On 13/08/26 5:36 am, Pirate Praveen wrote: > I got some feedback privately to clarify some more things. > > ---updated proposal v4.0 --- > > Using its power under Constitution section 4.1 (5), the project issues > the following statement describing its current position on AI-assisted > contributions. This statement describes the position of the project at > the time it is adopted. That position may evolve as time passes without > the need to resort to future general resolutions. The GR process remains > available if the project needs a decision and cannot come to a consensus. > > Preamble > > LLMs and its impact on society and environment is a hugely polarizing > debate. > > In this document, we mainly look at contributions using LLMs. > > LLMs have made a huge leap in language translations, but at the same > time depending on big tech companies to provide this service is not a > good idea. When it comes to generating code, we also need to consider > how it weakens the idea of copyleft, unlike translations. > > Enforcing copyleft requires us to depend on copyright law, if LLM > generated code cannot be copyrighted, then LLM could be used to take out > copyleft requirements from Free Software projects. But this is not > something we can really control. > > Basics > > 1. If a Free Software LLM model is run locally, we have some control > over it (we still need to retrain it, if we want to modify it). But even > for that level of control, the high hardware specifications required to > run these models makes access to such hardware difficult. So we cannot > entirely insist on running an LLM model locally, similar to not > insisting on use of Free Hardware Designs. So we will need to > collectively run the models to make sure everyone have access to Free > Software models in practice. > > 2. Public AI is AI as public infrastructure like highways, water, or > electricity. Public AI uses Free Software and Open Weight models. Open > Weights refer to the final weights and biases of a trained neural > network. These values, once locked in, determine how the model > interprets input data and generates outputs. > > Since Public AI is not a well defined term, we need a more precise > definition. PublicAI.Co also complies with Open Source AI definition by > OSI (https://opensource.org/ai) so we will base Public AI definition on > Open Source AI definition. > > For AI to be accessible to people, it has to be available easily to > people, like Wikipedia or Lets Encrypt. Not for profit collaborations > between multiple organizations and public funding is essential to keep > it sustainable, though public funding is not a requirement. How we are > going to fund such Public AI will evolve in the future. > > So to evaluate an AI web service, we will use the definition of Open > Source AI by OSI, but some requirements may be relaxed. > > 3. At this point, we don't want to insist on training data being freely > available, similar to how we don't insist on Free Hardware Designs. The > challenges to practically being able to use the available data should be > factored in. Similar to how costly it would be to produce hardware from > Free Hardware Designs, even when training data is available, huge > computing power is required to use it practically. > > This point is a specific relaxation from the Open Source AI definition. > > So Public AI = Open Source AI + relaxed requirement on training data. > > Guidelines > > 1. Translations generated by Public AI can be accepted. > > 2. Code / documentation generated by Publc AI can also be accepted. > Ideally it should preserve share alike / copyleft conditions of original > code used in training, but how copyright law evolves is not in our control. > > 3. Contributions (code/bug reports/patches/documentation etc) assisted > by Public AI should be accepted. > > 4. Any such contributions should also follow the generally accepted > norms for contributions like ownership and quality. > > The person submitting any such contributions generated or assisted by > Public AI should take full responsibility for its quality. > > 5. Any contributions using generative AI/LLM systems not matching > requirements of Public AI will not be accepted. > > References > > An example to understand what Public AI looks like in practice is > https://publicai.co, which is funded by Mozilla, the Future of Life > Institute, and the Center for Cultural Innovation. This project is the > inspiration and basis for this document. > > ---updated proposal v 3.0 --- > > If you feel Open Source AI is missing in the current set of ballot > options, I'd appreciate seconds for this option. We could still clarify > the draft if there are ambiguities. > > Summary: > > The core part of this proposal is, Accept if Public AI, else reject. > > Public AI = Open Source AI + relaxed requirement on training data.
Seconded, thanks!
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