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Can an Algorithm Hire Better Than a Human?

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.

Read more: Can an Algorithm Hire Better Than a Human? – The New York Times

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CONVERSATIONS

  1. Thanks. This debate goes way back… at least to the early 80s (at my age that’s not way back, really, more like “yesterday”). The advantage, as you point out, the computer doesn’t make mistakes of logic, nor does it “have a bad day” (let’s bracket the Ctrl-Alt-Del syndrome). What the computer cannot do is suspend it’s rules when they don’t apply. Any algorithm that could account for all factors would be so large as to be “unrunnable.” Given that we don’t need “all” factors to increase our hit-rate and decrease our miss-rate, this may be a quibble, and human interviewers certainly don’t cover all factors. What seasoned humans CAN do is suspend their rules when reasonable, learn (in the human sense), and create new rules. What goes beyond this discussion is the whole topic of “is the best human thinking rule-based at all.”

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