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52 Seton Hall L. Rev. 1111 (2021-2022)
AI Derivatives: The Application to the Derivative Work Right to Literary and Artistic Productions of AI Machines

handle is hein.journals/shlr52 and id is 1127 raw text is: Al Derivatives: The Application to the Derivative Work Right to Literary and Artistic Productions of Al Machines Daniel J. Gervais, PhD* This Article predicts that there will be attempts to use courts to try to broaden the derivative work right in litigation either to prevent the use of or claim protection for, literary and artistic productions made by Artificial Intelligence (AI) machines. This Article considers the normative valence of and the (significant) doctrinal pitfalls associated with, such attempts. It also considers a possible legislative alternative, namely attempts to introduce a new sui generis right in AI productions. Finally, this Article explains how, whether such attempts succeed or not, the debate on rights (if any) in productions made by AI machines is distinct from the debate on text and data mining exceptions. I. INTRODUCTION ....................................................................................................... 1112 II. THE Al CREATION PROCESS & ITS COPYRIGHT RAMIFICATIONS............. 1114 III. A NEW ROLE FOR THE DERIVATIVE WORK RIGHT?..................................... 1117 A. Overview of the Derivative Work Right....................................1117 B. (Relatively) Uncontroversial Aspects of the Derivative Work Right..........................................................................................1119 C. The Originality Controversy...........................................................1120 D. The Relationship between Reproduction and Derivation 1125 E. Application to Al..................................................................................1127 IV. DIFFERENT DEBATES ABOUT OTHER AI-RELATED RIGHTS AND EX CEPTIO N S....................................................................................................1 1 3 2 A. Sui generis rights ................................................................................1132 B. Text and Data Mining........................................................................1135 V. CONCLUSION........................................................................................................... 1136 * Milton R. Underwood Chair in Law, Vanderbilt University. The Author is grateful to Professors Christopher J. Sprigman and Lydia P. Loren for comments on an earlier version, to participants at the Seton Hall symposium at which the initial draft was presented in the fall of 2021 and to the student editors of the Seton Hall Law Review for their careful editing. All errors and omissions are the Author's sole responsibility. 1111

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