Can Hiring Algorithms Make Companies More Racially Diverse?

United States – June 23, 2015, 12:00 PM

"Humans are biased decision makers. One well-known and troubling example of this is the tendency for interviewers to hire candidates who remind them of themselves, resulting in workplace homogeneity," reports Bourree Lam in The Atlantic magazine. "Some recruiters are hoping that software can somehow compensate for human failings."

The June 22 article "For More Workplace Diversity, Should Algorithms Make Hiring Decisions?" looks at a new study by Infor that finds algorithmic hiring has improved diversity at companies that use its Infor Talent Science software.

Here are excerpts:
"One proposed solution is to try to remove some of those biases with systematic analysis of data-or in other words: Use an algorithm. Companies administer personality tests to candidates during screening, then use data analysis to determine its ideal hires.

"One study of algorithmic hiring found that a simple equation was significantly better than humans at identifying high-performing employees. The result held across different industries and levels of employment, and the researchers attributed the result to humans paying too much attention to inconsequential details and using information about candidates inconsistently."

Infor removes bias from the hiring process, helping companies improve diversity, through the application of Talent Science. By collecting behavioral information from top performers, Infor is able to use a predictive model to determine which prospective employees will make the best fit for given roles, without regard for racial or ethnic background.

Infor found an average increase of 26% in African Americans and Hispanics across a broad spectrum of industries by analyzing data on 50,000 hires made by Infor Talent Science customers.

"'What we've found is regardless of [the industry], whether it's restaurants, retail, call centers-it actually increases the diversity of the population,' says Jason Taylor, Infor's chief scientist for human capital management. In Infor's forthcoming report, they found that using an algorithm to help with hiring increased their wholesale clients' Hispanic hires by 31 percent. For their restaurant clients, African American hires increased by 60 percent.

"'What a systematic process does is it knows no color, no race, no ethnicity,' says Taylor. 'When [a hiring manager] doesn't know a person and they don't know what to look for, they basically hire people like themselves. It's "We have something in common," or "Oh, I like you," then it's "Okay you're hired." What this does is it provides them with an objective piece of information that shows the probability that they're going to be successful in the role. So it helps to qualify that pool.'"

Read the complete article on TheAtlantic.com.

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