Decision-making with artificial intelligence : Towards a novel conceptualization of patterns

Title data

Leyer, Michael ; Oberländer, Anna Maria ; Dootson, Paula ; Kowalkiewicz, Marek:
Decision-making with artificial intelligence : Towards a novel conceptualization of patterns.
In: Proceedings of the 23th Pacific Asia Conference on Information Systems (PACIS). - Dubai, United Arab Emirates , 2020

Official URL:

Abstract in another language

The rapidly increasing amount of data available in society and business drives the development of Artificial Intelligence (AI). As the number of AI-based services is increasing, customers delegate intimate and relevant decisions to AI. However, current literature lacks understanding of what patterns of decision-making processes with AI involved exist, and it remains unclear how to structure and classify AI-based services accordingly. Therefore, we present and evaluate a set of seven patterns of decision-making processes with AI involved. Building on decision-making theory as justificatory knowledge, we focus on the business-to-customer context to provide a novel perspective on the interactions of customers with AI. We apply the patterns to real-world examples of companies offering AI-based services. Our work contributes to the descriptive knowledge of AI and decision-making theory providing a foundation for future research and supporting practitioners in designing AI-based services.

Further data

Item Type:	Article in a book
Refereed:	Yes
Keywords:	Artificial Intelligence; AI; Decision-making; Patterns
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Business Administration Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management Faculties Faculties > Faculty of Law, Business and Economics
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Date Deposited:	06 Jul 2020 07:37
Last Modified:	04 Aug 2022 05:59
URI:	https://eref.uni-bayreuth.de/id/eprint/55695