
The traditional hiring process is failing candidates, companies and recruiters. It revolves around human interpretation of complex data that is too susceptible to prejudices and mental shortcuts. A hiring process assisted by machine learning could eliminate systemic biases that put social status over skill. However, in recent news, algorithms have failed at that task. A resume screening algorithm developed at Amazon became biased against female applicants. Another such algorithm favored candidates named Jared who played lacrosse.
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