生成式人工智能应用的社会风险与法律因应

Social Risks and Legal Responses to Generative Artificial Intelligence Applications

摘要: 生成式人工智能通过深度学习和大数据训练，能够生成高质量的内容，但其应用引发在个人隐私、算法偏见、间接侵权、权属界定等多方面引发了社会风险。本文从生成式人工智能的技术原理着手，将生成过程拆分为数据获取、数据处理、成果生成与成果存储四个阶段；各阶段社会风险集中体现为个人隐私风险、算法偏见风险、间接侵权风险与生成成果的权属界定风险。通过进一步探讨了这些风险的成因，本文提出要明确责任主体、健全多元监管机制和完善法律保障体系等规制进路，以期在保障个体权益和公共利益的同时，促进人工智能产业的良性发展。

Abstract: Generative artificial intelligence can generate high-quality content through deep learning and big data training, but its application triggers social risks in terms of personal privacy, algorithmic bias, indirect infringement, and ownership definition. In this paper, starting from the technical principle of generative AI, the generation process is divided into four stages: data acquisition, data processing, result generation and result storage; the social risks in each stage are centered on the risks of personal privacy, algorithmic bias, indirect infringement, and ownership definition of the generated results. By further exploring the causes of these risks, this paper proposes to clarify the main body of responsibility, improve the multifaceted regulatory mechanism and perfect the legal protection system and other regulatory approaches, with a view to promoting the benign development of the AI industry while safeguarding the rights and interests of individuals and the public interest.