ABSTRACT
In response to the threats posed by new copy-reliant technologies, copyright law often expands in scope. Frequently this results in overzealous rights enforcement and the suppression of lawful user expression. Generative AI is shaping up to be no different. Owners of copyrighted training data have asked the courts to find AI outputs to be infringing in the absence of substantial similarity, and to prohibit unlicensed training despite its extraction of unprotectable metadata. Many service providers automatically block or modify user prompts that retrieve copyrighted content even though fair use is a fact-specific inquiry.
These trends threaten to undermine the democratic and egalitarian potential of generative AI. Generative AI has the capacity to democratize cultural production by distributing powerful and accessible tools to previously excluded creator communities. Ordinary individuals can now create sophisticated synthetic media by modifying, remixing, and transforming cultural works without any artistic training or skills. This radically expands the range of individuals who can engage in aesthetic practice, irrespective of the legal status or exchange value of the resulting output.
To date, however, the democratic and egalitarian character of generative AI has been relatively under-theorized. Lawmakers are focused on averting two possible outcomes: the extinction of human artists, or the flight of technological capital to low-IP jurisdictions. As copyright owners and technology firms dominate public discourse, relatively little attention is paid to the expressive interests of users. This Article remedies that neglect by directing scholarly attention to the democratizing effects of generative AI. It suggests that jurists should not rush to pacify owners of copyrighted training data by enjoining generative models, or pressuring service providers to adopt unnecessary use restrictions. Instead, Congress should embrace the democratic and egalitarian potential of generative AI by protecting users from the chilling effects of infringement liability. This Article canvasses a range of options directed towards this objective, including a non-commercial use provision, a compulsory licensing regime for commercial generations, a DMCA-style safe harbor for service providers, and a presumption of user authorship of AI generations.
Geddes, Katrina, How Art Became Posthuman: Copyright, AI, and Synthetic Media (June 14, 2024).
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