From OSS to Open Source AI: an Exploratory Study of Collaborative Development Paradigm Divergence
Hengzhi Ye, Minghui Zhou

TL;DR
This study compares traditional open source software development with open source AI model development, revealing significant differences in collaboration practices, openness, and user innovation through extensive data analysis and interviews.
Contribution
It provides the first comprehensive quantitative and qualitative analysis of the divergence in collaborative paradigms between OSS and open source AI models.
Findings
OSM exhibits lower collaboration intensity than OSS.
OSM shows less openness in direct contributions but maintains knowledge exchange.
OSM favors user-innovation over collaborative improvement.
Abstract
AI development is embracing open-source paradigm, but the fundamental distinction between AI models and traditional software artifacts may lead to a divergent open-source development paradigm with different collaborative practices, which remains unexplored. We therefore bridge the knowledge gap by quantifying and characterizing the differences in the collaborative development paradigms of traditional open source software (OSS) and open source AI models (OSM), and investigating the underlying factors that may drive these distinctions. We collect 1,428,792 OSS repositories from GitHub and 1,440,527 OSM repositories from HF Hub, and conduct comprehensive statistical, social network and content analyses to measure and understand the differences in collaboration intensity, collaboration openness, and user innovation across the two development paradigms, complementing these quantitative…
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