Stephanie Lampkin is the founder and CEO of Blendoor, a company that uses AI and analytics to help companies remove unconscious biases and improve diversity.
In a Q&A with The Hustle, she talked about the reasons for the startup world’s diversity problems and what actions are needed for improvement:
It’s much easier to hire people that you know and in your network, and I think particularly given the ways that venture capitalists are incentivized, which is to provide a return on investment for their [limited partners] relatively quickly. That pressure sort of trickles down to startup CEOs. They need to hire quickly. That sort of behavior drives building very homogeneous teams — and once you have built that momentum and that culture, it’s really difficult to switch gears and think really critically about diversity.
I think it’s all rooted in incentives. Kapor Capital started with a diversity pledge for all of their new investments… you have to commit to making notable efforts for diversity recruiting and retention. I’m not a big fan of pledges, but it’s a good start. What will really move the needle is when investors make mandates that they will not provide funding for homogenous teams and/or it will impact your valuation. We’re starting to see that a little bit with bigger companies but not so much yet with startups.
There’s actually evidence that homogenous teams early on, when they’re really small and have to move really quickly, tend to perform better. The benefits decline as you grow… fundamental diversity helps avoid groupthink. When you have people with different perspectives and backgrounds, it enables a lot more of a critical eye that is oftentimes absent when you’re dealing with a lack of diversity, particularly diversity of thought. As companies are at the growth and scaling phase, it can be particularly inhibitive of innovation.
We are actually right as we speak researching ways to build machine learning algorithms that can identify traits, characteristics, and connections among those small groups of individuals that have been able to be successful in joining corporate boards or entering the ranks of executive leadership — women and underrepresented minorities specifically. What we realize is oftentimes the rubrics used to identify talent are either biased toward white, cigender, able-bodied men or they just leave a lot of people out through their filtering mechanisms. We’re trying to leverage data on those who have been successful so that we aren’t inputting our own biases into the algorithms that can surface high-potential candidates.