The rise of generative artificial intelligence (AI) poses challenges for the free and open-source software (FOSS) community, a global network committed to creating and maintaining publicly available software that anyone can use, modify and share. Many AI models have been built on open-source software but do not reciprocate the transparency that the FOSS community’s principles require, leaving open-source developers uncertain about how these AI tools are using their code.
A study by researchers at Yale’s Digital Ethics Center (DEC) explores a potential solution to this problem based on a concept used in free and open-source software known as “copyleft” licenses—a twist on typical copyright rules that obliges works derived from open-source materials to remain as free and transparent as the original work, rather than relicensing it under more restrictive terms. The study is published in the International Journal Of Law And Information Technology.
The authors propose what they call a Contextual Copyleft AI License (CCAI)—a novel extension of copyleft licensing that would treat generative AI models as derivative works and require AI developers training models on open-source code to make their architecture and training data freely available.
