Deep Background

Big Data in background screening? “Promising and scary”

The Equal Employment Opportunity Commission recently held a public forum exploring the pros and cons of companies’ use of Big Data to make background-screening decisions in hiring, as well as in promotions. Participants cited a recent survey showing that 32% of companies use Big Data to make HR decisions.

Big Data (in this context, sometimes called predictive talent analytics) includes merging traditional information such as work history and education with potentially thousands of data points lifted from the Web or purchased from data brokers. This could include a person’s history of addresses and car ownership; sweepstake entries and use of loyalty cards; social-media or video-game use (perhaps even the time of day or night they’re used); keywords used on Twitter; consumer data from laptops, smartphones, and wearable devices; and even from Internet of Things gear such as a home-security system.

For current employees, the information can be blended with data such as job evaluations, absenteeism, analysis of company email use, and participation in wellness programs.

Big Data advocates told the EEOC that studies have found it can successfully spot job prospects who turn out to be productive and enthusiastic. Proponents also said data-crunching can reduce the tendency of HR officials to make “similar-to-me” hiring choices. “People that are likely to gain the most [from Big Data use] include women, members of racial minorities, those who lack access to education and mentors / role models, and people who are short of cultural and social capital,” testified Michal Kosinski, a Stanford professor of organizational behavior.

Critics of the practice pointed out that public records and databases are riddled with inaccuracies and incomplete data. Algorithms defining what makes a successful employee are based on assumptions and guesses, skeptics testified. Experts who are transporting Big Data science from the marketing world into the job realm need to pay heed to employment and privacy law, critics told the EEOC. (An FTC study cited Big Data research showing that people who fill out job applications using web browsers that had to be installed, as opposed to browsers that came with their computers, “perform better and change jobs less often.” The FTC said using this correlation to deny someone a job arguably could be a violation of the law.)

“Programmers and data scientists may inadvertently or unconsciously design, train, or deploy big data systems with biases,” said a White House study of the same topic. Computer scientists building systems to hire people must practice “bias mitigation” to “avoid building in the designers’ biases that are an inevitable product of their own culture and experiences in life,” it said. Despite the risks, firms’ reliance on Big Data is “expected to grow exponentially in the future,” the EEOC said in its report.

Kathleen Lundquist, a psychologist and frequent expert witness in HR-related lawsuits, told the agency that Big Data “is the inevitable future of HR. It presents a future that is both promising and scary.”

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