生成式人工智能驱动下跨境贸易安全管理的机遇、挑战与治理路径

Generative AI-Driven Cross-Border Trade Security Management: Opportunities, Challenges, and Governance Pathways

摘要: 生成式人工智能的快速发展正在推动跨境数字贸易的技术升级，其在提升贸易效率和优化数据管理的同时，也带来了复杂的安全与治理挑战。本文系统分析了生成式人工智能在跨境贸易中的智能数据分类、匿名化处理和动态访问控制等技术优势，揭示其在提升数据安全性与贸易效率方面的作用。同时，从用户权益、伦理规范、监管合规和技术治理等多维视角深入探讨了生成式人工智能带来的潜在风险。研究进一步提出“技术–规则–治理”协同框架，包括算法审计机制的建立、技术标准适应性设计、开发者责任与信用体系完善，以及动态风险应对机制的创新。研究结论为企业和平台在推进数字贸易应用过程中提供了可行的技术与治理参考，有助于实现安全、可控与高效的数据流通环境。

Abstract: Generative Artificial Intelligence is reshaping the global landscape of cross-border trade. While enhancing trade efficiency and optimizing data management, it also brings complex security and ethical challenges. This paper systematically analyzes the technical advantages of Generative Artificial Intelligence in cross-border trade, including intelligent data classification, anonymization, and dynamic access control, revealing its central role in improving data security and trade performance. At the same time, from multiple perspectives—including user rights, ethical standards, regulatory frameworks, and technical governance—it explores the security risks posed by Generative Artificial Intelligence. The study further proposes a “technology-regulation-ethics” collaborative governance framework, encompassing the establishment of a global algorithm audit alliance, the formulation of sovereignty-adaptive technical standards, the improvement of developer ethical credit systems, and the innovation of dynamic risk response mechanisms. The findings provide policymakers and enterprises with practical pathways to balance technological innovation with risk management, contributing to the construction of an open, secure, and fair global digital trade ecosystem.