An increasing number of companies are using AI-assisted recruitment systems that carry significant risks of discrimination. Researchers from the Horizon Europe project Fairness and Intersectional Non-Discrimination in Human Recommendation (FINDHR), including the Information Retrieval Lab at the University of Amsterdam, present new tools, approaches and recommendations to tackle these issues.
The FINDHR initiative highlights that discrimination in automated hiring is not a theoretical concern but a real problem across Europe, affecting candidates with different backgrounds. The project focuses on intersectional discrimination, where combinations of personal characteristics can create compounded barriers.
Research at the IRLab has focused on embedding fairness and non-discrimination into ranking and recommendation algorithms used in recruitment processes. Technical guides and frameworks aim to uphold legal requirements and principles of fairness and transparency.
The freely accessible FINDHR resources include toolkits and guidelines tailored to job seekers, policymakers, product managers and algorithm auditors, HR professionals, and software developers. These materials include impact assessments, auditing frameworks, equality monitoring protocols, and a Software Development Guide for recruitment systems.
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