I agree that it's interesting. I can't say it's surprising for Oracle to care about licensing so much that they pump the breaks on AI contributions. Besides, as they note:
> Whether a user of a generative AI tool has IP rights in content generated by the tool is the subject of active litigation. I would question whether it's fair to say that *this* constitutes bad stewardship. Don't get me wrong, I've seen plenty of fair (and some uncharitable, if quite funny <https://www.youtube.com/watch?v=1KeYzjILqDo&t=71s>) complaints about Oracle's stewardship of Java. I'm not here to litigate those (pun intended). Even so... this might be a right move? We don't really know what the licensing status of AI-generated code is yet and that matters for everyone that consumes it, but *especially* those who consume it and then re-license it (for money <https://www.oracle.com/java/technologies/javase/jdk-faqs.html>!) in public. The broader AI and Open Source ecosystems are both going to have to evolve to better accommodate software licensing. I know there are already firms and industry groups building AI models that are trained exclusively permissively licensed code or content. BigCode <https://www.bigcode-project.org/> is one, KL3M <https://kl3m.ai/> is another. IBM has Granite <https://www.ibm.com/granite>. There are others out there, all trying to be ethically sourced, legally safe models. I wouldn't be surprised if the OpenJDK's policy evolves to permit contributions built using models like that which don't introduce tort risk. I'll grant that it would have been a much more preferable move for them to say, "These models are blessed, and here are our criteria for how we permit a model to be used for contribution," but that's just me armchair quarterbacking. To me, this seems pretty consistent with Java taking the "last mover advantage" move yet again. "We don't know how this will play out, so we're going to sit on our hands until the future resolves and focus on doing the stuff we know is worthwhile." I think the interesting question is what we at the Apache Software Foundation, and within the Groovy ecosystem in particular, want to do. I think it's fair to assume that we'd like to be more AI-forward than that OpenJDK policy, but I'm not ready to go full Linus Torvalds and embrace the vibe-coding. Plenty of us are using frontier models for our day jobs. Should those contributions be upstreamed into Groovy? Should *we* do what I just said and specify some blessed models that we'll accept contributions from? Should we be doing other stuff, like publishing skills <https://skills.sh/?q=groovy> within the main branch or providing AGENTS.md files for people who want to use AI agents to contribute (within certain parameters)? What do people think? On Thu, Apr 16, 2026 at 2:43 PM Jim White <[email protected]> wrote: > Oracle has been a bad custodian of Java since the Sun acquisition (ditto > for JavaScript - https://javascript.tm/). > > Sounds to me like (past) time for proper GPL fork. IcedTea is long > dormant afaik. Linux Foundation seems like a good home. > > -- Jim > > On Thu, Apr 16, 2026 at 5:44 AM Gianluca Sartori <[email protected]> > wrote: > >> >> This is interesting: >> https://openjdk.org/legal/ai >> >> OpenJDK Interim Policy on Generative AI >> >> The field of generative AI is evolving quickly. It brings compelling >> opportunities to improve developer productivity, but it also brings risks: >> to reviewer burden, to safety and security, and to intellectual property. >> >> Oracle, as the corporate sponsor of the OpenJDK Community, is working to >> draft a full policy governing the use of generative AI tools in OpenJDK >> contributions. Oracle will propose that policy to the OpenJDK Governing >> Board in due course. Until that policy is in place, the Governing Board has >> approved this interim policy: >> >> Contributions in the OpenJDK Community must not include content >> generated, in part or in full, by large language models, diffusion models, >> or similar deep-learning systems. Content, in this context, includes but is >> not limited to source code, text, and images in OpenJDK Git repositories, >> GitHub pull requests, e-mail messages, wiki pages, and JBS issues. >> >> Contributors in the OpenJDK Community may use generative AI tools >> privately to help comprehend, debug, and review OpenJDK code and other >> content, and to do research related to OpenJDK Projects, so long as they do >> not contribute content generated by such tools. >> >> This interim policy aims to encourage the use of generative AI tools in >> ways that limit their risks while we gain further experience that will >> inform the full policy. >> Frequently Asked Questions >> >> 1. >> >> *What are the risks to reviewer burden of using generative AI tools?* >> >> Generative AI tools, by their nature, make it easy to create large >> quantities of plausible-looking code, with plausible-looking tests, which >> is nonetheless incorrect or, even if it is correct, is poorly designed and >> therefore difficult to maintain. Reviewing submissions of such code can >> easily become a drain on the already limited time of human reviewers. For >> this reason, some open-source communities have limited, if not banned, the >> submission of code created by generative AI tools. >> 2. >> >> *What are the risks to safety and security of using generative AI >> tools?