The Invisible Hand of AI Libraries Shaping Open Source Projects and Communities
This research addresses the underexplored problem of how AI integration affects open-source projects and communities, providing evidence-based insights for developers and researchers, though it appears incremental as it applies existing analysis methods to new data.
The study assessed the adoption of AI libraries in Python and Java open-source software projects, analyzing 157.7k repositories to examine impacts on development, technical ecosystems, and community engagement, with expected findings on measurable differences in activity, engagement, and complexity.
In the early 1980s, Open Source Software emerged as a revolutionary concept amidst the dominance of proprietary software. What began as a revolutionary idea has now become the cornerstone of computer science. Amidst OSS projects, AI is increasing its presence and relevance. However, despite the growing popularity of AI, its adoption and impacts on OSS projects remain underexplored. We aim to assess the adoption of AI libraries in Python and Java OSS projects and examine how they shape development, including the technical ecosystem and community engagement. To this end, we will perform a large-scale analysis on 157.7k potential OSS repositories, employing repository metrics and software metrics to compare projects adopting AI libraries against those that do not. We expect to identify measurable differences in development activity, community engagement, and code complexity between OSS projects that adopt AI libraries and those that do not, offering evidence-based insights into how AI integration reshapes software development practices.