To Hire the Right Job Candidate, Humans and Machines Should Clear Up This Simple Miscommunication

Nearly every Fortune 500 company now uses some form of artificial intelligence to help them hire the best talent by screening resumes or analyzing test performance. But these AI hiring tools are probably spitting out worse candidates than hiring managers expect, according to new research.

The weakness comes down to a simple case of human-machine miscommunication: The AI thinks it is picking someone to hire, but the hiring manager just wants a list of promising candidates to interview. 

“When we ask these algorithms to select the 10 best resumes, we know we are not directly hiring these 10 people. We know there is a second stage of interviewing, but the AI doesn’t know that,” said Heng Xu, a professor of management in the University of Florida’s Warrington College of Business and lead author of the new study. 

“If you don’t specify that there are additional steps, the AI system might select 10 candidates that are good, but safe, choices. But if you tell the AI system there will be another round of screening by people, it might suggest different, and potentially stronger, candidates,” Xu added.

Xu and her co-author, UF management professor Nan Zhang, developed a new algorithm that accounts for the realities of the hiring process. In a test using data on thousands of employees from a Fortune 500 company, the improved algorithm saved 11% on human interviewing costs while meeting goals for identifying high-quality applicants and avoiding bias. 

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