Prestige and Prejudice: How the Interplay of Recruiting Work and Algorithms Reinforces Social Inequities in Software Engineering

The technology industry has long sought to diversify its workforce. This study evaluates one avenue that works against these efforts: the interaction between recruiter work practices and algorithmic recruiting tools. Through interviews and cognitive walkthroughs with fifteen recruiters, we find that recruiters—often under deadlines and quotas—develop shortcuts (e.g., computer science degrees and employment at prestigious companies) for identifying “typical” software engineers (one of the most sought-after roles in the field) who have a higher chance of being successfully hired. We then analyze the results of searches like those recruiters often conduct in one commonly-used recruitment tool. We see recruiters’ shortcuts also reflected in these results: candidates with computer science degrees, living in expensive tech hubs, and employed at high-profile tech companies are disproportionately favored. Given the lack of demographic diversity in software engineering at prestigious companies, we assert that algorithmically preferencing these factors helps to reify existing stereotypes, impacting the diversity of candidates who are ultimately hired.