Managing human and artificial knowledge bearers
- 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 asAs 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.…
| Author details: | Marcus GrumORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1007/978-3-030-52306-0_12 |
| ISBN: | 978-3-030-52305-3 |
| ISBN: | 978-3-030-52306-0 |
| Title of parent work (English): | Business modeling and software design : 10th International Symposium, BMSD 2020, Berlin, Germany, July 6-8, 2020, Proceedings |
| Subtitle (English): | the creation of a symbiotic knowledge management approach |
| Publisher: | Springer International Publishing AG |
| Place of publishing: | Cham |
| Editor(s): | Boris Shishkov |
| Publication type: | Part of a Book |
| Language: | English |
| Date of first publication: | 2020/07/07 |
| Publication year: | 2020 |
| Release date: | 2023/10/12 |
| Tag: | artificial intelligence; design of knowledge-driven systems; knowledge management; neuronal systems; symbiotic system design |
| Number of pages: | 20 |
| First page: | 182 |
| Last Page: | 201 |
| Organizational units: | Wirtschafts- und Sozialwissenschaftliche Fakultät / Wirtschaftswissenschaften / Fachgruppe Betriebswirtschaftslehre |
| DDC classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
| Peer review: | Nicht ermittelbar |
