Algorithmic Monocultures in Hiring
A large-scale study reveals that the widespread use of identical hiring algorithms by major employers creates 'algorithmic monocultures' that exacerbate racial disparities. The research highlights systemic rejection patterns and significant adverse impacts on Black and Asian job applicants.
Why it matters
The findings raise significant legal and ethical questions regarding the use of automated tools in high-stakes employment decisions and potential violations of civil rights.
Paper Code Blog Cite Over 90% of U.S. employers rely on hiring algorithms to screen job applicants. Many different employers use algorithms from the same few vendors. We conduct the largest empirical study of algorithmic hiring with data for 3.4 million real job applicants submitting 4 million applications to 156 employers across 11 market sectors . Every application was assessed by algorithms from a single vendor: we test whether this algorithmic monoculture bottlenecks job opportunities. We are the first to demonstrate large-scale evidence of racial disparities and homogeneous outcomes in high-stakes hiring decisions.
The focus on systemic bias and social justice implications aligns with a critical perspective on corporate technology practices.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in