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논문 리스트

2021
Happy Applicants Achieve More: Expressed Positive Emotions Captured Using an AI Interview Predict Performances Happy Applicants Achieve More: Expressed Positive Emotions Captured Using an AI Interview Predict Performances
한국감성과학회
신지은
논문정보
Publisher
감성과학
Issue Date
2021-06-30
Keywords
-
Citation
-
Source
-
Journal Title
-
Volume
24
Number
2
Start Page
75
End Page
80
DOI
ISSN
12268593
Abstract
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.

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