Mapping the Impact of Share Alike/Copyleft Licensing on Machine Learning and Generative AI
Abstract
The rise of generative artificial intelligence systems has raised a number of copyright issues. Some of the most hotly contested questions revolve around the use of copyrighted works to train AI models. One particular problem that has received relatively little attention is how AI training intersects with openly licensed works. To better understand the dynamics at play, Open Future commissioned the Institute for Information Law at the University of Amsterdam (IVIR) to conduct a study on the impact of Share Alike/CopyLeft (SA/CL) licensing on machine learning and generative AI.
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Bibtex
Report{nokey,
title = {Mapping the Impact of Share Alike/Copyleft Licensing on Machine Learning and Generative AI},
author = {Szkalej, K. and Senftleben, M.},
url = {https://www.ivir.nl/publicaties/mapping-the-impact-of-share-alike-copyleft-licensing-on-machine-learning-and-generative-ai/share-alike-and-ml/},
year = {2024},
date = {2024-06-12},
abstract = {The rise of generative artificial intelligence systems has raised a number of copyright issues. Some of the most hotly contested questions revolve around the use of copyrighted works to train AI models. One particular problem that has received relatively little attention is how AI training intersects with openly licensed works. To better understand the dynamics at play, Open Future commissioned the Institute for Information Law at the University of Amsterdam (IVIR) to conduct a study on the impact of Share Alike/CopyLeft (SA/CL) licensing on machine learning and generative AI.},
}