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About this paper
Naoshi Uchihira
Naoshi Uchihira, from the Japan Advanced Institute of Science and Technology, proposes the "GenAI SECI" model, an updated framework for organizational knowledge creation that integrates generative AI capabilities into the traditional SECI processes. The model introduces "Digital Fragmented Knowledge" to address the management of partial and latent workplace knowledge and details a "Digital Knowledge Twin System" as a practical architecture where GenAI serves as an auxiliary tool to support human knowledge internalization and "symbol grounding."
Key insights
- Generative AI can effectively process and utilize "Digital Fragmented Knowledge"—partial and incomplete information—which traditional KM systems struggled to manage, thereby unlocking previously inaccessible knowledge assets.
- Generative AI should be strictly positioned as an auxiliary means to support human knowledge creation and internalization, rather than as an autonomous actor, ensuring a human-centric approach to knowledge management.
- "Symbol grounding," the critical process of connecting abstract knowledge to concrete experience for true understanding and actionable insights, remains an indispensable human task that GenAI facilitates but does not perform autonomously.
Summary by alphaXiv.
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