从失范到规范:生成式人工智能的监管框架革新

From illegal to legal:evolving regulatory frameworks for generative artificial intelligence

生成式人工智能在技术变革下引发的失范性风险,对既有人工智能监管框架提出了挑战。从底层技术机理出发,可知当前生成式人工智能呈现出“基础模型-专业模型-服务应用”的分层业态,分别面临算法监管工具失灵、训练数据侵权风险加剧、各层级间法律定位不明、责任界限划分不清等监管挑战。为此需以分层监管为逻辑内核,对我国既有人工智能监管框架进行革新。在监管方式上应善用提示工程、机器遗忘等科技监管工具;在责任划定上应进行主体拆解与分层回溯,从而规范“基础模型-专业模型-服务应用”的分层监管框架,以期实现有效监管,促进生成式人工智能的高质量发展。

The risk of aberration caused by generative artificial intelligence under technological change challenges the existing artificial intelligence regulatory system.Starting from the underlying technical mechanism,it can be seen that the current generative artificial intelligence presents a hierarchical format of"basic model-professional model-service application",and faces regulatory challenges such as the failure of algorithm supervision tools,the intensified risk of training data infringement,the unclear legal positioning between different levels,and the unclear division of responsibility boundaries.Therefore,it is necessary to take layered regulation as the logical core and reform the existing artificial intelligence regulatory framework in China.In the way of supervision,we should make good use of technology supervision tools such as prompt engineering and machine forgetting.In the delineation of responsibilities,the main body should be disassembled and hierarchical backtracking should be carried out,so as to standardize the hierarchical regulatory framework of"basic model-professional model-service application",in order to achieve effective supervision and promote the healthy and high-quality development of generated artificial intelligence.