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NEW YORK — A new study by the National Bureau of Economic Research found that test-based hiring algorithms consistently choose better employees than company hiring managers, according to an .

The study, which looked at more than 300,000 hires in service-sector jobs, examined tests which asked questions about technical skills, personality, cognitive skills and job fit, as well as the algorithm that used the tests’ results to produce a three-tiered scaling system for job candidates.

“While hiring algorithms have started to gain popularity as a way to reduce hiring and turnover costs, finding employees who fit better within companies, there’s still a tendency to trust one’s gut over a machine,” the article said.

Green-rated candidates (highest rated) stayed at companies about eight percent longer than their yellow-rated (middle tier) candidate counterparts. The article also said that the less a company adhered to algorithm hiring recommendations, the worse results they found in hired candidates.

“It’s human nature to think that some of that information you’re learning in an interview is valuable,” Harvard Business School Assistant Professor of Entrepreneurship Danielle Li said in the article. “Is it more valuable than the information in the test? In a lot of cases, the answer is no.”

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For the full, original article from Bloomberg, please .