Hiring feels like a pretty touchy feely process. Sure, you assess a candidate's experience and character, but a lot of the final call often comes down to gut instinct. But does applying human intuition to the process actually make it better?
Not if a new study from the National Bureau of Economic Research is to be believed. The research, conducted by a team out of the University of Toronto, Harvard, and Yale, looked at data on 300,000 hires for low-skilled jobs such and call center employees with high turnover. The team examined how the employees picked by an algorithm compared to those chosen by a human hiring manager.
The computer was the clear winner. While both groups were equally productive once hired, those chosen by the algorithm stuck around on average 15 percent longer.
Michael Hoffman, a member of the research team and professor at the University of Toronto, puts the results down to hubris among hiring managers. "People tend to think [candidates] are better than they actually are," he told Boston.com. Not only are managers' gut instincts often excessively optimistic, algorithms don't discriminate. Humans sadly often do.
Should computers do more hiring?
So does that mean more and more hiring decisions should be taken over by computers? You might object that while an algorithm can do a fine job of picking a person for a low-skilled post, it would be much harder to design an effective screen for a more highly skilled position.
But Danielle Li, a professor at Harvard Business School and co-author of the study, thinks the idea of using algorithms might be more broadly applicable. "She'd be eager to see how the results translate toward people making more complicated decisions in the workplace, like doctors prescribing treatments," reports Boston.com "It's natural to think you're getting good information from personal interactions," she's quoted as saying, "but is that really better than statistical information from tests? In most cases, that's not true."
Still no one is suggesting we turn hiring decisions over to computers entirely. "Relegating people--and the firms they work for--to data points focuses only on the success of firms in terms of productivity and tenure, and that might be a shallow way of interpreting what makes a company successful," warns Gillian B. White in The Atlantic. "Firms that are populated only by high-achieving test takers could run the risk of becoming full of people who are all the same--from similar schools, or with the same types of education, similar personality traits, or the same views." And that would certainly be an innovation killer.
The right conclusion isn't to hand over hiring to algorithms, but to cultivate a healthier respect for computer-generated recommendations among managers. You might think your gut can do better than a computer, but most of the time you're probably wrong. So if you have a hiring test at your disposal, bear that in mind.
Would you let an algorithm choose who your company hires?