生成式人工智能引发的信息过载风险及其对策研究*

Research on the Risk of Information Overload Induced by Generative Artificial Intelligence and its CountermeasuresWANG huimin

摘要:

随着生成式人工智能(GAI)在各领域的广泛应用,其强大的信息生成能力容易诱发信息过载的风险,进而可能导致信息质量下降和筛选困难。故而,有必要深入探讨GAI引发的信息过载问题。通过分析GAI导致信息过载具体表现与成因,针对不同的问题提出具体的解决方案。GAI引发的信息过载风险主要表现为三个方面:其一,信息质量的下降；其二,信息筛选的困难；其三,信息的同质化。未来可以通过优化训练数据的质量和多样性、强化信息分类与过滤机制、改善信息展示与交互方式以及

Abstract:

With the wide application of Generative Artificial Intelligence (GAI) in various fields, its powerful information generation ability easily induces the risk of information overload, which may lead to the degradation of information quality and the difficulty of screening. Therefore, it is necessary to deeply explore the problem of information overload caused by GAI. By analyzing the specific manifestations and causes of information overload caused by GAI, specific solutions are proposed for different problems. The risk of information overload caused by GAI is mainly manifested in three aspects: first, the decline of information quality; Second, the difficulty of information filtering; Third, the homogenization of information. In the future, the risk of information overload caused by GAI can be alleviated by optimizing the quality and diversity of training data, strengthening the mechanism of information classification and filtering, improving the way of information display and interaction, and promoting data fusion. This study not only improves the understanding of the problem of information overload caused by GAI, but also provides a feasible solution for practical operation, which has certain theoretical and practical significance.