Open Source Attribution Rights

Join the Los Angeles, Northern California and Texas Chapters for an exciting program discussing attribution rights in open source and creative commons license in machine learning training. This is part of the Society’s  AI Series.

Authors that make their works available to the public under open source or Creative Commons licenses normally want to ensure their work is shared and disseminated broadly, in return for certain conditions like attribution and obligations to share alike any changes or derivatives made of the work.  Although authors that offer their works under open innovation licenses often want to ensure the maximum usefulness of that work, the value proposition can change when their works are used to train machine learning models or otherwise used in AI, especially because the most fundamental aspect of open license, attribution, is difficult if not impossible to provide. Our panelists will discuss the importance of the attribution covenant in open source licenses, the relationship between attribution and copyright management information rights under the Copyright Act and the DMCA, the potential impact of the ML Genius Second Circuit decision, and  the claims being made by the class action plaintiffs in the Doe v. GitHub class action complaint.