The Machine As Author

61 Pages Posted: 20 Jul 2019

See all articles by Daniel J. Gervais

Daniel J. Gervais

Vanderbilt University - Law School

Date Written: March 25, 2019

Abstract

The use of Artificial Intelligence (AI) machines using deep learning neural networks to create material that facially looks like it should be protected by copyright is growing exponentially. From articles in national news media to music, film, poetry and painting, AI machines create material that has economic value and that competes with productions of human authors. The Article reviews both normative and doctrinal arguments for and against the protection by copyright of literary and artistic productions made by AI machines. The Article finds that the arguments in favor of protection are flawed and unconvincing and that a proper analysis of the history, purpose, and major doctrines of copyright law all lead to the conclusion that productions that do not result from human creative choices belong to the public domain. The Article proposes a test to determine which productions should be protected, including in case of collaboration between human and machine. Finally, the Article applies the proposed test to three specific fact patterns to illustrate its application.

Keywords: copyright, author, artificial intelligence, machine learning

JEL Classification: K11, K20, 034, Z11

Suggested Citation

Gervais, Daniel J., The Machine As Author (March 25, 2019). Iowa Law Review, Vol. 105, 2019. Available at SSRN: https://ssrn.com/abstract=3359524

Daniel J. Gervais (Contact Author)

Vanderbilt University - Law School ( email )

131 21st Avenue South
Nashville, TN 37203-1181
United States
615 322 2615 (Phone)

Register to save articles to
your library

Register

Paper statistics

Downloads
394
Abstract Views
1,720
rank
73,105
PlumX Metrics