纪检监察大语言模型:应用场景、算法逻辑及治理挑战  

Disciplinary Inspection and Supervision Large Language Models:Application Scenarios,Algorithmic Logic and Governance Challenges

作　　者：李莉[1] 梁正霖 LI Li;LIANG Zhenglin(School of Discipline Inspection and Supervision,China University of Political Science and Law,Beijing 100088,China)

机构地区：[1]中国政法大学纪检监察学院,北京100088

出　　处：《成都理工大学学报(社会科学版)》2025年第3期1-11,共11页Journal of Chengdu University of Technology:Social Sciences

基　　金：国家社会科学基金重大项目(19ZDA134);国家社会科学基金一般项目(20BZZ013)。

摘　　要：随着大语言模型(Large Language Model,LLM)的快速崛起,特别是国产大模型DeepSeek在自然语言处理领域的突破性进展及其在政府治理与企业运营等场景的广泛应用,纪检监察领域智能化转型亦受到重要的影响,迎来新的技术契机。从应用实践而言,大语言模型在纪检监察工作中可以用于智能文书生成、新型腐败模式识别、跨域线索关联挖掘及网络舆情动态监测等多种场景。从算法逻辑而言,纪检监察大模型需秉持技术理性与政治伦理有效平衡的算法逻辑、分级授权数据共享机制的算法逻辑及“人机协同”模式构建的算法逻辑。与此同时,立足于国家治理现代化视域,纪检监察大模型构建面临治理挑战。基于这些挑战,可以从算法层面优化平衡技术理性与政治伦理、构建分级授权与隐私计算结合的数据防护模式、加强纪检监察干部的技术能力建设三个方面加以应对。With the rapid emergence of large language models(LLMs),particularly the groundbreaking advancements of domestic models like DeepSeek in natural language processing and their widespread applications in government and enterprise,the intelligent transformation of disciplinary inspection and supervision has also been significantly influenced,ushering in new technological opportunities.From a practical perspective,LLMs can be applied to multiple scenarios in disciplinary inspection and supervision work,including intelligent document generation,identification of novel corruption patterns,cross-domain clue correlation mining,and real-time monitoring of online public sentiment.From the algorithmic perspective,the development of the disciplinary inspection and supervision model should be structured around three core principles:balancing technical rationality with political ethics,establishing hierarchical authorization mechanisms for data sharing,and enabling human-machine collaborative governance.Simultaneously,in the context of national governance modernization,this model confronts systemic challenges that demand multidimensional solutions.To address these,strategic priorities include:optimizing the equilibrium between technical rationality and political ethics through algorithmic governance,designing a hybrid data protection framework that synergizes hierarchical authorization with privacy-preserving computing,and systematically enhancing the technical competencies of disciplinary inspection personnel.

关 键 词：纪检监察 大语言模型 应用场景 算法逻辑 治理挑战 应对策略 

分 类 号：F061.3[经济管理—政治经济学]