Hiring Algorithms Are Not Neutral
By Gideon Mann & Cathy O'Neil
Dec 19, 2016 3:30 PM ET
Campaign:
Bloomberg: Global Diversity & Inclusion
Originally posted on Harvard Business Review.
By Gideon Mann & Cathy O'Neil
Gideon Mann is head of data science at Bloomberg LP.
More and more, human resources managers rely on data-driven algorithms to help with hiring decisions and to navigate a vast pool of potential job candidates. These software systems can in some cases be so efficient at screening resumes and evaluating personality tests that 72% of resumes are weeded out before a human ever sees them. But there are drawbacks to this level of efficiency. Man-made algorithms are fallible and may inadvertently reinforce discrimination in hiring practices. Any HR manager using such a system needs to be aware of its limitations and have a plan for dealing with them.
