Hugh Pickens writes writes: "Joseph Walker writes at the WSJ that although personality tests have a long history in hiring, sophisticated software has now made it possible to evaluate more candidates, amass more data and peer more deeply into applicants' personal lives and interests. allowing employers to predict specific outcomes, such as whether a prospective hire will quit too soon, file disability claims or steal. For example after a half-year trial that cut attrition by a fifth, Xerox now leaves all hiring for its 48,700 call-center jobs to software. Xerox used to pay lots of attention to applicants who had done the job before, then, an algorithm told the company that experience doesn't matter and determined what does matter in a good call-center worker—one who won't quit before the company recoups its $5,000 investment in training. By putting applicants through a battery of tests and then tracking their job performance, Evolv has developed a model for the ideal call-center worker (PDF). The data say that person lives near the job, has reliable transportation and uses one or more social networks, but not more than four. He or she tends not to be overly inquisitive or empathetic, but is creative. "Some of the assumptions we had weren't valid," says Connie Harvey, Xerox's chief operating officer of commercial services. However data-based hiring can expose companies to legal risk. Practices that even unintentionally filter out older or minority applicants can be illegal under federal equal opportunity laws. If a hiring practice is challenged in court as discriminatory, a company must show the criteria it is using are proven to predict success in the job. "The public gets less comfortable when you're using extrinsic or personal factors," says Dennis Doverspike, a professor of industrial and organizational psychology at the University of Akron."