Purpose

Asynchronous Video Interviews (AVIs) incorporating Artificial Intelligence (AI)-assisted assessment has become popular as a pre-employment screening method. The extent to which applicants engage in deceptive impression management (IM) behaviors during these interviews remains uncertain. Furthermore, the accuracy of human detection in identifying such deceptive IM behaviors is limited. This study seeks to explore differences in deceptive IM behaviors by applicants across video interview modes (AVIs vs Synchronous Video Interviews (SVIs)) and the use of AI-assisted assessment (AI vs non-AI). The study also investigates if video interview modes affect human interviewers' ability to detect deceptive IM behaviors.

Design/methodology/approach

The authors conducted a field study with four conditions based on two critical factors: the synchrony of video interviews (AVI vs SVI) and the presence of AI-assisted assessment (AI vs Non-AI): Non-AI-assisted AVIs, AI-assisted AVIs, Non-AI-assisted SVIs and AI-assisted SVIs. The study involved 144 pairs of interviewees and interviewers/assessors. To assess applicants' deceptive IM behaviors, the authors employed a combination of interviewee self-reports and interviewer perceptions.

Findings

The results indicate that AVIs elicited fewer instances of deceptive IM behaviors across all dimensions when compared to SVIs. Furthermore, using AI-assisted assessment in both video interview modes resulted in less extensive image creation than non-AI settings. However, the study revealed that human interviewers had difficulties detecting deceptive IM behaviors regardless of the mode used, except for extensive faking in AVIs.

Originality/value

The study is the first to address the call for research on the impact of video interview modes and AI on interviewee faking and interviewer accuracy. This research enhances the authors’ understanding of the practical implications associated with the use of different video interview modes and AI algorithms in the pre-employment screening process. The study contributes to the existing literature by refining the theoretical model of faking likelihood in employment interviews according to media richness theory and the model of volitional rating behavior based on expectancy theory in the context of AVIs and AI-assisted assessment.

中文翻译：

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比较异步视频面试和同步视频面试中求职者的欺骗行为（有或没有人工智能辅助评估）

目的

结合人工智能 (AI) 辅助评估的异步视频面试 (AVI) 作为一种就业前筛选方法已变得流行。申请人在面试过程中进行欺骗性印象管理（IM）行为的程度仍不确定。此外，人类检测识别此类欺骗性 IM 行为的准确性是有限的。本研究旨在探讨视频面试模式（AVI 与同步视频面试 (SVI)）和人工智能辅助评估（人工智能与非人工智能）的使用中申请人欺骗性 IM 行为的差异。该研究还调查了视频面试模式是否会影响面试官检测欺骗性 IM 行为的能力。

设计/方法论/途径

作者基于两个关键因素，在四种条件下进行了实地研究：视频访谈的同步性（AVI 与 SVI）以及人工智能辅助评估的存在（人工智能与非人工智能）：非人工智能辅助的 AVI、人工智能-辅助 AVI、非人工智能辅助 SVI 和人工智能辅助 SVI。该研究涉及 144 对受访者和访谈员/评估员。为了评估申请人的欺骗性即时通讯行为，作者结合了受访者的自我报告和面试官的看法。

发现

结果表明，与 SVI 相比，AVI 在所有维度上引发的欺骗性 IM 行为实例均较少。此外，在两种视频采访模式中使用人工智能辅助评估会导致图像创建的范围小于非人工智能设置。然而，研究表明，除了 AVI 中的大量伪造之外，无论使用何种模式，人类采访者都很难检测到欺骗性 IM 行为。

原创性/价值

该研究首次响应了关于视频采访模式和人工智能对受访者造假和采访者准确性影响的研究的号召。这项研究增强了作者对在就业前筛选过程中使用不同视频面试模式和人工智能算法的实际影响的理解。该研究根据媒体丰富性理论完善了就业面试中作假可能性的理论模型，以及基于 AVI 和人工智能辅助评估背景下的期望理论的自愿评级行为模型，对现有文献做出了贡献。