' Rachel Foster | MTTLR

Machines May Not be the Solution to Tech Recruiting’s Gender Bias

The tech industry is currently being scrutinized for gender discrimination and a gender employment gap. While women make up more than half of the U.S. workforce, they make up less than 20% of U.S. tech jobs. High-profile women at technology companies have come forward to tell their stories of sexual harassment at work. Other women have spoken out about the often-toxic atmosphere for women in technology workplaces. Perhaps this is why, as Reuters reported, Amazon began testing an AI tool to help streamline the recruiting process. After all, since humans are clearly biased in hiring, making the process more objective and turning it over to machines could be the answer. Unfortunately, Amazon discontinued the experimental tool after discovering that it showed bias against women. The technology rated candidates on a scale of one star to five stars on a variety of factors. It was designed to take in a large number of candidates and output the top few options. However, Amazon discovered that the system taught itself to prefer male candidates: It penalized resumes that included the word “women’s,” as in “women’s tennis team member,” and downgraded graduates of two all-women’s colleges. Further, it gave preference to so-called “masculine language”: words such as “executed” or “captured.” Amazon tried altering the program to fix these problems, but the issue is bigger than these two instances. The computer model learned from patterns submitted to the company over a 10-year period, and male applicants have dominated the industry since its inception. The program learned the biases from the humans that had done the job before it, and these biases could present in...