AI Policy, Disclosure, and Human in the Loop: How Are Contribution Guidelines Adapting to GenAI?

TL;DR

This study empirically examines how open source projects are adapting their contribution policies to GenAI, revealing prevalent acceptance, disclosure requirements, and human oversight practices.

Contribution

It provides the first empirical analysis of 118 open source AI policies, highlighting current trends and best practices for AI-assisted contributions.

Findings

78% of policies allow GenAI contributions

51% require disclosure of AI-generated code

74% mandate human oversight in contributions

Abstract

Generative AI (GenAI) has recently transformed software development. Due to the ease of generating code, open source projects are experiencing a growth in contributions. To address the rise of GenAI, open source projects have begun implementing policies for AI usage in contributions. However, the extent to which open source specifies whether AI-assisted contributions are allowed or prohibited, along with the best practices for contributors, remains unclear. This paper provides an initial empirical study to explore how open source projects are adapting to GenAI contributions. We analyzed 1,000 popular GitHub repositories and identified 118 AI policies for contributors. Our results show that (1) 78% of the AI policies allow contributions generated with GenAI, while 22% explicitly discourage their use; (2) 51% of the AI policies require the disclosure of AI-generated contributions; and (3) 74% of the AI policies require a human in the loop during contribution. Overall, we find that the majority of the analyzed AI policies are positive regarding the usage of GenAI. However, AI disclosure and human in the loop are fundamental in the contribution process. Finally, we conclude by discussing implications for developers and researchers.