The Game between Efficiency and Power: Research on Privacy Risk and Compliance Path of AI Personalized Marketing

随着人工智能(AI)技术在电子商务领域的深度应用，个性化营销通过用户画像、实时推荐与动态定价显著提升了商业效率，但也引发了用户隐私保护与合规性的双重挑战。本研究以效率与权利的博弈为核心，系统剖析AI驱动营销场景下的隐私风险，包括数据过度收集、算法黑箱化及数据滥用问题，并结合法律框架(如欧盟GDPR与中国《个人信息保护法》)与行业实践，揭示电商平台面临的合规困境。研究发现，当前法律执行中存在“形式合规”与“最小必要原则模糊”等结构性矛盾，而跨境数据流动与平台责任边界模糊则加剧了行业特殊性挑战。为平衡效率与隐私，本文提出三重建构路径：技术层面深化隐私计算(联邦学习、差分隐私)以保障数据安全；治理层面通过透明化设计与算法解释功能破解信任危机；用户权益层面以简化控制选项与数据收益共享机制增强主权意识。研究强调，AI营销的可持续发展需以“效率–隐私–信任”三角平衡为目标，通过技术创新、制度优化与多方协作实现合规与效率的动态统一，为电商平台及监管机构提供理论与实践参考。With the deep application of artificial intelligence (AI) technology in e-commerce, personalized marketing has significantly improved business efficiency through user profiles, real-time recommendations and dynamic pricing, but it also raises the dual challenges of user privacy protection and compliance. With the game between efficiency and rights as the core, this study systematically analyzes the privacy risks in AI-driven marketing scenarios, including excessive data collection, algorithm black box and data abuse, and combines legal frameworks (such as EU GDPR and China’s “Personal Information Protection Law”) and industry practices to reveal the compliance dilemma faced by e-commerce platforms. The study found that there are structural contradictions in the current law enforcement such as “formal compliance” and “ambiguity of the principle of least necessity”, while the cross-border data flow and the ambiguity of platform responsibility boundary exacerbate the challenges of industry particularity. In order to balance efficiency and privacy, this paper proposes a threefold construction path: deepening privacy computing (federated learning, differential privacy) at the technical level to ensure data security; At the governance level, the trust crisis is solved through transparent design and algorithm interpretation. At the level of user rights, it enhances the awareness of sovereignty by simplifying control options and data revenue sharing mechanism. The research emphasizes that the sustainable development of AI marketing should aim at the triangle balance of “efficiency-privacy-trust”, and achieve the dynamic unity of compliance and efficiency through technological innovation, system optimization and multi-party collaboration, so as to provide theoretical and practical reference for e-commerce platforms and regulatory agencies.