Hiring Algorithms May Put Jobs Out of Reach
Many retailers, call centers, and other employers of entry-level service staff have begun using machine learning systems to evaluate job applicants. Analyzing numerous factors for thousands of employees, specialized technology firms develop online questionnaires that surface the factors most predictive of success for each employer and job.
Some firms have found that people with shorter commutes tend to make better hires, because they are statistically likely to stay in the job longer. This insight may be particularly important for service sector employers, whose hiring is increasingly automated, and for whom turnover is a major concern. According to a 2012 Wall Street Journal report, a hiring analytics firm called Kenexa (now owned by IBM) “asks applicants for call-center and fast-food jobs to describe their commute by picking options ranging from ‘less than 10 minutes’ to ‘more than 45 minutes.’ The longer the commute, the lower their recommendation score for these jobs, says Jeff Weekley, who oversees the assessments.”  The same story also notes that how reliable a person’s transportation is (i.e., whether they depend on public transportation) and how long they have lived at their current address may also be considered.
A second firm that applies big data to the hiring process, Evolv, has reportedly made a different choice. As the Atlantic Monthly reported:
There are some data that Evolv simply won’t use, out of a concern that the information might lead to systematic bias against whole classes of people. The distance an employee lives from work, for instance, is never factored into the score given each applicant, although it is reported to some clients. That’s because different neighborhoods and towns can have different racial profiles, which means that scoring distance from work could violate equal-employment-opportunity standards. 
A hiring preference against workers who live far away may be accurate—they may really average shorter tenure in the job—but is it fair?
A hiring preference against workers who live far away may be accurate—they may really average shorter tenure in the job—but is it fair? Such a preference punishes people for living far from where the jobs are, and can particularly hurt those living in economically disadvantaged areas, who are disproportionately people of color. Such practices make it even harder for people in disadvantaged communities to work their way out of poverty.
 Joseph Walker, Meet the New Boss: Big Data, Wall St. J. (Sep. 20, 2012), http://online.wsj.com/news/articles/SB10000872396390443890304578006252019616768.
 See Don Peck, They’re Watching You At Work, The Atlantic (Dec. 2013), http://www.theatlantic.com/magazine/archive/2013/12/theyre-watching-you-at-work/354681.