I see the issue now and this should go in the FAQ, too. The “classic” Open Source Definition is applied to licenses, not to the software. We’ve been working under the axiom that if a program is shipped with a license approved by the OSI then the software is considered Open Source. In the software space that’s generally understood and mostly works fine (although it’s challenged, at times.)
For machine learning systems the OSI can’t simply review licenses as the concept of the “program” in this case is not just the source/binary code. Through the co-design process of the Open Source AI Definition we learned that to use, study, share and modify a ML system one needs a complex combo of multiple components each following diverse legal regimes (not just the usual copyright+patents.) Therefore we must describe in more details what is required to grant users the agency and control expected.
There is vagueness with the Open Source Definition, too. And the interpretation of the OSD has evolved over time.
Some vagueness is fine but there must be clarity with the intentions, the preamble and basic principles we want to achieve: those shouldn’t change. The definition of preferred form to make modifications lists principles about data information, code and model and provides examples of things required to comply. I expect those examples to be used and refined by evaluators in the future… starting now (that’s the reason of the validation phase.)
A framework of reference that may be useful to evaluate if a ML system is granting you the necessary freedoms is to ask yourself:
- Do I have the preferred form to make modifications to the system?
- Do I have the elements necessary for me to fork the system and build something new on top of it?
We have time to add clarity to the definition of “preferred form to make modifications”.