AI in software programming: understanding emotional responses to GitHub Copilot

Farjam Eshraghian, Najmeh Hafezieh, F. Farivar, Sergio de Cesare
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Abstract

PurposeThe 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/approachWe 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.FindingsWe 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 implicationsOverall, 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/valueOur 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.
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软件编程中的人工智能:了解对 GitHub Copilot 的情绪反应
目的 人工智能(AI)在专业和知识工作各个领域的应用日益增多。在用户如何将一项技术融入其工作实践中,情感发挥着重要作用。本研究借鉴了人工智能驱动的技术适应性、情感和未来工作等领域的研究成果,以调查知识工作者对在工作中采用人工智能的看法。首先,在对数据进行清理和过滤后,我们采用主题建模法分析了 10,301 名软件程序员发布的 16,130 条推文,以确定他们所表达的情绪。然后,我们对结果主题进行定性分析,以了解驱动这些情绪的刺激特征。最后,我们对推文样本进行了分析,以探究情绪反应是如何随着时间的推移而变化的。研究结果我们发现软件程序员的情绪分为六类:挑战、成就、失落、威慑、怀疑和冷漠。此外,我们还发现这些情绪受四种刺激特征的驱动:人工智能开发、人工智能功能、身份工作和人工智能参与。我们还研究了情绪随时间的变化。结果表明,一旦软件程序员将注意力转向人工智能程序员的能力和功能,并将其与身份工作联系起来,消极情绪就会转变为更积极的情绪。关于人工智能在高技能工作中的作用的讨论刚刚开始,知识工作者普遍对人工智能持矛盾态度,与此形成鲜明对比的是,我们发现随着时间的推移和与人工智能接触的增多,知识工作者表现出更多的积极情绪。此外,本研究还揭示了职业认同在导致对人工智能产生更多积极情绪方面所起的作用,因为知识工作者认为这种技术是扩展其身份的一种手段,而不是对其身份的一种威胁。
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