Abstract. Calls for comprehensive regulation of artificial intelligence have intensified
as the technology’s capabilities have grown. Such calls conflate two distinct regulatory
objects: the domestic application of AI systems, which is already underway and broadly
feasible, and the development of increasingly capable AI systems at the global frontier,
the subject of this paper, where the structural constraints attenuate traditional regulatory
approaches. This paper examines three structural features of AI development that define
the constraint envelope within which any workable governance policy must operate: a
verification problem that makes enforcement fundamentally different from previous
dual-use technology regimes; a self-interest problem that will shape international
compliance in predictable ways; and a beneficial applications problem that creates an
unfavorable political economy for sustained restraint. Understanding these constraints
does not counsel despair, but it does counsel realism — a shift to shaping AI
development rather than preventing it, to strengthening resilience, and less ambitiously
but more honestly, ensuring that whoever sits at the frontier does so with some
transparency and accountability. The result is a menu of policy recommendations that
are achievable under real-world constraints.
Read more here.