5 papers
Prompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection Settings
Preet Baxi, Jiannan Xu, Jane Yi Jiang +1
Large language models (LLMs) are increasingly used to screen and rank job applicants, creating incentives for candidates to strategically manipulate algorithmic hiring systems. We…
AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights
Jiannan Xu, Gujie Li, Jane Yi Jiang
As artificial intelligence (AI) tools become widely adopted, large language models (LLMs) are increasingly involved on both sides of decision-making processes, ranging from hiring…
Which Demographic Features Are Relevant for Individual Fairness Evaluation of U.S. Recidivism Risk Assessment Tools?
Tin Trung Nguyen, Jiannan Xu, Phuong-Anh Nguyen-Le +4
Despite its constitutional relevance, the technical ``individual fairness'' criterion has not been operationalized in U.S. state or federal statutes/regulations. We conduct a human…
Effort-aware Fairness: Incorporating a Philosophy-informed, Human-centered Notion of Effort into Algorithmic Fairness Metrics
Tin Trung Nguyen, Jiannan Xu, Zora Che +6
Although popularized AI fairness metrics, e.g., demographic parity, have uncovered bias in AI-assisted decision-making outcomes, they do not consider how much effort one has spent…
How May U.S. Courts Scrutinize Their Recidivism Risk Assessment Tools? Contextualizing AI Fairness Criteria on a Judicial Scrutiny-based Framework
Tin Nguyen, Jiannan Xu, Phuong-Anh Nguyen-Le +4
The AI/HCI and legal communities have developed largely independent conceptualizations of fairness. This conceptual difference hinders the potential incorporation of technical fair…