The Open Source(ish) AI Definition (OSAID)

[Shamar]

@shujisado

If an “unknown” or “private” dataset is used, it is naturally impossible to reproduce the model. In other words, systems that use such datasets do not comply with OSAID.

Well, in fact they do comply with OSAID 0.0.9.

All developers have to do to comply is to provide plausible “Data Information” pretending they trained the system on a publicly available dataset.

Such “facade dataset” might even be a proper subset of the dataset actually used, but without the availability of the whole dataset actually used in training, nobody could really study or modify that AI system.

@shujisado

Unlike source code, datasets contain various types of content, and there are rights beyond copyright that arise, which are handled differently depending on the country. Even if a dataset is licensed under an OSD-compliant or DFSG-free license, if third-party privacy or publicity rights are included in that DFSG-free dataset, it cannot be freely distributed. However, even in such cases, it is legal in many jurisdictions to use such datasets for machine learning, and in many cases, datasets can be accessed by anyone for machine learning purposes.

Well, when the dataset cannot be distributed but are available for anyone to use in machine learning under the same legal terms that allowed their use during the system training, the system can still be considered Open Source AI, since both the freedom to study and the freedom to modify are preserved.

But being available is different from being made available.
Without requiring the dataset distribution, all legal issues disappear.

What do you think about such solution?

@shujisado

If anyone can recreate the dataset used for machine learning purposes, wouldn’t that be considered free?

Sure, if anyone can recreate the whole and exact dataset used during the training of a system, such system could be defined Open Source AI.