Comment by jstanley
3 days ago
I think you're just wrong about the OSI's definition of "open source AI"?
You can see https://opensource.org/ai/open-source-ai-definition
Specifically:
> A precondition to exercising these freedoms is to have access to the preferred form to make modifications to the system.
and
> The preferred form of making modifications to a machine-learning system must include all the elements below:
> Data Information: ...
> Code: ...
> Parameters: ...
Does this address your issues with the OSI definition?
The "data information" section ultimately says that a mere description of the training data is sufficient, which is the dilution on the part of the OSI that the FSF and SFC have criticized. I'm aligned with that criticism.
As for the "open source license" issue, you need the four fundamental software freedoms with whatever is distributed, just like with conventional open-source software. The OSAID enumerates a formulation of each of all four, but this is the one that this release fails to meet:
> An Open Source AI is an AI system made available under terms and in a way that grant the freedoms to¹ [...] [u]se the system for any purpose and without having to ask for permission.
> 1: These freedoms are derived from the Free Software Definition (https://www.gnu.org/philosophy/free-sw.en.html)
(The footnote is theirs, not mine.)
So the OSI agree with me that these weights cannot be considered, in their terms, "open-source weights". Our disagreement is that I think the training data itself should be considered a necessary part of a bona fide open-source ML model.
I think the answer to ethical concerns about releasing training data that involves data that carries privacy restrictions, like medical data, is that such models cannot be free/open-source. I think that's okay; it's okay to acknowledge that not every machine learning model in the world can be open-source. Eve the FSF, who are generally hardliners about using, let alone producing, non-free software, admit the ethical use of non-free models under just such circumstances. They just so so without blurring the distinction between free and non-free, which is the tack I wish the OSI had taken.
The OSI is an American organization founded in 1998, long after the term "Open Source" already had a clear meaning.
They have no right to make new and limited definitions for what Open Source means in other areas like LLMs. They can write and publish a definition if they like, but whether the rest of the world accepts it is another matter.
https://en.wikipedia.org/wiki/Open_Source_Initiative
What's missing from the OSI definition in this case? How do you think it is limited compare to the standard usage?
Most importantly would be recognition that the data used to train the AI also needs to be openly available.