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生成式人工智能与个人信息保护问题研究
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Abstract:
随着生成式人工智能技术的快速发展,其在提升社会生产效率的同时,也给个人信息保护带来了前所未有的挑战。本文分析了生成式人工智能在个人信息保护领域引发的诸多问题,包括数据收集的隐蔽性与超范围性、算法黑箱导致的风险、数据存储和共享的安全隐患以及数据使用的不可控性等。针对这些问题,本文提出三方面的协调路径:建立动态透明的信息告知机制,通过可视化界面和实时通知系统保障用户知情权;实施严格的数据采集源头审查制度,确保训练数据的合法性和真实性;完善算法解释说明机制,提升生成式人工智能系统的可解释性。通过对相关法律规制现状的分析,在促进技术发展的同时切实保护个人信息权益,最终实现人工智能创新与隐私保护的双赢格局。
With the rapid development of generative artificial intelligence technology, while enhancing social productivity, it has also brought unprecedented challenges to personal information protection. This paper analyzes the multiple issues raised by generative AI in the field of personal information protection, including the covert and excessive nature of data collection, risks caused by algorithmic black boxes, security vulnerabilities in data storage and sharing, as well as the uncontrolled ability of data usage. To address these challenges, this paper proposes a three-pronged coordinated approach: establishing a dynamic and transparent information disclosure mechanism to safeguard users’ right to know through visual interfaces and real-time notification systems; implementing a rigorous source review system for data collection to ensure the legality and authenticity of training data; and improving algorithmic explanation mechanisms to enhance the interpret ability of generative AI systems. Through an analysis of the current legal regulatory landscape, this paper aims to effectively protect personal information rights while promoting technological advancement, ultimately achieving a win-win scenario where AI innovation and privacy protection coexist harmoniously.
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