Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes?

Suen, Hung-Yue; Chen, Mavis Yi Ching; Lu, Shih‐Hao

doi:10.1016/j.chb.2019.04.012

Cited by 124 publications

(59 citation statements)

References 41 publications

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“…In contrast to those findings, Suen, Chen, and Lu (2019) found no differences in perceived fairness between digital interviews that use AI or human rater and synchronize videointerviews among job applicants, although they exhibited lower favorability to digital interviews. These results indicate that applicants perceived computer and AI decisions as similarly trustworthy to humans, thereby not influencing their fairness perceptions (see Ötting, & Maier, 2018).…”

Section: Digital Interviewscontrasting

confidence: 95%

Personnel selection in the digital age: a review of validity and applicant reactions, and future research challenges

Woods

Ahmed

Nikolaou

et al. 2019

European Journal of Work and Organizational Psychology

132

143

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We present a targeted review of recent developments and advances in digital selection procedures (DSPs) with particular attention to advances in internet-based techniques. By reviewing the emergence of DSPs in selection research and practice, we highlight five main categories of methods (online applications, online psychometric testing, digital interviews, gamified assessment and social media). We discuss the evidence base for each of these DSP groups, focusing on construct and criterion validity, and applicant reactions to their use in organizations. Based on the findings of our review, we present a critique of the evidence base for DSPs in industrial, work and organizational psychology and set out an agenda for advancing research. We identify pressing gaps in our understanding of DSPs, and ten key questions to be answered. Given that DSPs are likely to depart further from traditional nondigital selection procedures in the future, a theme in this agenda is the need to establish a distinct and specific literature on DSPs, and to do so at a pace that reflects the speed of the underlying technological advancement. In concluding, we, therefore, issue a call to action for selection researchers in work and organizational psychology to commence a new and rigorous multidisciplinary programme of scientific study of DSPs.

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Section: Digital Interviewscontrasting

confidence: 95%

Personnel selection in the digital age: a review of validity and applicant reactions, and future research challenges

Woods

Ahmed

Nikolaou

et al. 2019

European Journal of Work and Organizational Psychology

132

143

View full text Add to dashboard Cite

show abstract

“…Such a system processes applicant information and could provide hiring managers with rankings of candidates to aid during hiring processes. Other studies have investigated the use of automated job interviews (Naim et al, 2018;Suen, Chen, & Lu, 2019). Those studies argue that it might be possible to automatically process interviews to predict interview performance which would make it feasible to screen thousands of applicants and present an evaluation of the most suitable applicants to hiring managers (Langer, König, & Hemsing, 2020).…”

Section: Background and Development Of Hypothesesmentioning

confidence: 99%

Changing the means of managerial work: effects of automated decision support systems on personnel selection tasks

2020

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To enhance the quality and efficiency of information processing and decision-making, automation based on artificial intelligence and machine learning has increasingly been used to support managerial tasks and duties. In contrast to classical applications of automation (e.g., within production or aviation), little is known about how the implementation of automation for management changes managerial work. In a work design frame, this study investigates how different versions of automated decision support systems for personnel selection as a specific management task affect decision task performance, time to reach a decision, reactions to the task (e.g., enjoyment), and self-efficacy in personnel selection. In a laboratory experiment, participants (N = 122) were randomly assigned to three groups and performed five rounds of a personnel selection task. The first group received a ranking of the applicants by an automated support system before participants processed applicant information (support-before-processing group), the second group received a ranking after they processed applicant information (support-after-processing group), and the third group received no ranking (no-support group). Results showed that satisfaction with the decision was higher for the support-after-processing group. Furthermore, participants in this group showed a steeper increase in self-efficacy in personnel selection compared to the other groups. This study combines human factors, management, and industrial/organizational psychology literature and goes beyond discussions concerning effectiveness and efficiency in the emerging area of automation in management in an attempt to stimulate research on potential effects of automation on managers’ job satisfaction and well-being at work.

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“…Methods such as online applications (Sylva and Mol, 2009), digital interviews (Langer et al, 2017), and gamified assessments (Hawkes et al, 2018) have been found to provide practitioners with easier and faster selection procedures (Woods et al, 2020). While it has been argued that such digital selection procedures may be able to reduce implicit biases in applicant selection (Suen et al, 2019), research suggests that these methods may also replicate some of the biases from the traditional selection procedures (Lievens et al, 2015). To avoid replication of biases, recent research argues that the setup of the selection procedure may require change.…”

Section: Introductionmentioning

confidence: 99%

Applicant Fairness Perceptions of a Robot-Mediated Job Interview: A Video Vignette-Based Experimental Survey

et al. 2020

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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.

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Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes?

Cited by 124 publications

References 41 publications

Personnel selection in the digital age: a review of validity and applicant reactions, and future research challenges

Personnel selection in the digital age: a review of validity and applicant reactions, and future research challenges

Changing the means of managerial work: effects of automated decision support systems on personnel selection tasks

Applicant Fairness Perceptions of a Robot-Mediated Job Interview: A Video Vignette-Based Experimental Survey

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