Algorithmic Hiring

The use of algorithmic systems — including machine learning and large language models — to source, screen, rank, or select job candidates. Proponents argue algorithmic hiring reduces human bias and scales review; critics show it can amplify bias against disabled, Black, female, and older applicants, particularly when models are trained on historical hiring data that already encodes ableist preferences (e.g., GPT-4 résumé sorters demoting candidates whose CVs mention disability awards or activities).