Claire Cain Miller in The New York Times:
Hiring and recruiting might seem like some of the least likely jobs to be automated. The whole process seems to need human skills that computers lack, like making conversation and reading social cues. But people have biases and predilections. They make hiring decisions, often unconsciously, based on similarities that have nothing to do with the job requirements — like whether an applicant has a friend in common, went to the same school or likes the same sports. That is one reason researchers say traditional job searches are broken. The question is how to make them better. A new wave of start-ups — including Gild, Entelo, Textio, Doxa and GapJumpers — is trying various ways to automate hiring. They say that software can do the job more effectively and efficiently than people can. Many people are beginning to buy into the idea. Established headhunting firms like Korn Ferry are incorporating algorithms into their work, too.
If they succeed, they say, hiring could become faster and less expensive, and their data could lead recruiters to more highly skilled people who are better matches for their companies. Another potential result: a more diverse workplace. The software relies on data to surface candidates from a wide variety of places and match their skills to the job requirements, free of human biases. “Every company vets its own way, by schools or companies on résumés,” said Sheeroy Desai, co-founder and chief executive of Gild, which makes software for the entire hiring process. “It can be predictive, but the problem is it is biased. They’re dismissing tons and tons of qualified people.”