Highly automated job interviews: Acceptance under the influence of stakes

Abstract

Technological advancements allow the automation of every part of job interviews (information acquisition, information analysis, action selection, action implementation) resulting in highly automated interviews. Efficiency advantages exist, but it is unclear how people react to such interviews (and whether reactions depend on the stakes involved). Participants (N = 123) in a 2 (highly automated, videoconference) × 2 (high‐stakes, low‐stakes situation) experiment watched and assessed videos depicting a highly automated interview for high‐stakes (selection) and low‐stakes (training) situations or an equivalent videoconference interview. Automated high‐stakes interviews led to ambiguity and less perceived controllability. Additionally, highly automated interviews diminished overall acceptance through lower social presence and fairness. To conclude, people seem to react negatively to highly automated interviews and acceptance seems to vary based on the stakes. Open Practices This study was pre‐registered on the Open Science Framework (http://osf.io/hgd5r) and on AsPredicted (https://AsPredicted.org/i52c6.pdf).

Justice perceptions of artificial intelligence in selection

“…There is limited research available regarding applicants' reactions to the use of AI by companies in hiring (Langer, König, & Fitili, 2018; Langer, König, & Papathanasiou, 2019; Lee, 2018; McCarthy et al., 2017) despite the fact that understanding applicant reactions is becoming increasingly important due to AI integration (Black & van Esch, 2020) and the ethical considerations of AI decision making (Leicht‐Deobald et al., 2019). Applicant reactions can be defined as the attitudes, affect, or cognitions applicants might have about a hiring process or selection tools (McCarthy et al., 2017; Ryan & Ployhart, 2000).…”

“…As a crucial dimension of applicant reactions, the justice perspective (Gilliland, 1993) asserts that fairness perceptions directly influence attitudes and behaviors during the selection process and after the hiring decision, including organizational attractiveness, intention to accept a job offer, recommending the employer to others, motivation during the selection process, offer acceptance, and job performance (Bauer, Dolen, Maertz, & Campton, 1998; Hausknecht et al., 2004; Konradt, Garbers, Böge, Erdogan, & Bauer, 2017; McCarthy et al., 2013). However, extant research (e.g., Langer et al., 2018, 2019) has yet to fully examine justice perceptions of the use of AI in the selection, as no research has yet examined the entirety of the justice model (Gilliland, 1993) in the context of AI interviews.…”

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

“…Nowadays, automation based on artificial intelligence and machine learning is more wide reaching and takes over more complex information processing and high-inference information classification tasks assisting humans in many areas of everyday life. For instance, such highly automated information processing and decision support systems support judges at courts (Brennan, Dieterich, & Ehret, 2009), physicians with diagnoses (Bright et al, 2012), and high-stake managerial tasks (Langer, König, & Papathanasiou, 2019;Wesche & Sonderegger, 2019). Within human resource management, current practical developments and recent research point to a future where managers will collaborate with automated systems to work on tasks as varied as scheduling (Ötting & Maier, 2018), personnel selection (Campion, Campion, Campion, & Reider, 2016), and retention management (Sajjadiani, Sojourner, Kammeyer-Mueller, & Mykerezi, 2019).…”

“…Especially in personnel selection (as a specific managerial task), automation has already crucially affected the means of fulfilling a hiring manager's job. For instance, they might be supported by systems gathering applicant information and providing evaluations of candidates based on automatic screening of resumes (Campion et al, 2016) or job interviews (Langer et al, 2019). On the one hand, this potentially increases productivity and allows additional time to work on other tasks (Parasuraman & Manzey, 2010).…”

Editorial‐Current State and the Future of International Journal of Selection & Assessment

“…We have also decided as a new Editorial Board team to embrace the Open Science movement. IJSA was one of the first journals to join the Center for Open Science (https://cos.io) a few years ago, but has not fully implemented the necessary policies and guidelines, although we have already published preregistered reports (e.g., Langer, König & Papathanasiou, ). We will soon update the online submission system to allow author(s) to submit both registered reports and hybrid registered reports (i.e., results‐masked manuscripts), if they wish to do so, and will also revise the submission guidelines accordingly.…”