This work analyzes 281 AI contribution policies and identifies ten countermeasures against AI slop, targeting pull requests, users, and autonomous agents, to give maintainers and researchers a baseline and a labeled corpus for studying the impact of AI policies.
Abstract
Open source communities are converging on a new governance artifact: the AI contribution policy. These policies barely existed a few months ago and are now being written and adopted. We analyzed 281 AI contribution policies, and manually classified them along the six dimensions; to study how policies change, we also tracked 92 dedicated AI policy files over time. We answer four research questions on (1) AI usage allowance, (2) AI disclosure practices, (3) AI slop countermeasures, and (4) AI policy evolution. We find that, first, permission is the norm rather than the exception: 83.3% of policies permit or encourage AI in code contributions. But permission comes with conditions, as 67.3% require a high level of human involvement and 43.4% assign accountability. Second, AI disclosure is required by 48.8% of policies, most often in pull request descriptions and commit messages, but what must be disclosed varies widely. Third, we identify ten countermeasures against AI slop, targeting pull requests, users, and autonomous agents. Finally, policies are not static: half of the dedicated AI policy files have already been revised since creation. Our results give maintainers and researchers a baseline and a labeled corpus for studying the impact of AI policies.
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