Artificial intelligence could improve recruitment process
Artificial intelligence could remove some of the latent biases in hiring decisions and help companies recruit more workers from underrepresented groups, according to a recent article by Bloomberg.

The news organization highlights two companies – Stella and Entelo – which use machine learning to identify skills needed for certain jobs. “The AI then matches candidates who have those skills with open positions. The companies claim not only to find better candidates, but also to pinpoint those who may have previously gone unrecognized in the traditional process,” Bloomberg says.

Stella’s founder Rich Joffe says the algorithm reduces hiring biases by assessing candidates only on relevant skills. “The algorithm is only allowed to match based on the data we tell it to look at. It’s only allowed to look at skills, it’s only allowed to look at industries, it’s only allowed to look at tiers of companies,” he says.

Bloomberg reported that Entelo recently released its Unbiased Sourcing Mode, a tool that specifically aims at eliminating common biases in hiring decisions. For instance, the software allows recruiters to hide names, photos, school, employment gaps, and markers of someone’s age, as well as to replace gender-specific pronouns.

“Human decision-making is pretty awful,” notes Solon Borocas, an assistant professor in Cornell’s Information Science department who studies fairness in machine learning. But we shouldn’t overestimate the neutrality of technology, either, he told Bloomberg.

His research has found that machine learning in hiring, much like its use in facial recognition, can result in unintentional discrimination. Algorithms can carry the implicit biases of those who programmed them. Or they can be skewed to favor certain qualities and skills that are overwhelmingly exhibited among a given data set.