2021
By Anne Kroon and Toni van der Meer
Algorithms are fundamentally transforming how organizations recruit job candidates. The current project investigates the extent to which algorithmically-driven resume search engines inhibit or facilitate gender and age inequality in the recruitment process. The novelty of the project lies in tracing the influence of hidden (in addition to manifest) features that may implicitly signal social membership, such as variations in writing style, work experience, and hobbies listed. The potential for inequality is especially critical for hidden features—as they are arguably more difficult to identify and may therefore affect ranking despite explicit efforts to debias training data and algorithms.