Much has been written in recent years about how technology that is designed to make us all better connected has blurred the line between work and non-work time. For example, in an age in which many non-exempt workers check work email after work hours, on vacation, or on sick leave, defense lawyers have warned their clients about the potential for claims for overtime pay pursuant to the Fair Labor Standards Act (FLSA). Likewise, much has been written about the erosion of employee privacy in an age in which employers increasingly have the ability to use new technology to monitor their employees’ activities.
Professor Leora Eisenstadt’s forthcoming article, Data Analytics and the Erosion of the Work/Non-Work Divide, discusses these same issues, but with a focus on how the ability of employers to collect employees’ off-duty data impacts the erosion of the work/non-work divide. The article examines employers’ “non-transparent use of data analytics to monitor employee behavior, thoughts, and emotions when they are not working and [their ability] to use this data to make decisions about their workplace success.” (P. 18.)
Professor Eisenstadt provides several examples, including Project Comet, a program that mines data from employees’ social media accounts and then analyzes the information for use by the employer in developing better work teams. These types of programs obviously carry with them the potential for employer misuse. For example, a program that can gather information about an employee’s off-duty health-related internet searches can help an employer identify “which employees are contemplating becoming pregnant, which employees are concerned about developing diabetes, or those who believe they may need back surgery in the near future.” (P. 22.) While the authors of the Americans with Disabilities Act (ADA) could never have foreseen this type of scenario back in 1990 when the law was passed, the scenario involves the same concerns over disability discrimination that resulted in the ADA placing limits on the ability of employers to make health-related inquiries of employees and applicants.
While the article raises these types of immediate concerns, it also focuses more broadly on the extent to which programs like Project Comet weaken the traditional divide between work and non-work and the broader concerns this raises. The more employers are able to use data analytics to monitor employees’ off-duty activities for use in the workplace, the more muddy traditional employment law rules that are based on this distinction – like the going-and-coming rule in workers’ compensation or overtime laws – become in theory and practice. Moreover, the fact that employers are able to engage in extensive monitoring with only the most minimal level of employee consent raises concerns about the ability of modern workplace privacy laws to effectively deal with these practices. As Eisenstadt notes, several states have lifestyle discrimination statutes that prohibit adverse employment actions based on employees’ lawful off-work activities. However, the concerns raised by employers’ use of data analytics and facial scanning go beyond the concerns that initially motivated many of these statutes.
Ultimately, Eisenstadt’s survey provides the sort of overview that enables a reader to identify broad, big-picture concerns as well as more narrow, issue-specific concerns concerning employer practices in this area. At a time when concerns over the ability of employees to find a work-life balance are growing, Eisenstadt has written a thought-provoking piece about another way in which the work/non-work divide is increasingly crumbling.