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How AI Eliminates Hiring Biases Across the Entire Recruitment Process

To sustain growth and maintain a competitive edge, companies need to find, hire and keep the best available talent.

An ever-growing body of research demonstrates that certain skills and traits are linked to success in particular industries, positions and companies. But hiring managers don’t always do a good job of connecting those dots. Instead, their decision-making is subject to myriad, typically unconscious, biases.

That’s where artificial intelligence comes in. AI can find what backgrounds correlate with what skill sets, and it can do this without looking through the lens of human bias. Folding those tools and capabilities into a hiring process requires a two-pronged approach: First, companies will need to apply these tools consistently throughout the recruitment process. Then, they will need to educate their recruiting teams and hiring managers on how to use the tools in pursuit of the company’s diversity goals.

With the right tools and a strong strategy, companies can use AI to identify, fight and eliminate hiring biases throughout the process.

Sourcing

Talent acquisition has become a core concern for entire companies, not merely for their HR departments. A study by Michael Stephan, David Brown and Robin Erickson at Deloitte found that 83 percent of executives say talent acquisition is important or very important to their organization, and attracting skilled candidates ranks third overall on the list of companies’ top concerns.

During the sourcing process, AI can steer companies away from the places they’ve traditionally found candidates. Instead, AI can fine-tune the search process for the specific skills and traits the team needs, then cast those parameters out as a much broader net. For instance, AI tools that focus solely on passive candidates are currently available. These tools seek to identify professionals who have the traits to thrive with a certain company and who would be amenable to switching jobs in the right set of circumstances.

These tools can also help eliminate hiring biases by focusing on the traits and data points that actually predict success. For instance, a National Bureau of Economic Research working paper by Brian Jacob and fellow researchers examined the hiring habits of administrators in the Washington, D.C. public school system. Those researchers found that even though SAT scores and GPA were highly correlated with teacher effectiveness, administrators were likely to abandon these measures in favor of unrelated traits, like whether the candidate had gone to college in DC.

Because AI can learn from the datasets it analyzes, these systems can not only focus on traits highly correlated with effectiveness, but also traits that are linked to effectiveness over time. The system can help hiring managers better understand why their own staff succeed on the job while it also helps them source candidates with the same potential for success.

As AI-enabled tools become more commonplace for employers, the same underlying technology is likely to change the way job-seekers look for work, as well, says Scott Singer, president of Insider Career Strategies, LLC. When job-seekers also have access to AI that can help them screen employers and guide their choices, the opportunities for better candidate-company matches are likely to improve.

hiring biases

Applicant Tracking

One of the most difficult tasks for recruiters is candidate matching, or choosing qualified candidates from a vast pool of applicants. Artificial intelligence can make the work easier.

“The applicant tracking system (ATS) — which has traditionally been an immense TA filing cabinet — is being reinvented” by artificial intelligence, say Stephan, Brown and Erickson at Deloitte. An ATS uses keywords and similar data points to analyze resumes that job-seekers submit to the system.

While most ATSs have been able to sort by keyword for some time, modern AI can do more than simply automate word searches. Today’s artificial intelligence can identify patterns in data and make objective observations and even predictions based on what it sees.

The ability to observe, report and predict based on massive datasets allows AI to improve the screening process in several ways. For instance, AI can analyze resumes to gauge a candidate’s adaptability or communication skills. The technology can also democratize hiring by compiling, analyzing and sharing datasets. Recruiters can use this data to compare candidates directly while also building relationships with those candidates to discover information that computers can’t provide.

When integrated with applicant tracking systems, AI tools can seek out certain character traits by looking at past data, such as the candidate’s alma mater or years of experience. Some AI systems can even analyze language traits like pronoun use to make predictions about they ways a candidate interacts with people.

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Screening Interviews

While hiring managers overwhelmingly prefer to hold final interviews in person, AI tools are becoming increasingly common in the screening interview stages.

For instance, AI-enabled chatbots have recently been added to the hiring manager’s toolkit. These chatbots are capable of handling many of the simple, formulaic questions that appear in screening interviews, gathering data from applicants and sorting it for easier analysis by hiring managers. For the applicant, the process feels like having a chat with a friend via text message, which can help reduce stress and promote an improved impression of the company.

Artificial intelligence is also being coupled with video tools in order to help companies better understand candidates’ responses to questions. The tech does this by analyzing candidates’ facial expressions and offering feedback on each candidate’s moods and personality traits.

The video format of these screening interviews allows candidates to complete the task when they feel best capable. The pre-set questions benefit hiring managers by making it easier to compare candidates’ answers directly, and the AI can make better comparisons as well with a standardized collection of data.

Unilever says the technology has also increased the diversity of its hires. “This makes sense: Human recruiters, however well intentioned, are subject to unconscious bias that properly trained AI may be able to avoid,” Zetlin says.

Where Do Hiring Managers Fit In?

The final interview stage is ideal for leveraging the other opportunity AI provides: Knowing when to skip the tech in favor of building human relationships. While AI tools can do a great deal to help eliminate unconscious hiring biases in repetitive tasks like screening resumes or social media profiles, it’s the human connection between candidate and hiring manager that will help both parties determine whether the fit is right.

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