Generative artificial intelligence (AI) has opened the possibility of automated content production, including coding in software development, which can significantly influence the participation and performance of software developers. To explore this impact, we investigate the role of GitHub Copilot, a generative AI pair programmer, on software development in open-source community, where multiple developers voluntarily collaborate on software projects. Using GitHub's dataset for open-source repositories and a generalized synthetic control method, we find that Copilot significantly enhances project-level productivity by 6.5%. Delving deeper, we dissect the key mechanisms driving this improvement. Our findings reveal a 5.5% increase in individual productivity and a 5.4% increase in participation. However, this is accompanied with a 41.6% increase in integration time, potentially due to higher coordination costs. Interestingly, we also observe the differential effects among developers. We discover that core developers achieve greater project-level productivity gains from using Copilot, benefiting more in terms of individual productivity and participation compared to peripheral developers, plausibly due to their deeper familiarity with software projects. We also find that the increase in project-level productivity is accompanied with no change in code quality. We conclude that AI pair programmers bring benefits to developers to automate and augment their code, but human developers' knowledge of software projects can enhance the benefits. In summary, our research underscores the role of AI pair programmers in impacting project-level productivity within the open-source community and suggests potential implications for the structure of open-source software projects.

翻译：生成式人工智能（AI）开启了自动化内容生产的可能性，包括软件开发中的编码，这可能显著影响软件开发者的参与度和表现。为探究这一影响，我们研究了GitHub Copilot（一种生成式AI结对编程工具）在开源社区软件开发中的作用，在开源社区中，多位开发者自愿协作于软件项目。利用GitHub的开源代码库数据集和广义合成控制方法，我们发现Copilot将项目级生产力显著提升了6.5%。深入探究后，我们剖析了驱动这一改进的关键机制。我们的研究结果显示，个体生产力提高了5.5%，参与度提高了5.4%。然而，与此相伴的是集成时间增加了41.6%，这可能是由于更高的协调成本所致。有趣的是，我们还观察到开发者之间的差异化效应。我们发现，核心开发者通过使用Copilot获得了更大的项目级生产力提升，在个体生产力和参与度方面比边缘开发者受益更多，这很可能源于他们对软件项目更深入的熟悉度。我们还发现，项目级生产力的提升并未伴随代码质量的变化。我们得出结论，AI结对编程工具为开发者带来了自动化与增强代码的益处，但人类开发者对软件项目的了解可以增强这些益处。总之，我们的研究强调了AI结对编程工具在影响开源社区内项目级生产力方面的作用，并暗示了其对开源软件项目结构的潜在影响。