Jodi Beggs' résumé got dinged for being two pages long. She used her middle initial on one document but not another, which also cost her points. If she changed “percent” to the % sign, her score went up.
\n\nBeggs, a data scientist and job seeker, got this feedback from an online system that compares a job description with an applicant's materials to assess how well they match up. The most well known of these tools is Jobscan, though Beggs didn't say which one she tested.
\n\n“If my job is to please the robots,” Beggs says, “then even if I don't like AI-generated content, maybe the machines do.”
\n\nJobscan and other apps like it work on the premise that hiring committees use AI to automatically rate and rank candidates in their applicant tracking system (ATS). Only the top 10 to 20 percent of applicants are considered. The bottom 80 might never see the light of day. That's the belief, anyway. To get on the short list, candidates must tailor the formatting of their CVs and cover letters and pack them with the right keywords to match what the ATS wants to see.
\n\nThe problem is, this premise isn’t always correct. Automated…
Original source: https://www.wired.com/