Personality matters : predicting the acceptance of generative artificial intelligence through personality traits and job insecurity

• Autor(a) principal: Tassone, Debora
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.14/42713
• topic: Artificial intelligence; Technology acceptance model; Five­factor model; Job insecurity; Inteligência artificial; Modelo de aceitação da tecnologia; Modelo de cinco factores; Insegurança no emprego; Domínio/Área Científica::Ciências Sociais::Economia e Gestão

Generative artificial intelligence (GAI) has the potential to fundamentally change humans’ lives, organizations, and industries by being able to create new content, expanding AI’s capabilities to areas of production that were previously exclusively human. To ensure a successful implementation, human acceptance of GAI is crucial. This thesis aims to find out if personality traits predict acceptance of GAI in the workplace. As GAI may be used to automate processes and replace humans, this thesis also investigates the influence of job insecurity on the acceptance of GAI and the influence of personality traits on job insecurity. This thesis’ quantitative study revealed that highly neurotic participants perceive GAI as less useful and less easy to use, compared to participants who are low in neuroticism. Moreover, participants perceived job insecurity considering the potential applications of GAI as rather low. Considering the low perceived job insecurity and rather high number of participants who did not use GAI frequently, participants might lack awareness and knowledge of application possibilities. These findings contribute to existing research on the relevance of personality traits in predicting the acceptance of intelligent technologies and provide guidance for recruitment and training of employees for positions where the use of GAI is crucial.