人工智能大模型对档案学基础理论的挑战及其回应  

Challenges of Artificial Intelligence Large Models to the Basic Theory of Archival Science and Its Response

作　　者：徐拥军[1,2] 陈晓婷 闫静[3] XU Yongjun;CHEN Xiaoting;YAN Jing(School of Information Resources Management,Renmin University of China,Beijing,100871;Archival Undertaking Development Research Center,Renmin University of China,Beijing,100871;School of History,Shandong University,Jinan,250100)

机构地区：[1]中国人民大学信息资源管理学院,北京100871 [2]中国人民大学档案事业发展研究中心,北京100871 [3]山东大学历史学院,济南250100

出　　处：《图书情报知识》2025年第1期57-69,共13页Documentation,Information & Knowledge

基　　金：中国人民大学科学研究基金项目(中央高校基本科研业务费专项资金资助)“中国自主的档案学知识体系建构”(24XNN012)的研究成果之一。

摘　　要：[目的/意义]人工智能大模型对档案学基础理论带来挑战和变革,亟需探讨其如何推动档案学基础理论的创新与发展。[研究设计/方法]通过对比传统时代和人工智能时代档案学基础理论的内容要点,阐述档案学基础理论对大模型挑战的回应,进一步解释“大模型如何影响档案学基础理论?而档案学基础理论又应当如何回应大模型发起的挑战?”[结论/发现]大模型对档案学基础理论提出了来源原则概念狭窄,文件生命周期延伸、档案价值转化,档案鉴定理论缺失可信性、销而不毁,档案记忆观的建构主体危机等挑战。为回应这些挑战,档案学基础理论需进行自我调适和创新:新来源观概念与背景的再发现,强调文件生命周期的动态连续性,关注档案鉴定理论的可信度检测与被遗忘权,规范算法权力和掌握记忆话语权。[创新/价值]从理论层面重新审视大模型对档案学基础理论的挑战,以及档案学基础理论应如何进行自我修正以做出恰当回应,切实为人工智能时代的档案工作提供理论指导。[Purpose/Significance]The large models of artificial intelligence pose challenges and transformations to the basic theories of archival science,and it is urgent to explore how the large models can drive the innovation and advancement in the basic theories of archival science.[Design/Methodology]By comparing the key points of the basic theories of archival science in the traditional era and the era of artificial intelligence,this paper elaborates the response of the basic theories of archival science to the challenges of the large models,and further explains the question"How do the large models of artificial intelligence affect the basic theories of archival science?And how should the basic theories of archival science respond to the challenge posed by the large models of artificial intelligence?"[Findings/Conclusion]The large models of artificial intelligence have brought challenges to the basic theories of archival science,such as the narrow concept of the principle of provenance,the extension of the records life cycle theory,the transformation of archival value,the lack of credibility in archival appraisal theory,the pin but not destroy,and the crisis of the subject of the construction of the archival memory concept.In response to these challenges,the basic theories of archival science need to undergo self-adjustment and innovation:rediscover the concepts and contexts of the new provenance perspective,emphasize the dynamic continuity of the records life cycle,focus on the credibility assessment in archival appraisal theory and the right to be forgotten,regulate the power of algorithmic,and assert control over the discourse of memory.[Originality/Value]From a theoretical perspective,this article re-examines the challenges posed by large models to the basic theories of archival science,and how the basic theories of archival science should self-correct to respond appropriately,so as to provide theoretical guidance for archival work in the era of artificial intelligence.

关 键 词：人工智能 大模型 档案学基础理论 档案工作 

分 类 号：G270.7[文化科学—档案学]