Do hiring algorithms prevent bias or amplify it and how to get it right? Recruiting News and Views @ RecruitingDaily

Often managers assume that because the software is devoid of emotions (unlike humans), using them would mean the complete removal of personally-motivated bias from the hiring process. Any application of AI (Artificial Intelligence) or Machine Learning (ML) learns from the existing data fed to it. This raises concerns such as an amplification of pre-existing bias in the data that have made hiring managers approach them with caution. Amazon's experiment into an AI-based recruiting system was scrapped after it started penalizing resumes that included the term "women's" or names of women's colleges. Essentially, the software taught itself to prefer resumes of male candidates over those of female candidates.