New post: The Open Source AI Definition is not fit for purpose

Signed-off-by: Paul Barker <paul@pbarker.dev>

content/posts/2024-10-15-open-source-ai-definition.rst

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+   Copyright Paul Barker <paul@pbarker.dev>
+   SPDX-License-Identifier: CC-BY-NC-4.0
+
+The Open Source AI Definition is not fit for purpose
+====================================================
+
+:date: 2024-10-15
+:tags: open-source, ai
+:summary:
+    The `Open Source Initiative`_ have published a release candidate version of
+    their `Open Source AI Definition`_ and I expect that a version 1.0 release
+    will be published soon.
+
+    Unfortunately, I don't think that this is a good definition in its current
+    form. By requiring "data information" instead of the complete corresponding
+    training data, the definition cannot achieve its stated goals. This choice
+    also calls into question the purpose of the definition, and may lead to a
+    loss of respect for the existing Open Source definition.
+
+    The definition must be modified to require Open Source AI Systems to include
+    the release of complete corresponding training data under an open license.
+
+The `Open Source Initiative`_ have published a release candidate version of
+their `Open Source AI Definition`_ and I expect that a version 1.0 release will
+be published soon.
+
+Unfortunately, I don't think that this is a good definition in its current
+form. By requiring "data information" instead of the complete corresponding
+training data, the definition cannot achieve its stated goals. This choice
+also calls into question the purpose of the definition, and may lead to a
+loss of respect for the existing Open Source definition.
+
+The definition must be modified to require Open Source AI Systems to include the
+release of complete corresponding training data under an open license.
+
+.. _Open Source Initiative: https://opensource.org
+.. _Open Source AI Definition: https://opensource.org/deepdive/drafts/the-open-source-ai-definition-1-0-rc1
+
+.. note::
+    I led a well attended and productive `discussion on the Open Source AI
+    Definition at OggCamp 2024
+    </posts/2024-10-13/conference-talk-lets-talk-about-the-open-source-ai-definition/>`_.
+    I briefly made the same arguments I make below, and then invited others to
+    contribute their opinions. I will make clear in the text which points come
+    from this discussion - all other opinions shared here are my own.
+
+    `Jamie Tanna <https://www.jvt.me/>`__ also shared `his notes from this
+    discussion
+    <https://www.jvt.me/posts/2024/10/13/oggcamp/#lets-talk-about-the-open-source-ai-definition>`__
+    which I greatly appreciate.
+
+Call to Action
+--------------
+
+The OSI's Open Source AI Definition is currently at the release candidate stage
+and we may soon see a version 1.0 release. Now is the time to give feedback to
+OSI, both directly and indirectly.
+
+Direct feedback can be made to OSI. If you share my concerns, do not endorse the
+Open Source AI Definition in its current form. Instead, `leave comments on the
+text <https://hackmd.io/@opensourceinitiative/osaid-1-0-RC1>`__ and if you're
+able to, `attend the upcoming town hall sessions
+<https://opensource.org/deepdive#townhalls>`__ to share your feedback.
+
+Indirect feedback can be made by sharing your own thoughts in conference talks,
+blog posts, on the Fediverse, on social media sites such as LinkedIn and in
+individual discussions. Such debate and consensus building needs to continue
+regardless of whether the OSI releases their Open Source AI Definition in its
+current form.
+
+My argument in detail
+---------------------
+
+Will it be effective?
+~~~~~~~~~~~~~~~~~~~~~
+
+The stated aim of this definition is to identify AI systems made available under
+terms which allow free (*libre*) Use, Study, Modification and Sharing. I do not
+think the definition is effective in this aim.
+
+The definition of the "Preferred form to make modifications to machine-learning
+systems" specifically excludes the need to make the full training data available
+under a free or open license. Instead, it requires the provision of "Data
+information". At the risk of stating the obvious, "data information" is not
+"data". Possessing a description of the training data and how it was obtained
+does not guarantee that the recipient has the legal or technical ability to
+exactly re-create the training data. And if the training process for an AI model
+is followed using a similar but not exactly identical set of training data, the
+resulting model weights will differ. This is not a purely academic concern -
+without the ability to exactly re-run the training process and arrive at the
+exact same AI model, we cannot say that we have the preferred form to make
+modifications to the system. We can't answer questions like "How would the
+resulting model differ if we exclude some subset of the training data" or "How
