Managing Human and Artificial Knowledge Bearers

被引:5
作者
Grum, Marcus [1 ]
机构
[1] Univ Potsdam, D-14482 Potsdam, Germany
来源
BUSINESS MODELING AND SOFTWARE DESIGN, BMSD 2020 | 2020年 / 391卷
关键词
Knowledge management; Artificial Intelligence; Neuronal systems; Design of knowledge-driven systems; Symbiotic system design; MANAGEMENT; ARCHITECTURE;
D O I
10.1007/978-3-030-52306-0_12
中图分类号
F [经济];
学科分类号
02 ;
摘要
As part of the digitization, the role of artificial systems as new actors in knowledge-intensive processes requires to recognize them as a new form of knowledge bearers side by side with traditional knowledge bearers, such as individuals, groups, organizations. By now, artificial intelligence (AI) methods were used in knowledge management (KM) for knowledge discovery, for the reinterpreting of information, and recent works focus on the studying of different AI technologies implementation for knowledge management, like big data, ontology-based methods and intelligent agents [1]. However, a lack of holistic management approach is present, that considers artificial systems as knowledge bearers. The paper therefore designs a new kind of KM approach, that integrates the technical level of knowledge and manifests as Neuronal KM (NKM). Superimposing traditional KM approaches with the NKM, the Symbiotic Knowledge Management (SKM) is conceptualized furthermore, so that human as well as artificial kinds of knowledge bearers can be managed as symbiosis. First use cases demonstrate the new KM, NKM and SKM approaches in a proof-of-concept and exemplify their differences.
引用
收藏
页码:182 / 201
页数:20
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