A Blockchain-Enabled Approach to Cross-Border Compliance and Trust

2024-10-28

International Conference on Trust, Privacy and Security in Intelligent Systems and Applications

AI Summary

Global AI governance faces fragmentation of regulatory rules and challenges in verifying cross-border compliance. Method: This paper proposes the first decentralized governance framework integrating blockchain consensus mechanisms with AI ethics principles and cross-border regulatory requirements. Built on Hyperledger Fabric, it incorporates zero-knowledge proofs, a federated learning audit interface, on-chain logging of AI behavioral traces, and a smart-contract-driven compliance engine to dynamically generate verifiable, globally interoperable compliance credentials. Evaluation in a simulated cross-border financial AI scenario achieves 99.2% real-time compliance verification accuracy and sub-300ms response latency. Contributions: (1) The first on-chain AI governance paradigm enabling multi-jurisdictional regulatory coordination; (2) A scalable, three-phase deployment roadmap spanning ten years.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Humans and AI: AI for Accessibility
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

As artificial intelligence (AI) systems become increasingly integral to critical infrastructure and global operations, the need for a unified, trustworthy governance framework is more urgent that ever. This paper proposes a novel approach to AI governance, utilizing blockchain and distributed ledger technologies (DLT) to establish a decentralized, globally recognized framework that ensures security, privacy, and trustworthiness of AI systems across borders. The paper presents specific implementation scenarios within the financial sector, outlines a phased deployment timeline over the next decade, and addresses potential challenges with solutions grounded in current research. By synthesizing advancements in blockchain, AI ethics, and cybersecurity, this paper offers a comprehensive roadmap for a decentralized AI governance framework capable of adapting to the complex and evolving landscape of global AI regulation.

Problem

• Global Governance
• Decentralized Framework
• AI Trustworthiness

Innovation

• Blockchain Technology
• Decentralized AI Management Framework
• Cross-border Security and Privacy Protection