Artificial Code

Generative artificial intelligence (AI) has rapidly transformed software development, enabling the production of high-quality code at unprecedented speed and scale. Yet despite widespread litigation over the use of copyrighted works to train AI systems in fields such as music, journalism, and visual art, the software industry has thus far remained largely absent from the AI copyright wars. The explanation lies in the pervasiveness of free and open source software (FOSS), which has provided AI developers with a vast, low-risk corpus of training material while simultaneously insulating them from copyright liability. Ironically, however, the same AI technologies that have benefited from the FOSS ecosystem now threaten to undermine its legal and normative foundations. The core issue, this Article contends, is that much AI-generated software-what this Article terms "artificial code"-is not eligible for copyright protection under prevailing U.S. law. Because copyright requires human authorship, artificial code often falls into the public domain, rendering traditional copyright-based FOSS licensing frameworks increasingly ineffective. As copyright recedes as a viable governance mechanism, software innovators are likely to turn instead to trade secrecy and patents to protect their software innovations. These alternative regimes, while legally robust, are often at odds with the openness, reciprocity, and collaborative norms that have long defined the modern software economy. This shift has profound implications. As more software is withheld from public access or encumbered by exclusionary patent rights, the software commons risks contraction. In turn, the contraction of that commons threatens the future development of AI systems themselves. Generative models depend on continued access to large volumes of humancurated software to avoid degradation and "model collapse," as well as inventive AI innovations. If the FOSS ecosystem erodes, AI systems may find themselves deprived of the very inputs necessary to sustain their progress. By tracing the historical rise of FOSS, diagnosing the legal vulnerabilities introduced by artificial code, and examining the growing pull of alternative intellectual property regimes, this Article highlights a paradox at the heart of modern AI development: generative AI may be sowing the seeds of its own stagnation. The Article concludes by exploring how these concerns may arise in other creative contexts, too, as well as assessing possible responses aimed at preserving openness in software and AI innovation while accommodating the realities of AI-generated code.