Interpretive Symmetry and the Foundations of Legitimate AI Governance

As artificial intelligence systems grow in capability and autonomy, a structural transformation threatens the foundations of legitimate governance: the systematic erosion of human comprehension at scale. This paper develops interpretive symmetry as a maintained equilibrium between system complexity and human interpretive capacity, as a constitutive requirement for legitimate authority over autonomous systems. I argue that comprehension is not merely instrumental to effective control but constitutive of legitimate governance itself: when those responsible for oversight lose the capacity to understand what they govern, authority becomes domination regardless of other safeguards. Drawing on recognition theory, communicative rationality, and capabilities approaches, I defend interpretive symmetry against skeptical, posthumanist, and techno-optimist objections, develop a positive account of what interpretive governance enables, and show why this requirement applies specifically and urgently to AI systems in ways that distinguish them from other complex technologies. The framework has implications for democratic theory, institutional design, and the political economy of knowledge in technological societies.