OSS projects create policies for AI contributions to protect quality

You can contribute if you... An Empirical Framework of AI Contribution Policies in OSS

Software Engineering

Summary

Artificial intelligence is changing how people help out with open source software by making it easier to create code and documentation. This makes it possible for more people to contribute, but it also makes it harder for project leaders to judge how trustworthy or skilled contributors are. The authors studied new rules that open source projects are making to manage contributions created with the help of AI. They found these rules aim to keep quality, ensure proper review, protect legal rights, and help new contributors learn. Based on this, the authors developed a framework that helps projects create and understand policies about AI-assisted contributions.

What this means in practice

A survey. It maps existing work.

Authors

Gregorio Robles, Daniel M. German

Abstract

Artificial intelligence is reshaping open source software (OSS) contribution by lowering the cost of producing code, documentation, issue reports, and review interactions. This creates opportunities for broader participation, but also disrupts how maintainers assess contributor effort, competence, and accountability. In response, OSS projects are beginning to regulate AI-mediated contribution through contribution guidelines and other project documentation. This paper presents an empirical study of these emerging policies. We analyze project policies on AI-mediated contributions by evaluating their underlying rationales, rules, and expectations. Our analysis shows that these policies seek to protect scarce maintainer attention, preserve accountability, sustain meaningful review interactions, address legal and quality concerns, and maintain pathways for newcomer learning. Based on these findings, we introduce the AI Contribution Governance Framework, which organizes recurring concerns and governance mechanisms across projects. The framework helps OSS communities develop AI contribution policies and provides researchers with a vocabulary for studying how AI is changing collaborative software production.
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