3 ways AI can close the gender gap: from recruitment to performance reviews
Despite the advances in the workplace for women, the World Economic Forum predicts that it will take 217 years to close the economic gender gap globally. In other words, it will take 7 generations just to even the playing field. At this rate, we’re more likely to colonize Mars before we realize gender equity in the workplace.
However, as AI continues to take a prominent role in today’s society, technology-driven HR tools can eliminate the unconscious bias and subjectivity that hinder gender equity in the workplace. From recruitment to performance reviews, here are 3 ways AI can close the gender gap.
Recruiters receive hundreds to thousands of resumes on a weekly basis. How can they decipher the most qualified candidates in a timely and efficient manner without incorporating biased and arbitrary decisions? With the help of AI programs like Eightfold.ai, the recruitment process can be streamlined to hire based on meritocracy and experiences, removing gender-specific identifications. Consequently, Eightfold.ai helps to identify candidates who will be more qualified for the position and increase diversity in the team.
By discounting factors like gender, developers of these HR tools have taken the recruitment process to an intriguing level. For example, Unilever integrates neuroscience-based games to gain data on individual behavior traits, utilizing AI to analyze patterns within those traits. Without submitting a resume, candidates would participate in 20-minutes of online neuroscience challenges.
Once approved, candidates move onto the interview stage, where AI will break the conversation down to body language and keywords. This recruitment approach allows head hunters to target candidates that fulfill the job requirements, undistracted by bias and prejudice. In fact, Unilever has demonstrated that their strategies have altered their hiring pipeline dramatically. 50% of their analyst roles are now occupied by women, in comparison to 20% two years ago.
In a 2016 study, Stanford University noted that “women are systematically less likely to receive specific feedback tied to outcomes,” while “men are offered a clearer picture of what they are doing well and more-specific guidance of what is needed to get to the next level”. This traditional path have trapped women in a catch-22. Managers are not promoting women because ironically, they aren’t providing definitive directions. How can women rise to C-level roles without proper guidance?
Katica Roy, the founder of Pipeline, is determined to create equal opportunities and treatment during key moments like performance reviews and salary decisions. Pipeline is an AI software that collects internal company data and generates recommendations on who to promote, hire, or transfer with the goal of closing the equity gap. The program analyzes the impact of these modifications and how they can affect the company’s bottom line with each step.
Over time, AI platforms can standardize performance reviews. Each employee will receive concrete goals and feedback, which they can incorporate in their career development plans.
Realizing 50/50 equity
ABC Of Women Worker’s Rights and Gender Equality defines gender equity as the “fairness of treatment for women and men, according to their respective needs,” which includes “equal treatment or treatment that is different but which is considered equivalent in terms of rights, benefits, obligations, and opportunities”.
Most of the time, gender discrimination is unconscious – and that’s the problem. Both men and women are guilty of unconscious prejudice. On the other hand, AI has the potential to evaluate the high performers and distribute treatment in an unbiased manner. Ideally, AI should play the impartial judge who will bestow rewards and salaries based on talents and achievements.
Yet, there’s still a long way to go before AI can come close to eradicating unconscious bias in the workplace. Only recently, Amazon revealed that their AI hiring tool has learned to discriminate against women, favoring resumes with “masculine” terms like “captured” and disfavoring resumes that contain “women” (i.e. women’s engineer club).
AI is only in its beginning stages. With imperfect algorithms and coding, there will be kinks and hiccups. There will be moments when AI fails to live up to society’s ideals. Still, if the result is an unbiased and objective environment, the struggle is worth it.