“The current landscape of AI model licensing is riddled with confusion, restrictive terms, and misleading claims of openness,” Vidal said. “Instead of redefining ‘open’ to suit corporate interests, the AI industry should align with established open source principles to create a truly open ecosystem.”
The United Nations Open Source United community and the Open Source Initiative (OSI)Opens a new window today announced that the OSI has become the first organization to officially endorse the UN Open Source Principles. The UN Open Source Principles, recently adopted by the UN Chief Executive Board’s Digital Technology Network (DTN)Opens a new window, provide guidelines to drive collaboration and Open Source adoption within the UN and globally.
It’s currently unclear whether DeepSeek’s planned open source release will also include the code the team used when training the model. That kind of training code is necessary to meet the Open Source Initiative’s formal definition of “Open Source AI,” which was finalized last year after years of study. A truly open AI also must include “sufficiently detailed information about the data used to train the system so that a skilled person can build a substantially equivalent system,” according to OSI.
In traditional software, the perennial struggle between open source and proprietary revolves around the “true” meaning of “open source.” This can be resolved by deferring to the formal “definition” as per the Open Source Initiative, the industry stewards of what are and aren’t legitimate open source licenses. More recently, the OSI has formed a definition of “open source AI”
“The point of having definitions is to have criteria that can be scored, and focusing on licensing is how that is accomplished,” Maffulli said in a statement issued to TechCrunch. “The global community and industry have come to rely on the Open Source Definition and now the Open Source AI Definition as objective measures that they can rely on.”
OSI executive director Stefano Maffulli told me. “If only Meta’s license would remove the restrictions, we’d be more in sync. As it stands now, Llama is a liability for any developer; too opaque to be safe to use and with a license that ultimately leaves Meta in charge of their innovations.
Fontana also warns against overreach in defining openness, advocating for minimal standards rather than utopian ideals. “The Open Source Definition (OSD) worked because it set a floor, not a ceiling. AI definitions should focus on licensing clarity first, not burden developers with impractical transparency mandates.”
For an AI model specifically to be considered truly open, the OSI says its developers must provide detailed information about its training data and give people the ability to study, use and modify the system for any purpose.
While DeepSeek is “open,” some details are left behind the wizard’s curtain. DeepSeek doesn’t disclose the datasets or training code used to train its models. This is a point of contention in open-source communities. Most “open” models only provide the model weights necessary to run or fine-tune the model. The full training dataset, as well as the code used in training, remains hidden. Stefano Maffulli, director of the Open Source Initiative, has repeatedly called out Meta on social media, saying its decision to label its Llama model as open source is an “outrageous lie.”
While there are multiple claims to DeepSeek’s ‘open source’ AI model, in reality it is not open source. While both the model weights and the model architecture were shared in a technical paper, neither the code nor the training or evaluation data were shared openly. An analyst for the Open Source Initiative also confirmed that Deepseek is not Open Source AI and doesn’t meet the requirements of the Open Source AI definition. It joins other models which claim to be open source, but score poorly on data transparency.
Ai2’s fully open approach, which includes data, training code and models, ensures users can easily customize their pipeline for everything from data selection through evaluation.
The Open Source Initiative, after years of planning, in October 2024 introduced its initial definition of open source AI, which addresses four different kinds of data and requires those building and sponsoring AI technology to share what data they can as well as the model’s parameters and the source code used to train and run the system.
