利用生成式AI管理隐性知识:GenAI SECI模型提案 / Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model
1️⃣ 一句话总结
这篇论文针对现有知识管理研究过于关注显性知识的问题,提出了一个整合了生成式AI能力的升级版知识创造模型(GenAI SECI),其核心创新是引入“数字碎片化知识”这一新概念,以系统化地管理并融合显性知识与隐性知识。
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.
利用生成式AI管理隐性知识:GenAI SECI模型提案 / Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model
这篇论文针对现有知识管理研究过于关注显性知识的问题,提出了一个整合了生成式AI能力的升级版知识创造模型(GenAI SECI),其核心创新是引入“数字碎片化知识”这一新概念,以系统化地管理并融合显性知识与隐性知识。
源自 arXiv: 2603.21866