Data Audit Rules for Generative AI: Strategic Design and Governance Pathways

Authors

Song Lang 图书馆 Author

DOI:

Keywords:

generative artificial intelligence, data risk, data audit, digital trade

Abstract

The development of generative artificial intelligence (AI) models, typically represented by ChatGPT, has become a new wave in the growth of the science and technology industry. This emerging new technology has aroused worldwide concern about its security risks, especially legal risks. Among these, data security risk is a new type of risk brought about by large generative AI models. Because of its market-oriented, routine and professional advantages, data auditing has become a feasible option for addressing data security risks, yet China’s institutional and legal supply in the field of data auditing remains insufficient. China should focus as early as possible on building and improving the industrial policies and the industrial legal basis for data auditing, and should shift the emphasis of building the data audit rule system from a one-sided protection of the value of security to an all-dimensional protection of data subjects. While improving domestic legal norms, China should also respond at the legislative level to challenges worldwide, and should devote itself to developing data audit norms that can serve global data flows and trade, so as to occupy a favorable position in the development of data audit norms at the level of international law.

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