arXiv:2603.21866cs.AI2026-03被引 2

用生成式AI整合隐性与显性知识,构建新型知识管理模型

Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model

  • 提出GenAI SECI模型,融合生成式AI能力重构知识创造流程
  • 引入'数字碎片化知识'概念,实现显性与隐性知识在数字空间的融合
  • 提供可落地的系统架构,适合组织知识管理与AI融合研究者参考

生成式AI正深刻改变知识管理格局。尽管其在显性知识管理方面已有广泛应用,但对隐性知识的系统化处理仍不足。本文提出更新版的SECI知识创造模型——GenAI SECI,旨在充分挖掘生成式AI在知识转化中的潜力。核心创新在于提出‘数字碎片化知识’这一新概念,将显性与隐性知识在数字空间中进行整合。同时,本文设计了具体的系统架构,并与先前具有相似目标的研究模型进行了对比分析,为知识管理的智能化演进提供了理论框架与实践路径。

原文摘要 · Abstract (English)

The emergence of generative AI is bringing about a significant transformation in knowledge management. Generative AI has the potential to address the limitations of conventional knowledge management systems, and it is increasingly being deployed in real-world settings with promising results. Related research is also expanding rapidly. However, much of this work focuses on research and practice related to the management of explicit knowledge. While fragmentary efforts have been made regarding the management of tacit knowledge using generative AI, the modeling and systematization that handle both tacit and explicit knowledge in an integrated manner remain insufficient. In this paper, we propose the "GenAI SECI" model as an updated version of the knowledge creation process (SECI) model, redesigned to leverage the capabilities of generative AI. A defining feature of the "GenAI SECI" model is the introduction of "Digital Fragmented Knowledge", a new concept that integrates explicit and tacit knowledge within cyberspace. Furthermore, a concrete system architecture for the proposed model is presented, along with a comparison with prior research models that share a similar problem awareness and objectives.

知识管理生成式AI隐性知识SECI模型

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