INFORMATION RESEARCH

Large Language Models Trustworthiness: Connotation, Influence, Challenges and Strategy

  • Qian Minghui ,
  • Li Hurong ,
  • Yang Jianliang
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  • 1 School of Information Resource Management, Renmin University of China, Beijing 100872;
    2 Intelligent Information Analysis Research Center, Renmin University of China, Beijing 100872;
    3 Institute of Digital Humanities, Renmin University of China, Beijing 100872

Received date: 2024-03-22

  Revised date: 2024-06-18

  Online published: 2024-10-29

Supported by

This work is supported by the key project of National Social Science Fund of China titled “Innovation and Application of Information Analysis Methods Based on Digital Intelligence Fusion” (Grant No. 22AZD158).

Abstract

[Purpose/Significance] Large language models trustworthiness can ensure their reliable and safe deployment in key fields such as healthcare, education, and law, and gain the public trust. It is important to promote the healthy and sustainable development of generative artificial intelligence technology. [Method/Process] This paper uses the literature research to analyze the relevant literature on the large language models trustworthiness. It comprehensively analyzes the large language models trustworthiness from four aspects: its concept and connotation, its influencing factors, the challenges, and the “TRUE” strategy. [Result/Conclusion] The research on the large language models trustwortiness is still in the exploratory stage. Starting from its connotation, influence, challenges, it establishes a “TRUE” strategy system of information technology, information resources, information users and information environment, in order to promote the reasonable use of LLM and drive the development of generative artificial intelligence towards a better future.

Cite this article

Qian Minghui , Li Hurong , Yang Jianliang . Large Language Models Trustworthiness: Connotation, Influence, Challenges and Strategy[J]. Library and Information Service, 2024 , 68(20) : 69 -86 . DOI: 10.13266/j.issn.0252-3116.2024.20.007

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