摘要
在技术变革与数据累积之加速度作用下,生成式人工智能无疑带来一场空前的内容革命,也不可否认地引发诸多潜在数据风险。文章以厘清生成式人工智能的内容生成机制为起点,辩证分析其数据风险的成因并寻求化解进路。首先,从制度层面寻求数据获取行为的合法化路径。其次,充分利用现有多元机制解决数据的授权问题。最后,视具体情形将数据获取中的侵权责任在相关主体间进行合理分配。
Under the acceleration of technological change and data accumulation,generative artificial intelligence undoubtedly brings an unprecedented content revolution,and it also undeniably leads to many potential data risks.This paper starts from clarifying the content generation mechanism of generative artificial intelligence,dialectically analyzes the causes of its data risk and seeks solutions.Firstly,the legalization path of data acquisition behavior is sought from the institutional level.Secondly,make full use of existing multiple mechanisms to solve the problem of data authorization.Finally,according to the specific situation,the tort liability of data acquisition is rationally distributed among the relevant subjects.
作者
孙舒曼
Sun Shuman(Nanjing University of Finance&Economics,Nanjing,Jiangsu,210023)
出处
《市场周刊》
2024年第19期156-160,共5页
Market Weekly
关键词
生成式人工智能
数据垄断
数据风险
数据授权
generative artificial intelligence
data monopoly
data risk
data authorization
作者简介
孙舒曼,女,山东青岛人,南京财经大学法学院硕士研究生,研究方向:民商法。
