Are you feeling a bit paranoid about the use of data-mining tools to sift through huge piles of online information to predict or manipulate your behavior? How would you feel if companies started using Big Data to find job applicants, with an eye toward increasing racial diversity?
I couldn't get three paragraphs into an article on the subject at National Journal before my hackles went up, and that was one paragraph before concerns about how it could all go horribly wrong were explored:
Humans are fallible, biased creatures, and even the most well-intentioned hiring managers have a strong tendency to hire "look like me, act like me" candidates.
Those unintended prejudices in recruitment—whether racial, gendered, or economic—are shortcomings that a growing number of big-data firms are hoping they can help solve with their massive number-crunching operations. By mining troves of personal and professional data, these companies claim they can not only match employers with A-plus job candidates, but help close diversity gaps in the workforce, too.
"Big data in the workplace poses some new risks, but it may yet turn out to be good news for traditionally disadvantaged job applicants," said David Robinson, a principal at Robinson + Yu, a consulting group that works to connect social justice and technology.
Still, concerns abound. Earlier this year, the White House released a landmark report on big data, warning that the exploding enterprise could—intentionally or not—allow companies to use data to discriminate against certain groups of people, particularly minorities and low-income groups. That's also the fear of the Federal Trade Commission, which held a workshop last week exploring the concept of "discrimination by algorithm."
"Big data can have consequences," FTC Chairwoman Edith Ramirez said. "Those consequences can be either enormously beneficial to individuals and society, or deeply detrimental."