+would the resulting model differ if we extend the training data", etc, if
+re-training the model also introduces other differences due to our inability to
+start with the exact same set of training data.
+
+That is to say - the *effective* rights to study and modify an AI system require
+access to the complete corresponding training data.
+
+This view was shared by most of the folks who contributed to the discussion
+session at OggCamp 2024. There was one counter argument that the training data
+was similar to "working out" or research notes made while developing software,
+and that software can be Open Source without the need to share those private
+notes. There was disagreement with this analogy from others in the room.
+
+Why is training data excluded?
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Given the above, and that this view seems to be widely shared, why would the
+need to share training data under an open license be explicitly excluded from
+the Open Source AI Definition?
+
+The current AI hype cycle is focused on Large Language Models (LLMs) and other
+large-scale generative AI models. These models require vast amounts of data to
+train - so much data that no combination of truly open data sets can provide
+even a fraction of the required data volume.  Instead, training data is scraped
+from the internet at large without regard to the consent of authors, artists or
+users. Even if training AI models on this data is considered fair use under
+copyright legislation, distributing this data set in its full and original form
+could never qualify as fair use.
+
+If the OSI stated that complete corresponding training data must be shared under
+an open license for an AI System to be considered Open Source, no LLM or
+large-scale generative AI model could ever meet this requirement. So no LLM
+could be an Open Source AI system.
+
+And if the OSI argued that no LLM could be considered Open Source, they would
+have to contend with a fear of missing out (FOMO) or fear of becoming irrelevant
+if they aren't able to somehow attach themselves the current AI hype cycle.
+
+It's worth noting that there are no freestanding community projects developing
+such models - the training costs in both data and compute resources are simply
+too high for such community projects to exist independently from a corporate
+effort to train an AI model. These are mega-projects on the scale of a nuclear
+power station or an aircraft carrier.
+
+Smaller and more special purpose AI models do exist and do have freestanding
+communities, but they are not the subject of the current hype cycle.
+
+I would argue that this definition is targeted at the AI mega-projects, not at
+the developers of smaller AI models. It is a direct attempt to stop companies
+like Meta misusing the term "open source" to describe their AI systems - a thing
+that they are simply not going to do. They don't respect authors, artists or
+user consent, so why will they respect an Open Source AI Definition?
+
+How does this compare to the original Open Source definition?
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The original Open Source definition back in 1998 built on existing community
+efforts, licenses and policies such as the Debian Free Software Guidelines. It
+packaged these community values and best practices in a business-friendly way so
+that could reach a new audience - it was an invitation to join an existing and
+vibrant community.
+
+This Open Source AI definition attempts to define such a community into
+existence where I don't think one exists. The definition should be downstream of
+the long process of community development and consensus building, not upstream
+of it.
+
+What are the likely consequences of a bad Open Source AI Definition?
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+I expect that the most likely outcome if the Open Source AI Definition is
+released in its current form will be that it is not respected by the community.
+This does actually matter! It will damage the reputation of the Open Source
+Initiative and damage the integrity of Open Source as a coherent and well
+understood shared vision. It will also split the efforts of the OSI between two
+definitions which don't mesh together as well as they seem to think that they
+do.
+
+In the discussion session at OggCamp 2024 it was also pointed out that such a
+definition would be a gift to companies like Meta, OpenAI, Anthropic, etc and
+their lobbyists. It would be an independent document from a respected non-profit
+organisation which they can take with them when they talk to governments about
+how AI systems should be regulated.  Meta especially could argue that their AI
+system meets this gold standard of being open source without having to change
+their behaviour around the non-consensual collection of training data. So this
+definition could weaken the position of individuals and organisations trying to
+argue against these data collection practices.