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Bias in Hiring, Can It Be Minimized? How AI is Making Us More Human

Mike Fitzsimmons, CEO & Co-Founder, Crosschq

Mike Fitzsimmons, CEO & Co-Founder, Crosschq

Implicit bias - everyone has it, even people with avowed commitments to impartiality such as judges - are learned stereotypes that are unintentional yet ingrained in our beliefs about people or things. As defined by Ohio State University, these attitudes “affect our understanding, actions, and decisions in an unconscious manner. These biases, which encompass both favorable and unfavorable assessments, are activated involuntarily and without an individual’s awareness or intentional control...and do not necessarily align with our declared beliefs or even reflect stances we would explicitly endorse.”

But there are many types of unconscious biases; perception bias, halo effect, confirmation bias, groupthink, and more. It can be very hard to identify, but the eruption most often happens when you have a homogenous workforce. When the majority of employees look the same, dress the same, and socialize together, and when leadership leans heavily toward one sex or race, bias’ have probably already spun out of control. 

The one I most often look for is on hiring teams. When I sit in with a group, and we get to the culture portion of candidate reviews, I look for those that say they want a culture fit or that a candidate doesn’t seem to align with our company’s values. It’s a red flag, as a diverse team is built by adding to the culture, not having all employees fit into the existing culture. Also, with people data, you want to look at DEI data related to your employee population. Pay raises and promotions are a good example. You want to ensure that minority groups are getting promoted at the same rate as the majority and their raises are equivalent. These are obvious signs but often not realized until it’s too late, and bias has gone from emerging in your enterprise to rampant across your enterprise.

What if there was a way to mute these biases?

What if we could remove bias from what some might consider the most important step of the hiring process by using AI? What if AI could prevent our human tendencies that can, at times, inadvertently get in the way of creating a level playing field for all?

"We have a moral obligation to hire, build teams and companies, and manage people the right way.  We all need to take unconscious bias personally because it hurts real people, not just teams and companies’ bottom lines"

At Crosschq, we work to remove implicit bias, specifically in the reference check piece of the hiring puzzle. Some examples? Women are hired 9% more when companies use Crosschq, and Upwork increased diversity hires by 32% with this technology.

How Does Implicit Bias Happen?

Implicit bias can unintentionally creep into the notes of the hiring manager - perhaps the sound of the referral’s voice, the way they string sentences together - all of that can play into what gets evaluated about that candidate. By contrast, Crosschq’s AI-driven, Stanford University developed survey provides a series of multiple-choice questions, many of which are the same, just asked in different ways, as you’d see on a personality test. The survey elicits responses you wouldn’t typically get from a traditional phone interview.

Interestingly, we’re seeing some companies perform reference checks at the very start of the hiring process because they see the benefits of removing bias early on. Rather than pulling that data after weeks of interviews, collecting that data not only removes bias, but it saves time and money.

One additional benefit - It also helps the candidate know right from the start if the job is a good fit based on how the references respond.

We all know that diverse teams perform better, and better performance leads to improved business outcomes. But it’s the people that matter. We have a moral obligation to hire, build teams and companies, and manage people the right way. People who are or perceive themselves to be on the wrong side of a bias feel alienated. Then they withhold ideas and solutions. They don’t refer peers they believe are talented to their company. Obviously, this hurts the company, but it brings that person stress, lowers their emotional engagement in non-work situations, and can lead to serious depression. That depression can ruin their home life, family, and more, so much more than their career. We all need to take unconscious bias personally because it hurts real people, not just teams and companies’ bottom lines.

Is AI the future to making us more human, less biased in a world that seems to be lacking in that lately? Perhaps. But at the very least, it’s a step in the right direction.

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