Since more and more business tasks are enabled by Artificial Intelligence (AI)-based techniques, the number of knowledge-intensive tasks increase as trivial tasks can be automated and non-trivial tasks demand human-machine interactions. With this, challenges regarding the management of knowledge workers and machines rise [9]. Furthermore, knowledge workers experience time pressure, which can lead to a decrease in output quality. Artificial Intelligence-based systems (AIS) have the potential to assist human workers in knowledge-intensive work. By providing a domain-specific language, contextual and situational awareness as well as their process embedding can be specified, which enables the management of human and AIS to ease knowledge transfer in a way that process time, cost and quality are improved significantly. This contribution outlines a framework to designing these systems and accounts for their implementation.
CITATION STYLE
Grum, M., Kotarski, D., Ambros, M., Biru, T., Krallmann, H., & Gronau, N. (2021). Managing Knowledge of Intelligent Systems: The Design of a Chatbot Using Domain-Specific Knowledge. In Lecture Notes in Business Information Processing (Vol. 422 LNBIP, pp. 78–96). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-79976-2_5
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