The Value of AI-Inferred Facial Personality Traits: Evidence from Chinese Financial Analysts

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study investigates the predictive power of facial Big Five personality traits, inferred by AI, on the earnings forecast accuracy of financial analysts. Contributing to the broader discourse on the relationship between facial personality traits and social outcomes, we examine this link through the lenses of self-fulfilling prophecy effects and genetic/hormonal influences. Utilizing deep neural network analysis of ID photos, we successfully extract personality traits that show significant correlations with job performance: extraversion and conscientiousness positively influence performance, whereas neuroticism has a negative impact. These findings underscore the potential of AI-inferred traits to effectively predict job performance. Moving forward, we plan to refine our deep learning model using alternative related databases, validate the reliability of AI-inferred facial personality traits, and further explore the underlying mechanisms. This research deepens our understanding of how facial personality traits correlate with professional success, offering valuable insights for both scholars and practitioners.

Original languageEnglish
Title of host publicationProceedings - 28th Pacific Asia Conference on Information Systems, PACIS 2024
PublisherPacific Asia Conference on Information Systems
ISBN (Electronic)9781958200124
StatePublished - 2024
Event28th Pacific Asia Conference on Information Systems, PACIS 2024 - Ho Chi Minh City, Viet Nam
Duration: 1 Jul 20245 Jul 2024

Publication series

NameProceedings - 28th Pacific Asia Conference on Information Systems, PACIS 2024

Conference

Conference28th Pacific Asia Conference on Information Systems, PACIS 2024
Country/TerritoryViet Nam
CityHo Chi Minh City
Period1/07/245/07/24

Keywords

  • Personality traits
  • deep learning
  • financial analysts
  • job performance

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