The King Solomon Protocol™ proposes a framework for human supervised arbitration in multi model artificial intelligence systems operating within institutional environments. The paper argues that contradictions between AI systems generate what it terms interpretive debt, a burden frequently transferred to end users who must reconcile conflicting outputs without sufficient authority or context. Drawing on the Equilibrium Ledger Research Programme™, the work introduces a dual assistant architecture, the concepts of the Institutional Mind and Safeguarding Inversion, and a structured human arbitration layer designed to resolve contradiction before it reaches vulnerable users. Positioned at the intersection of philosophy of technology, AI governance, institutional theory, and disability studies, the paper explores the limits of automation and the continuing role of human judgment in safety critical decision making. ( direct link )