Hiring AI

Once the stuff of science fiction, artificial intelligence is fast becoming a staple to how people process information around the world. Staffing an office is not immune to this technological advancement. With so many businesses and organizations implementing AI to aid in the hiring process, is it the best way to screen job candidates?

Technology has been making our lives easier since the invention of the wheel and as tech improves, our jobs shift. The manpower behind sifting through thousands of applications, finding several candidates, interviewing them and deciding who is the best individual for the job can take weeks or months to do. Introducing AI to the equation allows people to get back to doing the tasks that they are better equipped to managing. In addition to freeing up workers, time can be saved exponentially– by having a computer quickly scan applicant information, what once took months is sorted to its appropriate file in minutes. Additionally, artificial intelligence is designed to avoid the unconscious bias that humans may unfortunately possess (Khandelwal & Upadhyay, 2018). Whereas managers may subconsciously seek out those with attributes similar to their own, AI does not have this base of traits to compare against (Eberhardt, 2019). However it can learn to be biased.

Artificial intelligence learns through inputs and trial and error; when the information it receives is biased, the way in which it functions can become biased (Shane, 2019). When screening applicants, AI will often lean more toward male candidates (Raub, 2018). Similarly, candidates with “ethnic” names are less likely to be picked over those with Anglo names like Paul or Robert, leading to a racial bias (Shane, 2019). If candidates are lucky enough to get the green light to a telecommunication interview, a face detecting software can monitor facial movements. Those with certain facial features or head coverings may not be detected as well as others and can therefore not rank as highly as those with more symmetrical faces. 

As much as we would like it to be, the science just is not there yet. Artificial intelligence is not capable enough to do what humans want it to do without the various hiccups and mistakes it presents. Perhaps one day technology will meet our candidacy screening needs but for now, AI is too young; where we are asking it to be multifaceted in hiring people, realistically, AI can only do one tiny job at a time (Shane, 2019). Until a computerized hiring manger can fairly screen applicants, it is best it stays on the back burner.  


Eberhardt, J. (2019). Biased: uncovering the hidden prejudice that shapes what we see, think and do. Viking. New York.

Khandelwal, K. & Upadhyay, A. (2018), “Applying artificial intelligence: implications for recruitment”, Strategic HR Review, Vol. 17 No. 5, pp. 255-258.

Raub, M. (2018). Bots, bias and big data: artificial intelligence, algorithmic bias and disparate impact liability in hiring practices. Arkansas Law Review. Vol 71.2. pp 529-570.

Shane, J. (2019). You look like a thing and I love you. New York. Voracious.

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