data

The widespread use of big data and algorithms raises new concerns about bias and discrimination in many business contexts including employment, advertising, consumer finance, and healthcare. Artificial intelligence and machine learning techniques allow firms to harness big data to make inferences about people. For example, these tools can help predict which job candidates will perform well in a given job, or which customers are more creditworthy

At the same time, these automated decision-making processes may generate disparate impact across groups through inadvertent algorithmic discrimination. Cornerstone Research’s understanding of the economics of discrimination and the science of algorithms and big data enables us to provide insightful analyses of algorithmic discrimination claims.

Data-Driven Self-Assessment

Algorithmic decision-making tools come with both new opportunities for combating bias and new risks for creating it. Many organizations are choosing to mitigate risk and improve equity by retaining external experts to conduct pre-emptive, independent, data-driven self-assessments of these processes.

Independent self-assessment of internal data and processes that leverages economic and statistical analysis can help organizations identify ways to increase equity and avoid potential litigation. These methods can be used to identify where a given decision process has generated—or if it is at risk of generating—harmful, disparate outcomes for different groups of employees and/or customers. This type of self-assessment can also provide support for establishing procedures for internal data collection and analysis that promote equitable decision making.

Worker Classification and the Gig Economy

Tech platforms and the rise of the gig economy are disrupting traditional labor markets. 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.