ANOA — Essay XVI: The Axiomatic Theory of Constitutional Stability, Systemic Resilience and Common Welfare in AI-Native Civilizations
Year: 2026
Type: article
Abstract: This paper develops an integrated axiomatic framework for constitutional stability, systemic resilience, and common welfare in AI-native civilizations, with particular attention to agentic artificial intelligence, federated protocols, geopolitical sovereignty, and monetary stability. The study examines the conditions under which heterogeneous sovereign jurisdictions can cooperate through interoperable computational infrastructures without transferring constitutional authority to autonomous agents or technological protocols. A multilayer theoretical model connects human rights, sovereign institutions, protocol governance, agentic execution, monetary circulation, critical infrastructure, and real economic welfare. The framework distinguishes technical stability from systemic resilience, legal authorization from protocol conformance, and aggregate economic performance from distribution-sensitive human welfare. The manuscript presents twelve axioms, conditional mathematical propositions, counterexamples, a robust viability criterion, and institutional stress scenarios addressing financial instability, geopolitical fragmentation, infrastructure concentration, synchronized agentic behavior, and cross-border regulatory conflicts. The central proposition is that AI-native economic coordination does not require a single global political authority, universal currency, central bank digital currency, or blockchain infrastructure. Instead, institutional cooperation may be supported by federated protocols operating within existing legal and monetary jurisdictions. The research advances a human-centered institutional perspective in which technological progress is evaluated through stability, recoverability, constitutional legitimacy, and the preservation of essential human welfare. Research status: Independent theoretical working paper. Mathematical results are conditional on explicitly stated assumptions. The proposed architecture has not been empirically validated or independently peer-reviewed. Research framework: ANOA — AI-Native Organizational Architecture. Author: Marco Patrone. DOI: 10.5281/zenodo.24054157.
Author: Patrone, Marco
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225580463