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 [Inclusion &amp; Opportunity](/categories/inclusion-opportunity)

 # Hiring Algorithms Are Not Neutral

 

##### By Gideon Mann &amp; Cathy O'Neil

 

 

 Dec 19, 2016 3:30 PM ET

  Campaign:  [Bloomberg: Global Diversity &amp; Inclusion](/news/campaign/bloomberg-global-diversity-inclusion) [Originally posted on Harvard Business Review.](https://hbr.org/2016/12/hiring-algorithms-are-not-neutral)  
  
By Gideon Mann &amp; 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](https://www.accesswire.com/436847/72-of-Resumes-are-Never-Seen-by-Employers) 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.  
  
[Cliick here to read more.](https://hbr.org/2016/12/hiring-algorithms-are-not-neutral)



 

 

 

 

 

 

 

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