* >> >> The JDK, developed and maintained in the OpenJDK Community, is the >> primary implementation of the Java Platform. It sits at the foundation of >> mission-critical systems in businesses, governments, and other >> organizations around the world. Safety and security are paramount. >> Plausible-looking but incorrect code would put these critical properties >> at risk. >> 3. >> >> *What are the intellectual-property risks of using generative AI >> tools?* >> >> The Oracle Contributor Agreement (OCA) requires that a contributor >> own the intellectual property rights in each contribution and be able to >> grant those rights to Oracle, without restriction. Most generative AI >> tools, however, are trained on copyrighted and licensed content, and their >> output can include content that infringes those copyrights and licenses, >> so >> contributing such content would violate the OCA. Whether a user of a >> generative AI tool has IP rights in content generated by the tool is the >> subject of active litigation. >> 4. >> >> *Despite these risks, generative AI tools can provide significant >> value. Are OpenJDK contributors forbidden from using them altogether?* >> >> No. As the policy says, you are welcome to use such tools to help >> comprehend, debug, and review OpenJDK code and other content. Anecdotal >> evidence from other communities suggests that analysis of existing code, >> rather than creation of new code, is where generative AI tools shine for >> established projects with large code bases. This is consistent with our >> experience thus far. >> 5. >> >> *What does it mean to use generative AI tools “privately”?* >> >> The intent of that term is to emphasize that you may use such tools >> on your own, without contributing the content that they generate. It does >> not mean that you cannot, *e.g*., share and discuss the output of >> such tools with a colleague. When sharing such content, consider adding >> prominent comments that identify it as being AI-generated. >> 6. >> >> *Is it okay to continue using the spell-checking, grammar-checking, >> auto-completion, and refactoring features in my editor or IDE?* >> >> Yes, so long as they are not based on large language models or >> similar deep-learning systems. >> 7. >> >> *Is it okay to use a generative AI tool to review draft JEPs, >> JavaDoc, or other documents, so long as I write all of the text myself?* >> >> Yes. This is clearly a case of using a generative AI tool to review >> content, which is fine. >> 8. >> >> *If I use a generative AI tool to create 100 lines of code, and then >> edit ten of those lines myself, may I contribute the result?* >> >> No. Your contribution would still include, in part, AI-generated code. >> 9. >> >> *Can we improve any of our tooling to help remind contributors of >> this policy?* >> >> Yes. We will shortly reconfigure Skara to add a checkbox to the body >> of each pull request on GitHub. When you create a pull request, you must >> check the box to affirm that your contribution is in accordance with the >> policy. More details, including how to add the checkbox to the body of an >> existing pull request, are available in the wiki >> >> <https://wiki.openjdk.org/spaces/SKARA/pages/56524965/FAQ#FAQ-OpenJDKInterimAIPolicy> >> . >> 10. >> >> *In an OpenJDK Project, is it okay to add a feature that calls out to >> an external AI service?* >> >> That depends upon the service’s terms of use, so this amounts to a >> legal question. Be aware that many such terms place strict limits on how >> the service may be used. Consult your attorney, or your employers’ >> attorney, as appropriate, and make sure that everyone with a vested >> interest in your Project has also consulted appropriate attorneys. >> 11. >> >> *As a Reviewer in an OpenJDK Project, am I responsible for detecting >> when a contributor has submitted code or other content created with a >> generative AI tool?* >> >> In this role you are already expected to do your best to ensure that >> incoming contributions are consistent with OpenJDK Community policies and >> conventions. In general, reliably distinguishing human-generated content >> from AI-generated content is impossible. If, however, you see evidence >> that >> content in a contribution was created with a generative AI tool, then it >> is >> your responsibility to notify the contributor of that fact. If the >> contributor does not respond positively and remove the content, please >> bring that to the attention of the appropriate Project Lead. >> 12. >> >> *What are some tell-tale clues of content created by generative AI >> tools?* >> >> Sometimes it is obvious, for example when a commit message in the >> personal fork from which a contributor initiates a pull request includes a >> Co-Authored-By trailer line that gives credit to a specific >> generative AI tool. Other times it is more subtle, for example when a >> contributor’s comments in a pull-request conversation or an e-mail message >> are in a chatty, verbose style inconsistent with their past writing. Other >> clues include highly structured comments with multiple headings, >> unnecessary comments in code, gratuitously defensive programming, and the >> use of emoji characters. >> >> Generative AI tools are evolving rapidly, so clues that are effective >> indicators today might not be effective indicators tomorrow. In general, >> if >> something in a pull request seems uncannily cheerful or meticulous then >> you >> could be looking at AI-generated content. >> >> >> >> Gianluca Sartori >> -- >> https://dueuno.com >> >
