One of the factors often cited as contributing to racial and gender disparities in the workplace is discrimination in the hiring process. This could come in the form of explicit discrimination against women or people of color by a hiring manager.
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But, more often, it comes in the form of implicit bias, where humans are unaware that they are subconsciously making judgments about others based on perceived differences.
Artificial Intelligence to the Rescue?
Artificial intelligence (AI) has been touted as a potential means of eliminating—or at least minimizing—the human bias inherent in the recruitment process. After all, a computer can’t be biased, right? You might be surprised. Sometimes, unintended consequences occur even when processes are driven by objective technologies.
Biased Tech
Consider, for example, Amazon’s new recruitment engine, which was started in 2014. “The experimental solution used artificial intelligence to rate candidates’ resumes to identify top talent,” says one expert. “However, shortly after the solution was tested, the team found that the system was not rating candidates in a gender-neutral way. The algorithm, like any deep learning algorithm, relied on training with historical data. Unfortunately, the pre-existing real-world data embedded within it had patterns that exhibited gender bias, which the AI algorithm eventually incorporated into its functioning.”
The big takeaway here is that even technological solutions are subject to the impacts of human bias, specifically because these systems often rely on historical data that may be bias driven.
Proceed with Caution
In addition to introducing the creators’ inherent biases into the algorithms intended to eliminate such bias, some argue that we don’t fully understand these proposed solutions well enough at this point to understand their true impact.
While some believe that these technologies may promise to remove human bias from the hiring process, they could actually be introducing more. According to a new report from Team Upturn, a Washington, DC-based public advocacy research group, the rapid growth of these technologies has outpaced understanding of them by both employers and regulators.
There may well be a place for AI in eliminating bias in the hiring process. However, recent examples and attempts at doing so haven’t proved to be the resounding successes that many had hoped.