We ❤️ Open Source
The process of defining Open Source AI exists in an environment of unprecedented complexity but of utmost importance. I want to provide a short background on why the Open Source Initiative (OSI) is doing this, how the work is being done, and why global community—working in a spirit of collaboration—has confidence that issuing the Open Source AI Definition v.1.0 is the correct and most prudent next step in a process to help the open source community make a big leap forward in AI innovation for the good of everyone who relies on the meaning of the term.
Open Source software (OSS) succeeds because anyone can learn, use, share, and improve it without having to ask for permissions. For over 26 years since the term was defined, an entire ecosystem of business, research, and governments around the world has relied on the set of legal documents reviewed and approved for compliance to the Open Source Definition by the Open Source Initiative to build collaboration efforts leading to massive innovation and economic benefits. A 2022 European Commission report estimated that open source contributed between €65 and €95 billion to the European economy (Blind et al. 2021). A 2023 working paper by Harvard Business School (Hoffman et al, 2024) estimates the supply-side value of widely-used OSS is $4.15 billion, and the demand-side value at $8.8 trillion. OSS generates enormous value because it is underpinned by a stable and well-defined set of licenses that are widely understood and adopted.
Unfortunately, as AI and machine learning evolve, traditional open source licenses and definitions fall short in addressing the unique complexities of AI components, especially concerning datasets and machine learning models.
