How HR software can reduce gender bias in the technology sector

How many female candidates has your business turned down?

How many female candidates has your business turned down?

The technology sector continues to deal with a gender imbalance, despite an active hiring process. Part of this can be attributed to a lack of interested applicants, but some of this struggle could possibly be due to subconscious biases in the hiring process. 

According to the National Academy of Sciences, male candidates have nearly twice the chance to get an offer as their female counterparts.

"We find that without any information other than a candidate's appearance (which makes sex clear), both male and female subjects are twice more likely to hire a man than a woman," the abstract reads. "The discrimination survives if performance on the arithmetic task is self-reported, because men tend to boast about their performance, whereas women generally underreport it."

Initially, arguments concerning the gender gap centered around a lack of support for women in the fields of science, technology, engineering or math (STEM), but this study shows a whole different problem: men and women recruiters are discriminating against female candidates without even noticing it. Even if they have similar skills and a had a strong interview, female job seekers in STEM positions will lose the opportunity to a male, EE times, a magazine dedicated to the global electronics industry, explained. 

Changing this bias will require a change of mindset from executives and hiring managers.

"Until hiring and promotion practices change, women can "lean in" all they like, graduate in record numbers from top universities, and dominate buying decisions — but they still are much less likely to make it to the top," Harvard Business Review contributor Avivah Wittenberg-Cox wrote. "The corporate world is led by men confident that they are identifying talent objectively and effectively."

HR software solutions can be a company's first step toward a more level playing field. Instead of reading applications with the plain eye, the system can pick up on specific filters that may make them a stronger candidate for the job opening.