Copyright in Generative Deep Learning

Abstract

Machine-generated artworks are now part of the contemporary art scene: they are attracting significant investments and they are presented in exhibitions together with those created by human artists. These artworks are mainly based on generative deep learning techniques. Also given their success, several legal problems arise when working with these techniques. In this article we consider a set of key questions in the area of generative deep learning for the arts. Is it possible to use copyrighted works as training set for generative models? How do we legally store their copies in order to perform the training process? And then, who (if someone) will own the copyright on the generated data? We try to answer these questions considering the law in force in both US and EU and the future alternatives, trying to define a set of guidelines for artists and developers working on deep learning generated art.

Copyright in generative deep learning

“…Acknowledgment. A preprint version of the article is available in arXiv (Franceschelli and Musolesi, 2021a).…”

WhyGen: Explaining ML-powered Code Generation by Referring to Training Examples

“…Although there has already been a lot of debates on this issue from the legal perspectives [1, 7,14], how to technically ease this tension is still an open problem. There is an inevitable trade-off between achieving higher accuracy and reducing training data memorization.…”