An Introduction

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January 17, 2019
Hello, and welcome to the RecruitBot blog! In the coming months, we’ll use this space to dive deep into some of the many features RecruitBot offers; highlight new research that’s relevant to the recruiting process; and, because this is the internet, we’ll try and post some cat videos when we can.

For our first entry, we’re going to talk about how and why RecruitBot mitigates the role of unconscious bias in the recruiting process. The fact that RecruitBot analyzes resumes without factoring in age or race or gender is a feature of which we are very proud—there’s a reason we’re highlighting it in our inaugural blog post, after all.

Let’s start with a very simple statement: bias exists—for everyone. A whole raft of academic literature is out there suggesting that even those who consider themselves to be enlightened enough to not be subjected to some sort of bias are, in fact, inevitably biased. To cite just one example, distinctly “white” sounding names are 50% more likely than distinctly “black” sounding names with identical resumes to receive a callback in the recruiting process, even among “equal opportunity” firms.

(If you have a few minutes to spare, head over to Harvard’s implicit bias test page, and get a first-hand experience in how implicit bias asserts itself.)

In any event, we believe that addressing the issue of bias is a vital moral issue. But even beyond that, from a practical perspective, encouraging diversity leads to numerous positive business outcomes:

There is of course much more research documenting the economic benefits of a diverse workforce, but there’s no need to belabor the point. The data is overwhelmingly in support of doing so.


RecruitBot helps reduce the role of unconscious bias in recruiting by focusing entirely on a candidate’s specific qualifications and talents as its algorithms review and rank thousands of resumes instantly. In fact, RecruitBot pointedly ignores all surface demographic characteristics in its evaluations.

It’s important to remember that RecruitBot won’t magically solve systematic discrimination. For example, just because RecruitBot doesn’t privilege male candidates in a pool of resumes for a STEM position doesn’t mean that the STEM pool isn’t already subject to bias. And even though RecruitBot presents its findings impartially, talent evaluators are under no obligation to agree with our results.

But all that being said, we believe that RecruitBot is a giant step in the right direction. It’s not perfect—nothing is—but using RecruitBot to reduce unconscious bias is a great step to putting your company on the road to a more profitable, equal-opportunity operation.

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