Toward a Unified Theory of Knowledge Sharing: Artificial Intelligence, Epistemic Justice, and Platform-Mediated Tacit Knowledge in the Digital Age

Moody Wahongan, Niel Ananto

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Knowledge sharing is undergoing a paradigm shift driven by three converging forces: the integration of artificial intelligence (AI) into knowledge management systems, the platform-mediated reconstitution of tacit knowledge, and the rise of open science and epistemic justice movements. This study aims to examine whether existing frameworks, particularly Nonaka and Takeuchi's SECI model, remain adequate for explaining knowledge sharing under these conditions, and to propose an integrative alternative. The study employs a conceptual research design based on a theoretical synthesis of peer-reviewed literature published between 2018 and 2025. The results show that AI is shifting knowledge repositories from passive storage to active brokering, that the tacit-explicit boundary behaves as a variable permeability shaped by relationships, platforms, culture, and AI, and that platform governance functions as knowledge governance that determines whose knowledge flows. Based on these findings, the study proposes the Dynamic Knowledge Flow Model (DKFM), which consists of four layers (knowledge substrate, AI augmentation, platform mediation, and epistemic justice) and three dynamic properties (endogenous boundary reconstitution, bi-directional causation between layers, and organizational culture as a binding medium). The DKFM reframes knowledge sharing as a system rather than a dyadic transaction. The study concludes with practical implications for knowledge management and six priority directions for future research.
Keywords: knowledge sharing; artificial intelligence; tacit knowledge; epistemic justice; knowledge management=

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DOI: https://doi.org/10.37531/mirai.v12i1.12970

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