Elgendy, N. (2022). Enhancing collaborative rationality between humans and machines through data-driven decision evaluation. In H. Koç, J. Stirna, K. Sandkuhl, U. Seigerroth, M. Kirikova, P. Forbrig, C. Møller, A. Gutschmidt, & B. Johansson (Eds.), BIR 2022 Workshops and Doctoral Consortium: Joint Proceedings of the BIR 2022 Workshops and Doctoral Consortium co-located with 21st International Conference on Perspectives in Business Informatics Research (BIR 2022), Rostock, Germany, September 20-23, 2022 (pp. 177-188). RWTH Aachen University.
Enhancing collaborative rationality between humans and machines through data-driven decision evaluation
|Online Access:||PDF Full Text (PDF, 0.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022100761306
RWTH Aachen University,
|Publish Date:|| 2022-10-07
Organizational decisions have become more data-driven and collaborative, with the increasing utilization of artificial intelligence, machine learning, and analytics to support decision making. While humans and machines are each bounded in their own rationalities, their collaboration has enabled a new, collaborative rationality by augmenting the intelligence and capabilities of each. New research is required to explore the degree and mode of human-machine collaboration, with the aim of enhancing collaborative rationality, and its effect on decision making. Furthermore, the resulting decisions must be evaluated to enable learning, rationalization, and sensemaking from the decision outcomes. However, data-driven decisions are complex in nature, and current theoretical developments fall short in accommodating for their multi-faceted nature and changing context, and there is lack of theoretical support on how, when, and why to evaluate such decisions. Accordingly, we follow a design science research methodology to develop and evaluate a model for data-driven decision evaluation. This model depicts the relationship and role of the multiple elements involved in data-driven decision making, and provides a feedback loop which inputs the results of evaluating decision outcomes back into the process/system, thus enabling learning from the past through experience, and ultimately enhancing collaborative rationality and decision making.
CEUR workshop proceedings
|Pages:||177 - 188|
BIR 2022 Workshops and Doctoral Consortium : joint proceedings of the BIR 2022 Workshops and Doctoral Consortium co-located with 21st International Conference on Perspectives in Business Informatics Research (BIR 2022) Rostock, Germany, September 20-23, 2022
|Host publication editor:||
BIR Workshops and Doctoral Consortium
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
I would also like to acknowledge the ITEA3 project Oxilate (https://itea3.org/project/oxilate.html), and the organizations and experts who have willingly collaborated in this research.
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