DFAS-PAG (V1.0): PostObjective Autonomy Governance Doctrine — Embedding Sovereignty, Explainability, and Enforceability Beyond Ethics-Washing

This manuscript introduces the DFAS-PAG (PostObjective Autonomy Governance Doctrine), a forward-thinking framework addressing the growing intersection between artificial intelligence and public authority. It critically examines the structural, legal, and ethical challenges arising from AI integration in public sector decision-making, with a specific focus on sovereignty, accountability, explainability, and institutional resilience. The work identifies key vulnerabilities in current governance models—particularly in relation to algorithmic opacity, vendor dependency, and the erosion of localized control—arguing that traditional ethics-based approaches are insufficient. Instead, it advocates for enforceable, sovereign-aligned mechanisms that preserve democratic oversight and institutional integrity in the face of increasing automation. The manuscript contributes to global discourse on AI governance by highlighting the need for actionable doctrines that align technological progress with public trust, operational legitimacy, and systemic transparency.