The hiring process has for a long time been accused of being biased. In fact, the employee referrals is one of the processes that usually leaves large groups of potential employees out, but is still utilized by many companies when hiring.
What’s more, studies have found out that hiring managers and recruiters also introduce their own biases to the process, whereby they pick people with the right sounding names and academic background.
Generally, companies lack both gender and racial diversity, with the ranks of the underrepresented individuals becoming fewer at the top levels of the corporate ladder. Worst case scenario, less than 5% of CEOs at Fortune 500 companies are female. The number is expected to decline later in October when Indra Noovi, the current chief executive officer of Pepsi, steps down.
Additionally, the racial diversity on the boards of Fortune 500 companies is nearly dismal since only four out of five new board appointees in 2016 were white. In the same group, there are only three black chief executive officers.
According to Alan Todd, CorpU’s CEO, recognizing high-potential candidates is highly subjective. He added that individuals select who they feel drawn to in terms of unconscious biases. Nevertheless, AI proponents suggest that the technology could be used in getting rid of some of the biases.
As such, companies like Stella. Ai and Entelo utilize machine learning to identify the skills required for certain jobs instead of depending on people’s feelings in making the right hiring choices. In turn, the AI matches candidates who have the required skills with open positions.
Both Entelo and Stella.ai claim that thanks to AI they are able to spot better candidates and identify those who may have gone unrecognized in the past, particularly in the traditional process. According to Stella’s founder Rich Joffe, his company’s algorithm only evaluates candidates based on skills. In this case, the algorithm is allowed to only look at skills, tiers of companies, and industries, which minimizes bias.
On the other hand, Entelo recently unveiled Unbiased Sourcing Mode, which is a tool that helps in making hiring more anonymous. The company’s software enables recruiters to hide various aspects including employment gaps, markers of someone’s age, school, photos, and names. This effort is intended to reduce different types of discrimination.
Artificial intelligence is currently being utilized in developing internal talent. In fact, CorpU has partnered with the University of Michigan’s Ross School of Business to create a 20-week online course, which leverages machine learning to spot high-potential employees.
According to Todd, the individuals who are ranked highest are not normally the ones who were previously on the promotion track. He added that the process often displays qualities like introversion that are often overlooked during hiring.
Solon Borocas, a Cornell’s Information Science department assistant professor known for studying fairness in machine learning, said that the human decision-making process is highly awful. However, he cautioned humans against overestimating the neutrality of technology.
Borocas’s research has revealed that machine learning in recruitment can lead to unintentional bias, as algorithms can possess the implicit discrimination traits of those who programmed them. Nevertheless, he is convinced that hiring with the aid of AI is much better than the traditional technique.