When Recommendation Must Cease: Structural Limits of AI Guidance in Irreversible Aeronautical Regimes Author

aeronautical systems increasingly rely on artificial intelligence to generate real-time recommendations under uncertainty. This paper identifies a fundamental structural limit to such systems: there exist regimes in which no recommendation can remain causally valid within a given reference frame, independently of data quality or model accuracy.We show that beyond specific thresholds of irreversibility, the space of admissible actions collapses into what we term a knot regime, in which all candidate recommendations entail unavoidable structural loss. In such regimes, continued recommendation is not merely suboptimal but logically illegitimate.The result is non-empirical, non-ontological, and independent of any specific physical law. It establishes a necessary condition for legitimate recommendation in safety-critical systems and implies that silence can constitute a formally valid, and ethically required, system output.