AI programs such as TensorFlow, PyTorch, and Hugging Face Hub work well under their open source licenses. The new AI artifacts are another story. Datasets, models, weights, etc. don’t fit squarely into the traditional copyright model. (OSI director) Maffulli argued that the tech community should devise something new that aligns better with our objectives, rather than relying on “hacks.”
Specifically, open source licenses designed for software, Maffulli noted, might not be the best fit for AI artifacts. For instance, while MIT License’s broad freedoms could potentially apply to a model, questions arise for more complex licenses like Apache or the GPL. Maffulli also addressed the challenges of applying open source principles to sensitive fields like healthcare, where regulations around data access pose unique hurdles.
RAIL has its own problems-the use restrictions make it very different from normal open source models.