{"id":444,"date":"2026-02-26T18:00:39","date_gmt":"2026-02-26T14:00:39","guid":{"rendered":"https:\/\/redmonk.com\/kholterhoff\/?p=444"},"modified":"2026-04-16T04:41:19","modified_gmt":"2026-04-16T00:41:19","slug":"generative-ai-policy-landscape-in-open-source","status":"publish","type":"post","link":"https:\/\/redmonk.com\/kholterhoff\/2026\/02\/26\/generative-ai-policy-landscape-in-open-source\/","title":{"rendered":"The Generative AI Policy Landscape in Open Source"},"content":{"rendered":"

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\nAfter publishing AI Slopageddon and the OSS Maintainers<\/a> I wanted to move beyond anecdotes and get a clearer picture of how the open source community is actually responding to AI-generated contributions. The stories of maintainer burnout and “AI slop” flooding pull requests were compelling, but I still had lots of questions. How many projects have formal policies? Are most communities permissive, restrictive, or still figuring things out? What concerns are driving these decisions? Are they primarily about code quality, copyright liability, or something else entirely?<\/p>\n

To answer these questions, I compiled and analyzed the generative AI policies of 32<\/del> 60<\/del> 70<\/del> 73<\/del> 77<\/del> 86 open source organizations, including foundations like the Linux Foundation, Apache, and Eclipse, as well as individual projects like the Linux Kernel, Gentoo, curl, and Matplotlib. The resulting visualization maps the current policy landscape across several dimensions: overall stance (permissive, ban, or undecided), primary concerns (quality, copyright, and ethics), disclosure requirements, and adoption timeline.<\/p>\n

Below is an interactive visualization of what I found. You can explore policy stances, see how adoption has accelerated since 2023, and compare how different organizations weigh quality, copyright, and ethical concerns. The full directory at the bottom links to each organization’s policy document for those who want to read the primary sources.<\/p>\n

Did I miss some AI policies? Definitely. These are just the ones I could find. If you know of one I missed please email me<\/a> so I can add it.<\/p>\n

If you have trouble viewing the visualization in the iframe below, you can access a standalone version at oss-ai-policies.netlify.app<\/a>.<\/p>\n

Project Edited on 26 February 2026 22:00 EST<\/strong>: Thanks to Alex Bradbury<\/a>,\u00a0Scott Shambaugh<\/a>, and Melissa Weber Mendon\u00e7a<\/a> for alerting me to several more projects, which I have added to my data visualization. Also, be sure to check out Melissa’s own excellent open-source-ai-contribution-policies<\/a>\u00a0on GitHub.<\/p>\n

Project Edited on 2 March 2026 17:30 EST<\/strong>: Thanks to ell1e<\/a>\u00a0and Sviatoslav Sydorenko<\/a> for sharing more projects with me. Also, the folks at CHAOSS have collected a number of “Awesome LLM Policy<\/a>” examples.<\/p>\n

Project Edited on 3 March 2026 10:00 EST<\/strong>: Thanks to Jannis Leidel<\/a> for pointing out that I conflated the CPython project and the Python Foundation. I have fixed this and updated the pip-tools entry.<\/p>\n

Project Edited on 9 March 2026 00:05 EST<\/strong>: Thanks to\u00a0ell1e, Sviatoslav Sydorenko and Erin Schnabel<\/a> for informing me about 3 additional policies: Zig, pytest, and Quarkus.<\/p>\n

Project Edited on 18 March 2026 12:50 EST<\/strong>: Thanks to Sviatoslav Sydorenko and ell1e for informing me about 4 additional policies: zizmor, Redox OS, elementary OS, and stb.<\/p>\n

Project Edited on 3 April 2026 22:00 EST<\/strong>: Thanks to ell1e and Paul Cooper for informing me about 4 additional policies: W3C, Node.js (petition), gedit, Forgejo, Inkscape, GIMP, L\u00d6VE, Asahi Linux, OpenTTD.<\/p>\n

Project Edited on 12 April 2026 07:00 EST<\/strong>: Thanks to Dawn Foster for informing me about Kubernetes’ updated policy.<\/p>\n

Project Edited on 12 April 2026 07:00 EST<\/strong>: Thanks to Turan Furkan Topak for informing me about FreeCAD’s updated policy.<\/p>\n