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Research Handbook on Artificial Intelligence and Decision Making in Organizations
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.
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Critical Acclaim
Contributors
Contents
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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.
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.
Critical Acclaim
‘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.’
– Natalia Levina, New York University, US
‘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 Research 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!’
– Omar A. El Sawy, University of Southern California, US
‘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.’
– Robert D. Austin, Ivey Business School, Western University, Canada
‘This timely Research 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.’
– Paolo Quattrone, University of Manchester, UK
– Natalia Levina, New York University, US
‘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 Research 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!’
– Omar A. El Sawy, University of Southern California, US
‘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.’
– Robert D. Austin, Ivey Business School, Western University, Canada
‘This timely Research 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.’
– Paolo Quattrone, University of Manchester, UK
Contributors
Contributors include: Margunn Aanestad, Angela Aristidou, Benedikt Berger, Jonna Bornemark, Adrian Bumann, Panos Constantinides, Ioanna Constantiou, Antonio Cordella, Camille G. Endacott, Robert D. Galliers, Francesco Gualdi, Gunnar Holmberg, Jonny Holmström, Marleen Huysman, Lena Hylving, Sirkka L. Jarvenpaa, Mayur P. Joshi, Stefan Klein, Dina Koutsikouri, Angelos Kostis, Nicolette Lakemond, Paul M. Leonardi, Susanne Lindberg, Jingyao (Lydia) Li, Yulia Litvinova, Marco Marabelli, Attila Márton, Anne-Sophie Mayer, Nikolay Mehandjiev, Patrick Mikalef, Miriam Möllers, Alex Murray, Sue Newell, Stella Pachidi, Ilias Pappas, Elena Parmiggiani, Jen Rhymer, Andrew Sarta, Arisa Shollo, David Sirmon, Marta Stelmaszak, Franz Strich, Leif Sundberg, Mike H.M. Teodorescu, Bijona Troqe, Polyxeni Vassilakopoulou, Lauren Waardenburg, Tiantian Xian
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
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
