Value Sensitive Design for Fair Online Recruitment: A Conceptual Framework Informed by Job Seekers' Fairness Concerns
Provides a human-centered design framework for fair recruitment systems, but is incremental as it applies existing value sensitive design to a new domain.
This paper develops a conceptual framework for fair online recruitment based on job seekers' fairness concerns identified from Reddit posts, addressing the gap between theoretical fairness and actual user concerns.
The susceptibility to biases and discrimination is a pressing issue in today's labor markets. While digital recruitment systems play an increasingly significant role in human resource management, a systematic understanding of human-centered design principles for fair online hiring remains lacking, particularly considering the gap between idealized conceptualizations of fairness in research and actual fairness concerns expressed by job seekers. To address this gap, this work explores the potential of developing a fair recruitment framework based on job seekers' fairness concerns shared in r/jobs, one of the largest online job communities. Through a grounded theory approach, we uncover four overarching themes of job seekers' fairness concerns: personal attribute discrimination beyond legally protected attributes, interaction biases, improper interpretations of qualifications, and power imbalance. Drawing on value sensitive design, we derive design implications for fair algorithms and interfaces in recruitment systems, integrating them into a conceptual framework that spans different hiring stages.