Department of Business Development and Technology

Applicant fairness perceptions of a robot-mediated job interview: A video vignette-based experimental survey

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It is well established in the literature that biases (e.g., related to body size, ethnicity, race etc.) can occur during the employment interview and that applicants’ fairness perceptions related to selection procedures can influence attitudes, intentions, and behaviors toward the recruiting organization. This study explores how social robotics may affect this situation. Using an online video vignette-based experimental survey (n=235), the study examines applicant fairness perceptions of two types of job interviews: a face-to-face and a robot-mediated interview. To reduce the risk of socially desirable responses, desensitize the topic, and detect any inconsistencies in the respondents’ reactions to vignette scenarios, the study employs a first-person and a third-person perspective. In the robot-mediated interview, two teleoperated robots are used as fair proxies for the applicant and the interviewer, thus providing symmetrical visual anonymity unlike prior research that relied on asymmetrical anonymity, in which only one party was anonymized. This design is intended to eliminate visual cues that typically cause implicit biases and discrimination of applicants, but also to prevent biasing the interviewer’s assessment through impression management tactics typically used by applicants. We hypothesize that fairness perception (i.e., procedural fairness and interactional fairness) and behavioral intentions (i.e., intentions of job acceptance, reapplication intentions, and recommendation intentions) will be higher in a robot-mediated job interview than in a face-to-face job interview, and that this effect will be stronger for introvert applicants. The study shows, contrary to our expectations, that the face-to-face interview is perceived as fairer, and that the applicant’s personality (introvert vs. extravert) does not affect this perception. We discuss this finding and its implications, and address avenues for future research.
Original languageEnglish
Article number586263
JournalFrontiers in Robotics and AI
Number of pages18
Publication statusPublished - 2020

    Research areas

  • Robot-mediated interview, Fairness perceptions, Implicit biases, Fair proxy, Job interview

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