The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot

Generative AI holds great promise for reshaping software development. We examine the impact of GitHub Copilot, a generative AI pair programmer, on collaborative open-source software (OSS) development, where developers voluntarily contribute and collaborate on projects. Using GitHub’s proprietary Copilot usage data combined with public OSS data from GitHub, we find that Copilot increases project-level code contributions by expanding developer participation and increasing code contributed by individual developers. However, these gains lead to increase in time to coordinate, review and integrate code. Overall, Copilot still increases the amount of code that is integrated in a timely manner, but the benefits are unevenly distributed. Core developers (highly active contributors) gain more from Copilot, whereas contributions from peripheral developers (occasional contributors) require relatively more coordination time. These findings suggest that as AI increasingly reduces the cost of producing code, coordination and integration may become more important constraints in software development. Organizations and OSS communities should therefore complement AI adoption with governance structures and coordination processes that facilitate code integration and support peripheral developers. More broadly, as AI increasingly automates routine coding activities, organizational processes and team structures may become critical determinants of the returns to generative AI adoption.

• 저널Information Systems Research
• 토픽Scientific Computing and Data Management · Information Systems and Management
• DOI10.1287/isre.2024.1361
• 저자Fangchen Song, Ashish Agarwal, Wen Wen