Design principles for artificial intelligence-augmented decision making: An action design research study

Herath Pathirannehelage, S., Shrestha, Y. R., von Krogh, G. (2024). Design principles for artificial intelligence-augmented decision making: An action design research study. European Journal of Information Systems, https://doi.org/10.1080/0960085X.2024.2330402

24 Pages Posted: 13 Apr 2022 Last revised: 26 Mar 2024

See all articles by Savindu Herath Pathirannehelage

Savindu Herath Pathirannehelage

ETH Zurich

Yash Raj Shrestha

University of Lausanne - Faculty of Business and Economics (HEC Lausanne)

Georg von Krogh

ETH Zurich

Date Written: March 31, 2022

Abstract

Artificial intelligence (AI) applications have proliferated, garnering significant interest among information systems (IS) scholars. AI-powered analytics, promising effective and low-cost decision augmentation, has become a ubiquitous aspect of contemporary organisations. Unlike traditional decision support systems (DSS) designed to support decisionmakers with fixed decision rules and models that often generate stable outcomes and rely on human agentic primacy, AI systems learn, adapt, and act autonomously, demanding recognition of IS agency within AI-augmented decision making (AIADM) systems. Given this fundamental shift in DSS; its influence on autonomy, responsibility, and accountability in decision making within organisations; the increasing regulatory and ethical concerns about AI use; and the corresponding risks of stochastic outputs, the extrapolation of prescriptive design knowledge from conventional DSS to AIADM is problematic. Hence, novel design principles incorporating contextual idiosyncrasies and practice-based domain knowledge are needed to overcome unprecedented challenges when adopting AIADM. To this end, we conduct an action design research (ADR) study within an e-commerce company specialising in producing and selling clothing. We develop an AIADM system to support marketing, consumer engagement, and product design decisions. Our work contributes to theory and practice with a set of actionable design principles to guide AIADM system design and deployment.

Keywords: AI-augmented decision making, artificial intelligence, decision support systems, design principles, action design research

Suggested Citation

Herath Pathirannehelage, Savindu and Shrestha, Yash Raj and von Krogh, Georg, Design principles for artificial intelligence-augmented decision making: An action design research study (March 31, 2022). Herath Pathirannehelage, S., Shrestha, Y. R., von Krogh, G. (2024). Design principles for artificial intelligence-augmented decision making: An action design research study. European Journal of Information Systems, https://doi.org/10.1080/0960085X.2024.2330402, Available at SSRN: https://ssrn.com/abstract=4071519 or http://dx.doi.org/10.2139/ssrn.4071519

Savindu Herath Pathirannehelage (Contact Author)

ETH Zurich ( email )

WEV
Weinbergstrasse 56/58
Zurich, Zürich 8092
Switzerland

Yash Raj Shrestha

University of Lausanne - Faculty of Business and Economics (HEC Lausanne) ( email )

Switzerland

Georg Von Krogh

ETH Zurich ( email )

D-MTEC, SMI, WEV J 411
Weinbergstrasse 56/58
Zurich, 8092
Switzerland
+41 44 632 88 50 (Phone)

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