This paper presents Kinetic Alignment of Domains (KAD Theory), a unified control theoretic framework for modeling failure across engineered, cognitive, and organizational systems. The theory formalizes misalignment as the fundamental driver of failure under partial and dy namic observability. By embedding agent domain interaction within a measurable Hilbert spaceand introducing visibility as a conditional expectation operator, KAD establishes a closed dynamical system governing alignment. A key result is the Information Failure Law, which proves that unobserved domain components impose a strict lower bound on achievable alignment. The framework further introduces dual control over action and perception, yielding a generalized stability criterion under stochastic drift. This work provides a mathematically rigorous foundation for alignment, bridging control theory, AI safety, and socio-technical governance.
Usman Zafar (Sun,) studied this question.