Data security risks of generative large model and its legal governance
Liu Yiming1，Lin Zihan2
1 Institute of Cyber Governance, Wuhan University, Wuhan 430072, China; 2 Shanghai Data Exchange, Shanghai 201203, China
Abstract： Generative large models have a wide range of application prospects, however, the training and operation of those models need the support of massive data, which is very likely to cause data security risks. Cognitive risk is the premise of risk resolution, and it is necessary to establish a cognitive system of data security risk of generative model application from both static and dynamic perspectives. Combining the governance experience of generative models in the EU and the United States, and addressing the deficiencies in the governance of data security risks of generative models in China, it is recommended to establish a categorized regulatory path based on data security risks, improve the data security responsibility system based on the whole process of large model operation, and explore the innovative regulatory mechanism based on the inclusive and prudent regulation, in order to provide sufficient rule of law guarantee for realizing the credible future of large model applications.
Key words : generative large model; data security risk; ChatGPT; risk classification
