| Title |
The Meaningfulness of Knowledge for the Design of Sustainable AI |
| ID_Doc |
65458 |
| Authors |
Grum, M; Gronau, N |
| Title |
The Meaningfulness of Knowledge for the Design of Sustainable AI |
| Year |
2024 |
| Published |
International Journal Of Knowledge Management, 20.0, 1 |
| DOI |
10.4018/IJKM.350409 |
| Abstract |
A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the necessary transfer of knowledge between individuals in business processes can lead to a huge competitive advantage, for instance, if intelligent information systems are enabled to analyze complex patterns of knowledge flows and adapt to the individual knowledge transfer situation. This paper introduces a time-dependent knowledge transfer model incl. an experimentation tool with the intention of predicting and furthermore accelerating the speed of knowledge transfer among people and information systems. While intelligent information systems start to function as management instances on the basis of this model, experiment results show the validity of considering intervening information systems as strategic tools for improving resource allocation in processes and clarifying the meaningfulness of knowledge for the creation of sustainable AI. |
| Author Keywords |
Knowledge Transfer Velocity; Regression Analysis; Experimentation; Process Improvement Techniques; Adaptable Information Systems; Sustainable Artificial Intelligence |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:001292632200002 |
| WoS Category |
Management |
| Research Area |
Business & Economics |
| PDF |
https://www.igi-global.com/ViewTitle.aspx?TitleId=350409&isxn=9798369324608
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