Source | FastCompany : By Lydia Dishman
Tech workers are among the most in demand this year, commanding the highest salaries and most career opportunities. And while there is a plethora of job openings, not every potential candidate has the coding chops combined with work experience and a solid business background. But Stephanie Lampkin certainly did.
Like many accomplished tech workers, Lampkin started coding at as a kid. From her first steps into programming at age 13, Lampkin worked her way through an engineering degree from Stanford and an MBA from MIT’s Sloan School of Management. Yet after spending five years at Microsoft, the 31-year old applied for a data analytics role at the company and was told she’d be a better fit for a sales or marketing position.
Why? Lampkin believes she was overlooked because as an African American woman she didn’t fit the typical profile. There had to be a better way for qualified candidates to make it past recruiting gatekeepers operating on the premise that a “good fit” meant hiring someone who looked like everyone else already at a particular company. So she built an app that helps eliminate unconscious bias from the hiring process. It took two years of development, but Blendoor finally launched in public beta on March 11.
Rather than relegate her experience to the anecdotal, Lampkin points to quantifiable evidence that unconscious bias is alive and well, despite tech companies’ efforts to diversify their talent pools.
First, she notes that scientists estimate that the brain receives about 11 million bits of information per second, but that the conscious mind can only process about 200 bits. The way the brain works to do this is by connecting new information to preconceived concepts. So, for example, when an applicant for a job is unknown, recruiting and hiring are a ripe environment for people to make decisions based on what —or who—they can relate to best.