The question to ask if you’re introducing a hiring algorithm is whether it is outperforming the human processes—not if it’s perfect. And when there are biases, what are the sources, and can they be corrected, for example, by adding more training data? How much can we debias as humans versus how much can we improve the different systems?
A vast majority of large companies today are using some form of automated resume screening. It’s important for agencies like the US Equal Employment Opportunity Commission and the Labor Department to look at the claims versus the results. There hasn’t been enough nuanced conversation about the sources of the risks and whether they can be corrected.