AI in software programming

Understanding emotional responses to GitHub Copilot

Dados Bibliográficos

ID7155698
AutoresFarjam Eshraghian (0000-0002-0729-684X, University of Tasmania), Najmeh Hafezieh (0000-0002-3912-2895), Farveh Farivar (0000-0001-8413-8143, University of Tasmania), Sergio De Cesare (0000-0002-2559-0567, University of Tasmania)
Ano2025
Volume38
Fascículo4
Páginas1659-1685
Data de publicação2025-05-19
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoInformation Technology and People (JOURNAL)
Identificadores do periódicoISSN: 0959-3845 • E-ISSN: 1758-5813
EditoraEmerald (PUBLISHER)
DOI10.1108/itp-01-2023-0084
OpenAlexW4393452481
IdiomaEN
Citações recebidas5
Referências citadas56

Purpose The applications of Artificial Intelligence (AI) in various areas of professional and knowledge work are growing. Emotions play an important role in how users incorporate a technology into their work practices. The current study draws on work in the areas of AI-powered technologies adaptation, emotions, and the future of work, to investigate how knowledge workers feel about adopting AI in their work. Design/methodology/approach We gathered 107,111 tweets about the new AI programmer, GitHub Copilot, launched by GitHub and analysed the data in three stages. First, after cleaning and filtering the data, we applied the topic modelling method to analyse 16,130 tweets posted by 10,301 software programmers to identify the emotions they expressed. Then, we analysed the outcome topics qualitatively to understand the stimulus characteristics driving those emotions. Finally, we analysed a sample of tweets to explore how emotional responses changed over time. Findings We found six categories of emotions among software programmers: challenge, achievement, loss, deterrence, scepticism, and apathy. In addition, we found these emotions were driven by four stimulus characteristics: AI development, AI functionality, identity work, and AI engagement. We also examined the change in emotions over time. The results indicate that negative emotions changed to more positive emotions once software programmers redirected their attention to the AI programmer's capabilities and functionalities, and related that to their identity work. Practical implications Overall, as organisations start adopting AI-powered technologies in their software development practices, our research offers practical guidance to managers by identifying factors that can change negative emotions to positive emotions. Originality/value Our study makes a timely contribution to the discussions on AI and the future of work through the lens of emotions. In contrast to nascent discussions on the role of AI in high-skilled jobs that show knowledge workers' general ambivalence towards AI, we find knowledge workers show more positive emotions over time and as they engage more with AI. In addition, this study unveils the role of professional identity in leading to more positive emotions towards AI, as knowledge workers view such technology as a means of expanding their identity rather than as a threat to it

Programming language · Software engineering · AI in Service Interactions · Computer Science · Ethics and Social Impacts of AI · Online Learning and Analytics · Psychology · Software