Compliance Risk Evolution Mechanism and Dynamic Governance Paradigm of Generative Artificial Intelligence—An Empirical Study Based on Five-Dimensional Assessment Matrix and Legal-Technical Synergy
生成式人工智能的快速迭代与现有法律框架的静态监管冲突,催生了数据安全、算法伦理与责任归属等多维合规风险。本文通过构建“五维评估矩阵”(数据安全、算法透明性、内容合规、元规制效能、动态适应性),提出动态分层风险评估模型,创新性地整合熵权法与LSTM时序修正机制,量化技术迭代速度(TCRS% ≥ 80%)与合规更新延迟率(CUD% ≤ 10%)等核心指标。实证研究表明,该模型可将合规失效概率降低61%,并通过监管沙盒验证法律–技术协同工具链的有效性。研究发现:(1) 生成式人工智能的“涌现能力”导致风险传导呈现非线性特征,需通过全周期动态阈值设计实现敏捷治理;(2) 企业合规能力缺口源于法律抽象性与技术黑箱的协同性矛盾,区块链存证与智能合约可提升算法备案率至100%;(3) 跨国合规冲突需构建分层豁免规则,结合GDPR与中国《生成式人工智能服务管理暂行办法》的双轨制验证框架。本文为AI企业提供了兼具严谨性与灵活性的合规操作范式,并为全球治理体系优化贡献中国方案。The rapid iteration of generative artificial intelligence (GAI) conflicts with static regulatory frameworks, leading to multidimensional compliance risks in data security, algorithmic ethics, and liability attribution. This study constructs a “Five-Dimensional Assessment Matrix” (data security, algorithmic transparency, content compliance, meta-regulatory efficacy, and dynamic adaptability) and proposes a dynamic layered risk assessment model. By innovatively integrating the entropy weight method and LSTM temporal correction mechanisms, it quantifies core indicators such as technical iteration compliance synchronization rate (TCRS% ≥ 80%) and compliance update delay rate (CUD% ≤ 10%). Empirical results demonstrate that the model reduces compliance failure probability by 61% and validates the effectiveness of legal-technical collaborative toolchains through regulatory sandbox testing. Key findings include: (1) The “emergent capabilities” of GAI result in nonlinear risk transmission, necessitating agile governance via full-cycle dynamic threshold design; (2) The corporate compliance gap stems from the synergy contradiction between legal abstraction and technical opacity, where blockchain-based evidence preservation and smart contracts elevate algorithm filing rates to 100%; (3) Transnational compliance conflicts require hierarchical exemption rules, supported by a dual-track verification framework aligning GDPR with China’s Interim Measures for Generative AI Services. This research provides a rigorous yet flexible compliance paradigm for AI enterprises and contributes Chinese insights to global governance system optimization.
Authors
- 家媛 张
Publication Details
- Journal
- Advances in Social Sciences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.12677/ass.2025.146567
- Citations
- 1
- Primary Topic
- Legal and Policy Issues
- Type
- article
- Field-Weighted Citation Impact
- 15.98