Age Bias: A Tremendous Challenge for Algorithms in the Job Candidate Screening Process

Abstract

As societies grow older, a growing percentage of workers over the traditional retirement age are choosing to remain in the workforce. However, age discrimination against older workers seeking new job opportunities is prevalent. We conducted a study that asked participants to rate resumes of job candidates from various backgrounds for an IT job position. We found age bias, or ageism, in hiring decisions is implicit and more prevalent than other well-reported forms of bias, such as race or gender biases, yet ageism is also far more difficult for job candidate search algorithms to ignore. In this paper, we examine the challenges of age biases in job hiring algorithms and discuss various steps that can be taken to mitigate them.