How Recruiters Can Team Up with AI to Reduce Bias

Research shows that bias in hiring practices continues to have a significant impact on who does or doesn’t get hired.

We want to think that experience, education and skills are what drive candidates to stand out. Unfortunately, one survey found that a candidate’s name has a significant impact on the hiring process.

“It was a little shocking,” the researchers said, “to have some of our respondents say outright that they would not consider an applicant, and it was also insightful to see the biases that were present when our respondents viewed the same resumes, with the only difference being the name at the top of the document.”

Biased hiring not only negatively impacts your employer brand; it creates severe risk for an organization. Thankfully, properly using AI-driven sourcing in the recruiting and hiring process can help reduce bias.

AI-driven sourcing can help level the playing field and save you time which can then be used to train recruiters and hiring managers about bias and establish bias-free processes that support your long-term recruiting strategy.

Level the playing field. As organizations seek to recruit and retain diverse candidates, it highlights our natural human tendency towards “affinity bias”—or, in other words, hiring in our image. Careful and thoughtful programming that enables AI-driven sourcing can help an organization remove the bias that may exist when a recruiter sorts through applicants.

Rather than reviewing names, the AI reviews data about relevant skills, experience and background. Likewise, the use of AI in this way helps reduce the time spent combing through resumes and talent pools for a great match.

If you’re hiring based on affinity or any other bias, it will yield a homogenous workforce that can negatively impact your company’s profitability. According to research from McKinsey, companies with the most ethnically diverse teams see benefits. If executive teams are diverse, the study found the organization was 33% more likely to outperform its peers on profitability.

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Use gained time for training about unconscious bias. As one report from Harvard Business Review indicates, unconscious bias is an issue that must be addressed, not only in sourcing but throughout the hiring process. The author relays experiences in which hiring managers reported on whom they wanted to hire, citing “I could easily see myself having beers with them after work” as the reason. These comments weren’t challenged and, unfortunately, appeared to have had an impact on hiring in that organization.

“Internal analyses showed that even though the company had interviewed a higher number of non-white candidates in preliminary rounds, their final hires were still overwhelmingly white.”

To combat bias in hiring, it’s critical to use AI-driven sourcing, but it’s also essential to provide training. The time saved by implementing AI-driven sourcing can be used to train recruiters and hiring managers about how to eliminate unconscious bias in the other areas of the hiring process.

Reduce bias at every stage of the hiring process. Once they’ve been trained about bias and understand how it negatively impacts the hiring process, hiring managers and recruiters can create systems and processes that make it less likely that bias will drive hiring decisions.

When the organization mentioned above understood the use of unconscious bias to make hiring decisions, that’s what they did.

“They start candidate debrief meetings by asking, ‘Where could unconscious bias show up in our decisions today?’ This intervention, along with other process changes, led the team to hire two women leaders.”

Organizational commitment to address issues of bias in the hiring is a vital part of becoming an employer of choice. AI-driven sourcing, unconscious bias training and changes in hiring processes are all essential steps in ensuring you have a diverse workforce to innovate and drive your organization forward.

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Simon Oldham

Simon Oldham
Simon Oldham is the president at QJumpers, a recruitment platform.

Simon Oldham

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