Disruptive discrimination – a down side of big data

Often touted as the great disruptor, big data has proven a valuable tool. But in the world of health and disability discrimination, big data may be driving some of the most serious and disturbing employment discrimination epidemics at every level.

At its core, discrimination is the use of a known current characteristic – such as age, gender, race, religion, disability, sexual orientation, country of national origin, etc. – to treat certain individuals worse than others. Often based on historic prejudice and anecdotal bias, however, even the most reprehensible cases of class-wide discrimination lacked the powerful impact of data troves. But big data brings something new – “predictive” analytics – and in the world of health and disability discrimination, that may drive some of the most serious discrimination practices, as employers now possess more information about their employees’ health than ever before.

Where you shop, your online search queries, your credit rating, your voting habits, your consumer purchases and other data may better predict your health than your genetics – whether you’re at risk for diabetes, pregnant or in need of surgery. Couple that with data on pharmacy claims possessed by most human resource departments, and many companies now have enough information to know your health and possibly predict your future. Whether they will make employment decision based on that information remains the question, especially considering that predictive analytics does not translate into an actionable problem with any employee, but I’m hard-pressed to think they won’t.

The Wall Street Journal and Fortune published articles about the problem this week, and it deserves attention. I’ve included a link to the Fortune article here (Fortune Article), as it is not behind a paywall, although the WSJ article was on point, too. Let me know your thoughts.

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