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Some companies have begun relying more on computer-administered tests than human interviewers to find the best applicants. New research by Harvard Business School Assistant Professor Danielle Li and colleagues suggests that in this case, we may have to score one for the machine.
Job testing was popular in the 1950s and ’60s as a way of sifting through bulging applicant pools. After researchers questioned its reliability, testing fell out of use in favor of personal interviews. Now, with the emergence of big data, machine testing has come back in sophisticated new forms.
Testing companies use a rash of custom-designed assessments, including personality tests, skills assessments, math and logic problems, and judgment tests, on hypothetical work situations. Results are measured using proprietary algorithms and machine learning to predict which candidates will do best in a particular position.
Via The Learning Factor
In many cases, it may behoove companies to rely more on computer-administered tests than human interviewers to find the best job candidates.