PopResume: Causal Fairness Evaluation of LLM/VLM Resume Screeners with Population-Representative Dataset

This collection of recent CS/AI papers highlights systemic risks and governance gaps across algorithmic decision-making, fairness, and deployment of advanced AI. Key contributions: PopResume — a 60.8K population-representative resume dataset enabling path-specific (PSE) causal fairness audits that reveal discrimination patterns masked by outcome-level metrics; a call for evidentiary rights and counterfactual interrogation to enable meaningful contestation of algorithmic decisions; analyses arguing for a strengthened EU-level AI agency and rights-based implementation of the EU AI Act; an audit—