Cloud Integrated Governance Driven Reinforcement Framework for Ethical and Legal Compliance in AI Based Regulatory Enforcement

Abstract

This paper addresses the ethical, legal, and operational challenges of using AI in regulatory enforcement, particularly concerning algorithmic bias, transparency, data protection, and privacy. It introduces a novel cloud-integrated governance-based reinforcement framework designed to ensure ethical decision-making, legal adherence, and operational efficiency. The framework incorporates multi-level governance mechanisms, dynamic compliance-driven reward algorithms, and explainable AI (XAI) models. Operating on a cloud platform for real-time updates and cross-jurisdictional compliance, the framework includes a governance-driven reinforcement component, an ethical and legal compliance layer, a dynamic reward algorithm, XAI integration, and a cross-jurisdictional compliance engine. Tested with real-world and synthetic data, the framework enhances compliance, transparency, and performance, offering a robust solution for responsible AI use in regulatory enforcement. By incorporating dynamic governance updates and real-time feedback mechanisms, the framework can continuously adapt to evolving ethical and legal standards. The integration of XAI models and the cloud-based dashboard is expected to increase transparency, resulting in higher trust scores from regulatory officers and stakeholders. Future research will extend the framework to other areas such as healthcare and energy.