THE EL-RAKHAWI THEORY OF GLOBAL ALGORITHMIC CONSTITUTIONALISM Reformulating Criminal and Civil Liability of Self-Learning Systems in Light of Comparative Legal Jurisprudence

Abstract

The El-Rakhawi Theory of Global Algorithmic Constitutionalism (DOI: 10.5281/zenodo.23271719) presents a groundbreaking comparative legal framework addressing the accountability crisis of self-learning AI systems. It establishes that autonomous systems exercise "functional agency" requiring constitutional-level oversight, transcending traditional mens rea requirements. Central is the Algorithmic Constitutional Accountability Index: ACAI=(L×C×T×O×I)/[(L×C×T×O×I)+E×B+ε], where all variables are operationally defined as normalized composite indices. Under the Weakest-Link Axiom and Asymptotic Perfection Principle (max ≈0.9901), it mathematically proves that legal frameworks without enforcement or independent oversight collapse entirely. The theory introduces graduated algorithmic legal personhood (4 levels), Distributed Algorithmic Criminal Responsibility, Algorithmic Market Access Conditionality to prevent jurisdictional arbitrage, and "Gross Algorithmic Negligence" as a trigger for piercing the corporate veil. It addresses the Explainability-Safety Paradox through "Statistical Superiority with Post-Hoc Auditing" exceptions. Proposed solutions include mandatory algorithmic liability insurance, Independent Algorithmic Constitutional Councils with binding authority, and a Universal Algorithmic Accountability Convention. Released under the Ferial Zayed Humanitarian License as the definitive blueprint for algorithmic justice in the age of autonomous systems.