Productivity vs. Purpose: Generative AI Enhances Task Performance but Reduces Meaningfulness in Programming

Maren F. Mehler and Kai Krautter

Publications of Darmstadt Technical University, Institute for Business Studies (BWL) from Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL)

Abstract: Generative Artificial Intelligence (GenAI) has become widespread in daily work but present novel challenges for users as previously meaningful tasks can now be completed by GenAI. This study examines the impact of ChatGPT on task performance and perceived meaningfulness in two programming tasks. In an online experiment (n=161) assigning participants to coding or debugging tasks, with and without ChatGPT assistance, we found that using ChatGPT improved task performance, partially because the supported tasks are less difficult. However, using ChatGPT resulted in lower perceived meaningfulness, partly because participants considered the tasks less effortful. Notably, both tasks exhibited slightly different results, indicating that contextual factors may amplify or mitigate the effects. This study emphasizes the dual nature of GenAI integration, balancing enhanced performance with psychological impacts on users. Our findings offer insights for organizations and developers on integrating GenAI, highlighting the importance of incorporating efficiency gains with the meaningfulness of human work.

Date: 2024
New Economics Papers: this item is included in nep-ain, nep-eff and nep-exp
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Persistent link: https://EconPapers.repec.org/RePEc:dar:wpaper:146774

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