Research Handbook on Artificial Intelligence and Decision Making in Organizations: (Research Handbooks in Business and Management series)

About the Book

Featuring state-of-the-art research from leading academics in technology and organization studies, this timely Research Handbook provides a comprehensive overview of how AI becomes embedded in decision making in organizations, from the initial considerations when implementing AI to the use of such solutions in strategic decision making.

Bringing together cutting-edge scholarship on the many issues and complexities surrounding the use of AI in decision making for organizations, this enlightening Research Handbook illustrates how technology is intertwined with organizational processes and outcomes. Contributors examine human-AI collaboration in welfare services, responsible AI governance, AI systems in medical imaging, and the ethical implications of AI use in practice. Furthermore, the editors propose an integrative framework for decision making in organizations that encompasses making decisions about AI, with AI, and the implications of decisions made by AI.

The Research Handbook will be essential reading for students, academics and researchers in business analytics, information systems, organizational innovation, organizational behavior, and organizational and occupational psychology. It will also be a valuable resource for business managers and AI engineers.

Table of Contents:
Contents: Introduction to Artificial Intelligence and Decision Making in Organizations 1 Ioanna Constantiou, Mayur P. Joshi and Marta Stelmaszak PART I MAKING DECISIONS ABOUT AI 1 Sourcing data for data-driven applications: foundational questions 17 Sirkka L. Jarvenpaa 2 Data work as an organizing principle in developing AI 38 Angelos Kostis, Leif Sundberg, and Jonny Holmström 3 Natural language processing techniques in management research 58 Mike H.M. Teodorescu 4 Captains don’t navigate with a keyboard: developing AI for naturalistic decision-making 79 Adrian Bumann 5 Reconfiguring human‒AI collaboration: integrating chatbots in welfare services 96 Elena Parmiggiani, Polyxeni Vassilakopoulou, and Ilias Pappas 6 Circumspection as a process of responsible appropriation of AI 111 Margunn Aanestad 7 Responsible AI governance: from ideation to implementation 125 Patrick Mikalef PART II MAKING DECISIONS WITH AI 8 Human judgment in the age of automated decision-making systems 143 Dina Koutsikouri, Lena Hylving, Jonna Bornemark, and Susanne Lindberg 9 Making decisions with AI in complex intelligent systems 159 Bijona Troqe, Gunnar Holmberg, and Nicolette Lakemond 10 Addressing the knowledge gap between business managers and data scientists: the case of data analytics implementation in a sales organization 178 Stella Pachidi and Marleen Huysman 11 Constructing actionable insights: the missing link between data, artificial intelligence, and organizational decision-making 194 Arisa Shollo and Robert D. Galliers 12 It takes a village: the ecology of explaining AI 213 Lauren Waardenburg and Attila Márton 13 Synthetic stakeholders: engaging the environment in organizational decision-making 225 Jen Rhymer, Alex Murray, and David Sirmon 14 Interpretable artificial intelligence systems in medical imaging: review and theoretical framework 239 Tiantian Xian, Panos Constantinides, and Nikolay Mehandjiev 15 Artificial intelligence to support public sector decision-making: the emergence of entangled accountability 265 Francesco Gualdi and Antonio Cordella 16 Contrasting human‒AI workplace relationship configurations 281 Miriam Möllers, Benedikt Berger, and Stefan Klein PART III IMPLICATIONS OF DECISIONS MADE WITH AI 17 Who am I in the age of AI? Exploring dimensions that shape occupational identity in the context of AI for decision-making 304 Anne-Sophie Mayer and Franz Strich 18 Imagination or validation? Using futuring techniques to enhance AI’s relevance in strategic decision-making 321 Andrew Sarta and Angela Aristidou 19 Artificial intelligence as a mechanism of algorithmic isomorphism 341 Camille G. Endacott and Paul M. Leonardi 20 Ethical implications of AI use in practice for decision-making 358 Jingyao (Lydia) Li, Yulia Litvinova, Marco Marabelli, and Sue Newell

About the Author :
Edited by Ioanna Constantiou, Full Professor, Department of Digitalization, Copenhagen Business School, Denmark, Mayur P. Joshi, Assistant Professor of Information Systems, Telfer School of Management, University of Ottawa, Canada and Marta Stelmaszak, Assistant Professor of Information Systems, Isenberg School of Management, University of Massachusetts Amherst, US

Review :
‘In this extremely timely and very well-researched volume, Constantiou, Joshi, and Stelmaszak have assembled a distinguished group of scholars to explore how AI is shaped by and shapes organizational decisions, and with what consequences. A must read for scholars of modern technology in organizations.’ ‘I think this research handbook is very timely and the editors have put together an elite set of contributing authors which reads like a who’s who list and who provide very informative and carefully crafted chapters on various facets of AI and decision making. They deal with the relationship between AI and organizational decision making in a very grounded non-hyped way. They draw on the information systems discipline but maintain a socio-technical perspective as the backbone of the handbook. It is an excellent reference compendium for scholars, but also provides useful connections for practice. I find to be “spot-on” the guiding integrative framework used in the book to connect AI and organizational decision making through what the editors have called “decision redistribution.” The emphasis on the notion that AI and human decision-makers are not viewed as conflicting, but rather considered holistically in relation to each other is something we really need to internalize wisely as we go forward into the AI future. And this research handbook is showing us the way!’ ‘The recent dawning of a new AI era raises many management questions. There is much work to do to answer these questions, and this book offers vital early thinking that can help researchers and managers move toward a better understanding of AI and the challenges it presents.’ ‘This timely Handbook is a compelling call for rethinking the meaning of rationality in decision-making in the era of AI. A must have if one wants to navigate the unchartered waters of AI and decision-making in the years to come.’