Big Data and Employment Screening: Promising and Scary

“Big Data has the potential to drive innovations that reduce bias in employment decisions and help employers make better decisions in hiring, performance evaluations, and promotions.” This powerful statement from EEOC Chair, Jenny R. Yang, came with an equally powerful disclaimer: “At the same time, it is critical that these tools are designed to promote fairness and opportunity, so that reliance on these expanding sources of data does not create new barriers to opportunity,” Yang warned.

The EEOC held a meeting last October, to hear from experts on the growing use of algorithms to make employment-related decisions. Known as big data, predictive analytics, or talent analytics, Dr. Kathleen Ludquist, an organizational psychologist, expressed her opinion that organizations will inevitably be moving toward harvesting a wide range of empirical data for HR decision making. In her view, this is both promising and scary. Other experts appear to agree.

The promising side of big data:

Dr. Michael Housman, a workforce scientist with a background in Applied Economics, feels big data can give a fair shot to non-traditional candidates who might not otherwise have a chance at employment, including individuals who have had long-term unemployment.

Dr. Michal Kosinski, a professor of Organizational Behavior at Stanford Graduate School of Business, also expressed optimism. He remarked, “If used properly, Big Data, coupled with modern computational techniques, can improve person-job fit, increase the ability to identify talent, raise equality in access to jobs and careers, and help overcome implicit and explicit prejudice in the workplace.”

The ‘scary’ side of big data:

Other experts warned of the dangers of big data and the use of algorithms in HR decisions. Dr. Lundquist warned, “Algorithms may be trained to predict outcomes which are themselves the result of previous discrimination…The algorithm is matching people characteristics, rather than job requirements.”

Dr. Ifeoma Ajunwa, a Fellow at the Berkman Klein Center at Harvard University and Assistant Professor of Law at University of the District of Columbia School of Law, expressed a similar concern. He said, “Absent careful safeguards, demographic, sensitive health or genetic information is at risk for being incorporated in the Big Data analytics technologies that employers are beginning to use. These challenge the spirit of antidiscrimination laws such as the Americans with Disabilities Act and the Genetic Information Nondiscrimination Act.”

How Employers Should Proceed with Big Data:

As with any other employment screening or hiring practice, the use of big data must be carefully considered. Employers have an obligation to avoid discriminatory hiring practices, both those that are known and unknown. It’s the unknown side of using big data or predictive analytics that makes this new frontier especially risky for employers. Add to this the fact that today’s legal environment has not yet evolved to fully account for the use of big data, employers may find themselves in uncharted territory from a legal standpoint.

If you have questions about your employment screening practices and how big data might play a role in your decision making, give us a call.

About MichaelGaul

Michael is a results-oriented marketing executive with over two decades of experience in employment screening, physical security, and business process management. Michael has deep experience in human capital risk management and a passion for educating business leaders and HR professionals on strategies that tangibly protect their interests. Michael serves on the Board of the Secure Cash and Transport Association (SCTA) and is a member of the Professional Background Screening Association (PBSA), and the American Society of Industrial Security (ASIS).
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