Understanding User Perceptions of Trustworthiness in E-recruitment Systems
Ogunniye, Gideon, Legastelois, Benedicte, Rovatsos, Michael, Dowthwaite, Liz, Portillo, Virginia, Perez Vallejos, Elvira, Zhao, Jun and Jirotka, Marina (2021) Understanding User Perceptions of Trustworthiness in E-recruitment Systems. IEEE Internet Computing ( Volume: 25, Issue: 6, 01 Nov.-Dec. 2021).
Abstract
Algorithmic systems are increasingly deployed to make decisions that people used to make. Perceptions of these systems can significantly influence their adoption, yet, broadly speaking, users’ understanding of the internal working of these systems is limited. To explore users’ perceptions of algorithmic systems, we developed a prototype e-recruitment system called Algorithm Playground where we offer the users a look behind the scenes of such systems, and provide “how” and “why” explanations on how job applicants are ranked by their algorithms. Using an online study with 110 participants, we measured perceived fairness, transparency and trustworthiness of e-recruitment systems. Our results show that user understanding of the data and reasoning behind candidates’ rankings and selection evoked some positive attitudes as participants rated our platform to be fairer, more reliable, transparent and trustworthy than the e-recruitment systems they have used in the past.
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