Dear Diary: A randomized controlled trial of Generative AI coding tools in the workplace
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913561661407232 |
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| author | Butler, Jenna Suh, Jina Haniyur, Sankeerti Hadley, Constance |
| author_facet | Butler, Jenna Suh, Jina Haniyur, Sankeerti Hadley, Constance |
| contents | Generative AI coding tools are relatively new, and their impact on developers extends beyond traditional coding metrics, influencing beliefs about work and developers' roles in the workplace. This study aims to illuminate developers' preexisting beliefs about generative AI tools, their self perceptions, and how regular use of these tools may alter these beliefs. Using a mixed methods approach, including surveys, a randomized controlled trial, and a three week diary study, we explored the real world application of generative AI tools within a large multinational software company. Our findings reveal that the introduction and sustained use of generative AI coding tools significantly increases developers' perceptions of these tools as both useful and enjoyable. However, developers' views on the trustworthiness of AI generated code remained unchanged. We also discovered unexpected uses of these tools, such as replacing web searches and fostering creative ideation. Additionally, 84 percent of participants reported positive changes in their daily work practices, and 66 percent noted shifts in their feelings about their work, ranging from increased enthusiasm to heightened awareness of the need to stay current with technological advances. This research provides both qualitative and quantitative insights into the evolving role of generative AI in software development and offers practical recommendations for maximizing the benefits of this emerging technology, particularly in balancing the productivity gains from AI-generated code with the need for increased scrutiny and critical evaluation of its outputs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_18334 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dear Diary: A randomized controlled trial of Generative AI coding tools in the workplace Butler, Jenna Suh, Jina Haniyur, Sankeerti Hadley, Constance Software Engineering D.2.3 Generative AI coding tools are relatively new, and their impact on developers extends beyond traditional coding metrics, influencing beliefs about work and developers' roles in the workplace. This study aims to illuminate developers' preexisting beliefs about generative AI tools, their self perceptions, and how regular use of these tools may alter these beliefs. Using a mixed methods approach, including surveys, a randomized controlled trial, and a three week diary study, we explored the real world application of generative AI tools within a large multinational software company. Our findings reveal that the introduction and sustained use of generative AI coding tools significantly increases developers' perceptions of these tools as both useful and enjoyable. However, developers' views on the trustworthiness of AI generated code remained unchanged. We also discovered unexpected uses of these tools, such as replacing web searches and fostering creative ideation. Additionally, 84 percent of participants reported positive changes in their daily work practices, and 66 percent noted shifts in their feelings about their work, ranging from increased enthusiasm to heightened awareness of the need to stay current with technological advances. This research provides both qualitative and quantitative insights into the evolving role of generative AI in software development and offers practical recommendations for maximizing the benefits of this emerging technology, particularly in balancing the productivity gains from AI-generated code with the need for increased scrutiny and critical evaluation of its outputs. |
| title | Dear Diary: A randomized controlled trial of Generative AI coding tools in the workplace |
| topic | Software Engineering D.2.3 |
| url | https://arxiv.org/abs/2410.18334 |