Missed Anthropic Perspectives & Mixed AI Meta-Phors Cloud Copyright Law
By James Flynn & Ariana Tagavi,* Epstein Becker Green
The evolution of generative artificial intelligence has prompted courts in two highly-publicized recent federal district court decisions to apply copyright law’s doctrine of fair use to the “training” and output of generative AI systems. We will discuss those two cases—Kadrey v. Meta Platforms, Inc. and Bartz v. Anthropic PBC—in further detail below to illustrate the evolving legal issues surrounding this emerging technology. In addition to addressing AI-focused issues, these rulings revisit, and seem to reinterpret, copyright’s fair use doctrine in a manner displaying two shortcomings to our way of thinking:
- First, the opinions appear to conflict with the Supreme Court’s nuanced analysis in Andy Warhol Foundation for the Visual Arts, Inc. v. Goldsmith, particularly in their treatment of the first factor of fair use: the purpose and character of the use, and this piece will explore those inconsistencies, concluding that these AI decisions misapply, or insufficiently engage with, Warhol’s guidance on “transformativeness” and market substitution.
- Second, these opinions also deal inconsistently, and ultimately unpersuasively for us, with the concept of “copying,” and the “learning” and “training” metaphors, used to describe how large language models (LLMs) are created and then work, leaving largely unexplored in the AI context the existing body of law under the doctrine of non-literal infringement, which prohibits unauthorized reproduction of protected expression beyond exact copying, as seen the Second Circuit decision in Castle Rock Entm’t, Inc. v. Carol Publ’g Grp., Inc. and in other cases.
Let’s turn to those issues now.