Resume Screening

AI-powered resume screening tools automatically evaluate resumes against job requirements, producing scores, rankings, or pass/fail decisions that determine which candidates advance in the hiring pipeline. These tools use natural language processing to extract information from resumes and machine learning models to predict candidate suitability. Resume screening is one of the highest-impact applications of AI in hiring because it operates at the top of the funnel, affecting the largest number of candidates. A biased resume screener can systematically exclude qualified candidates from protected groups before any human reviewer sees their application. Common sources of bias in resume screening include: name-based discrimination (correlating candidate names with race or gender), education bias (preferring certain institutions that correlate with socioeconomic status), experience gap penalties (disproportionately affecting women and caregivers), and keyword bias (favoring terminology associated with certain demographic groups). Resume screening tools are classified as AEDTs under NYC LL144 and as high-risk AI under the EU AI Act.