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KCI 등재
Happy Applicants Achieve More: Expressed Positive Emotions Captured Using an AI Interview Predict Performances
( Ji-eun Shin ) , ( Hyeonju Lee )
감성과학 24권 2호 75-80(6pages)
DOI 10.14695/KJSOS.2021.24.2.75
UCI I410-ECN-0102-2022-500-000657826

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.

1. INTRODUCTION
2. METHOD
3. RESULTS
4. DISCUSSION
REFERENCES
[자료제공 : 네이버학술정보]
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