Unbundling AI Openness
Abstract
The debate over AI openness—whether to make components of an artificial intelligence system available for public inspection and modification—forces policymakers to balance innovation, democratized access, safety and national security. By inviting startups and researchers into the fold, it enables independent oversight and inclusive collaboration. But technology giants can also use it to entrench their own power, while adversaries can use it to shortcut years and billions of dollars in building systems, like China’s Deepseek-R1, that rival our own. How we govern AI openness today will shape the future of AI and America’s role in it.
Policymakers and scholars grasp the stakes of AI openness, but the debate is trapped in a flawed premise: that AI is either “open” and “closed.” This dangerous oversimplification—inherited from the world of open source software—belies the complex calculus at the heart of AI openness. Unlike traditional software, AI is a composite technology built on a stack of discrete components—from compute to labor—controlled by different stakeholders with competing interests. Each component’s openness is neither a binary choice nor inherently desirable. Effective governance demands a nuanced understanding of how the relative openness of each component serves some goals while undermining others. Only then can we determine the trade-offs we are willing to make and how we hope to achieve them.
This Article aims to equip policymakers with the analytical toolkit to do just that. First, it introduces a novel taxonomy of “differential openness,” unbundling AI into its constituent components and illustrating how each one has its own spectrum of openness. Second, it uses this taxonomy to systematically analyze how each component’s relative openness necessitates intricate trade-offs both within and between policy goals. Third, it operationalizes these insights, providing policymakers with a playbook for how law can be precisely calibrated to achieve optimal configurations of component openness.
AI openness is neither all or nothing nor inherently good or evil—it is a tool that must be wielded with precision if it has any hope of serving the public interest.