Recruiting New Talent: Understanding the Use of Algorithms

Unfortunately, as human beings, we have certainy tendencies that comes from nature and nurture.  As we grow, we develop certain thoughts and biases that can make it nearly impossible to be objective when evaluating candidates.  In fact, in studies of hiring practices, it has been demonstrated that people are most likely to hire candidates that are like themselves.  This, of course, prevents the desired diversity. In order to combat this problem, many companies have turned to algorithms, which are programs developed to assess candidates in a very scientific manner.  This is not necessarily a new idea, but one that has seen increased interest and much advancement in recent years.

Despite concerns that algorithms can involve buried bias, there is evidence – via scientific research – that suggests even the most basic algorithm was better at identifying candidate potential than human beings.  Researchers believe that these findings can be explained by the ingrained thought patterns of human beings.  We have a tendency to develop patterns in the way that we problem solve, and that can lead to interviewers putting too much weight on particular details, which will ultimately mean very little in the workplace.

Further research has showcased the ability of algorithms to increase diversity. This portion of the equation is easily understood.  We are raised to have certain ideas about other people, and it does not necessarily come down to race alone.  There are many biases that can be highlighted when interviewing. Race is certainly one issue, but also sexual preference, weight, age, and sex, for instance, can weigh into the decision making process.  According to recent reports, the use of algorithms could increase diversity by as much as 26%, because it focuses entirely on talent-related traits, and professional indicators.  Of course, because the person hiring will undoubtedly meet with the highest ranking candidates before filling the position, there must be a desire to increase diversity.

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