More human-likeness, less self-disclosure? Avatars' form realism and job applicants' self-disclosure in AI interviews

• Main Authors: XU, Yamin, SIAU, Keng, NAH, Fiona Fui-hoon
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: AI interview; Avatar; Form realism; Trustworthiness; Fairness; Privacy; Self-disclosure; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9993
• Institution: Singapore Management University

The rise of AI in recruitment promises to revolutionize how organizations evaluate job candidates. The quality of AI evaluations is determined by the input data, which depends on job applicants' self-disclosure. However, little is known about how the design elements of AI interview systems, particularly avatar interviewers, influence job applicants' self-disclosure during these interactions. This study aims to address this gap by specifically focusing on how the form realism of avatar interviewers affects job applicants' self-disclosure through their perceptions. In addition, the study will examine the effects of job type as a moderator. Drawing on the Stimulus-Organism-Response (S-O-R) model, this study proposes hypotheses on the influence of avatar form realism on selfdisclosure. We will design and conduct experiments to test the hypotheses and draw conclusions. This research will improve understanding of avatar design's influence on self-disclosure in AI interviews and provide valuable knowledge for organizations using AI in recruitment.