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