Big Data: Risks and Considerations in Using Predictive Data in Employment Decisions

Labor and Employment Lawnotes Spring 2016

Adam S. Forman, a Member of the Firm, and Matthew Savage Aibel, an Associate, in the Employment, Labor, and Workforce Management practice, authored an article in the State Bar of Michigan’s Labor and Employment Lawnotes titled “Big Data: Risks and Considerations in Using Predictive Data in Employment Decisions.” The article discusses a January 2016 report issued by the U.S. Federal Trade Commission regarding the use of data analytics in making employment decisions.

Following is an excerpt:

Many concerns about the use of big data for employment decisions were also identified in the FTC’s Report, such as the quality of the data, uncorrected biases in the underlying data, and the observation that whereas big data is highly effective in showing correlations, correlation is not causation. Ultimately, the concerns fed into the larger concern about whether big data will be used to categorize applicants and employees in way that can result in the exclusion of certain populations and classifications.

The FTC’s Report also described some of the laws that may apply to big data practices. With respect to employment practices, the FTC advised companies using big data analytics to consider federal equal opportunity laws, such as Title VII of the Civil Rights Act of 1964, the Age Discrimination in Employment Act, the Americans with Disabilities Act, and the Genetic Information Nondiscrimination Act. The FTC’s Report also discusses how the use of big data could lead to disparate treatment and/or disparate impact.