Ard on Copyright’s Latent Space: Generative AI and the Limits of Fair Use

Bj Ard (U Wisconsin Law) has posted “Copyright’s Latent Space: Generative AI and the Limits of Fair Use” on SSRN. Here is the abstract:

Generative AI poses deep questions for copyright law because it defies the assumptions behind existing legal frameworks. While fair use is at the heart of the ongoing debate, the doctrine struggles because several features of generative systems take them beyond the reckoning of settled law. This Article takes up the fair use question to expose copyright’s limitations as well as its latent commitments, particularly its allowance for the exploitation of non-authorial value.
Fair use’s transformative use paradigm, which compares the purpose of the use with that of the original work, faces difficulty because the indeterminate and modular nature of AI training processes renders the purpose of copying contingent. This hurdle can be overcome by recognizing that purpose serves as a proxy for determining whether the use intrudes on markets rightly belonging to the copyright owner. However, this raises the question of which markets those are.
Answering this question requires delving into copyright’s latent space—the unarticulated principles and commitments embedded in its jurisprudence. This Article identifies a dividing line between value that stems from an author’s creative choices and value that does not, with courts permitting users to tap into the latter even to the copyright owner’s detriment. The reoriented test would ask whether a user exploits non-authorial value like that which stems from facts, tropes, and third-party investment versus the authorial value arising from an artist’s creative decisions. The precise line remains to be hashed out—courts have historically drawn the line differently across creative contexts to calibrate the scope of protection with copyright’s goals.
The fair use question also reveals deeper structural limitations of the copyright regime. The argument that fair use should be denied to vindicate copyright policy misses that AI systems trained on licensed works may still displace human creators. The lack of unauthorized use takes the problem outside copyright’s domain. The core problem is not the duplication of specific works, but the ability to produce comparable works more cheaply and quickly. The challenge cannot be resolved through the mere extension or denial of fair use, and demands we put copyright in dialog with other regimes for promoting the arts, blunting the misuse of these tools, and confronting the technology’s capacity to consolidate power.