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Happy Applicants Achieve More: Expressed Positive Emotions Captured Using an AI Interview Predict Performances KCI 등재

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감성과학 (Korean Journal of the science of Emotion & sensibility)
한국감성과학회 (The Korean Society For Emotion & Sensibility)
초록

Do happy applicants achieve more? Although it is well established that happiness predicts desirable work-related outcomes, previous findings were primarily obtained in social settings. In this study, we extended the scope of the "happiness premium" effect to the artificial intelligence (AI) context. Specifically, we examined whether an applicant's happiness signal captured using an AI system effectively predicts his/her objective performance. Data from 3,609 job applicants showed that verbally expressed happiness (frequency of positive words) during an AI interview predicts cognitive task scores, and this tendency was more pronounced among women than men. However, facially expressed happiness (frequency of smiling) recorded using AI could not predict the performance. Thus, when AI is involved in a hiring process, verbal rather than the facial cues of happiness provide a more valid marker for applicants' hiring chances.

목차
Abstract
1. INTRODUCTION
2. METHOD
    2.1. Subjects
    2.2. Procedure
    2.3. Measurement
3. RESULTS
4. DISCUSSION
REFERENCES
저자
  • Ji-eun Shin(Department of psychology, Chonnam National University) Corresponding author
  • Hyeonju Lee(Psychological solution planning part, MIDAS IT)