The Invisible Hand of AI Libraries Shaping Open Source Projects and Communities

TL;DR

This paper investigates how the adoption of AI libraries influences open source software projects and communities, revealing measurable differences in development and engagement through large-scale analysis.

Contribution

It provides the first large-scale empirical analysis of AI library adoption in OSS projects, highlighting its impact on development practices and community dynamics.

Findings

AI adoption correlates with increased development activity

AI projects show higher community engagement

Code complexity varies with AI library use

Abstract

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.