AI and Decision-Making

This initiative is about the key to understanding the real impact of AI lies in studying the role of organizations in decision-making and software systems. By focusing on this overlooked middle layer, it offers a fresh perspective on how AI is actually being used in practice.

The last few years have witnessed a renewed enthusiasm for AI, accompanied by strong criticisms of these technologies. On the one hand, the enthusiasm is motivated by the hope that AI could result in data-driven decisions to make organizations and society more efficient and better. On the other hand, critics point to the asymmetry between individuals whose data are being collected and large digital companies who manipulate them. We argue, however, that both views seem to assume an instrumental rationality, or a straightforward relation in between the design of AI and its algorithm and its effects. Yet, at the moment, the AI revolution does not seem to be able to hold its promises. People have not turned into manipulated puppets of large digital companies just yet. However, it would be equally foolish to deny that AI has changed processes of decision-making. We suggest that the decisive middle level which is rarely studied by proponents and critics alike is the organization. Organizations are sites for decision-making, produce quantification, and often operate an entire ecology of software systems. Any systematic use of AI will be filtered through practices of organizing. Focusing on this layer is the central academic target of this strategic initiative.

For inquires about AID or in case you want to join us or one of our activities, please contact Christian Huber (chu.om@cbs.dk).

Approaches and Goals

We take a perspective from interpretative accounting research, critical management studies, and the sociology of quantification to investigate the relation between AI and decision-making. This initiative aims at relating the specificities of contemporary AI quantifications – which can be equated to machine learning, a set of quantification algorithms that produce predictive scores on some future possibilities. The initiative aims at understanding how AI quantification influence managerial decisions modify organizational structures. 

Research Themes

We divide our work in three related sub questions:

(1) How are the data collected and processed in relation to their subsequent use? What type of representation of the quantified entities do they offer?

(2) How are these quantifications made sense of in practice? How are they handled, and what beliefs do different actors invest in them in practice? How does the practice impact back the quantifications?

(3) What is the relation in between the hopes that led to the adoption of such local decision-systems based on quantifications and the modifications that organizational actors perceive?

Key Activities

Selected Publications

Anatoli Bourmistrov; Jan Mouritsen / Guest Editorial : Accounting for Sustainable and Smart Cities. In: Journal of Public Budgeting, Accounting & Financial Management, Vol. 34, No. 5, 2022, 6 p., p. 577-582

Aziza Laguecir; Bernard Leca; Élise Berlinski / Souveraineté et évaluation académique : Une histoire de virgule en sciences de gestion. In: Revue Francaise de Gestion, Vol. 48, No. 305, 2022, p. 103-117

Dane Pflueger; Martin Kornberger; Jan Mouritsen / What is Blockchain Accounting? : A Critical Examination in Relation to Organizing, Governance, and Trust. In: European Accounting Review, 15.12.2022

Élise Berlinski / Debate: The Multiple Paradoxes of Meta and Mark Zuckerberg Paris : The Conversation Media Group 1.3.2023 Net publication - Internet publication

Elise Berlinski; Marianne Strauch; Quentin Plantec / Hyperloop, une mythologie de marchés In: Revue Francaise de Gestion, Vol. 48, No. 304, 5.2022, p. 65-88

Élise Berlinski / The Multiple Paradoxes of Meta and Mark Zuckerberg In: Irish Examiner, 15.3.2023 Contribution to newspaper - Comment/debate

Huber, C. & Scheytt, T. (2018). Pitfalls of algorithmic control and their implications for support systems: Algorithmic control as a threat to accountability. In: Weidner, R. & Karafillidis, A. (eds.) Konferenzband (Proceedings) zur Dritten Transdisziplinären Konferenz Technische Unterstützungssysteme, die die Menschen wirklich wollen, Hamburg, 205-212. 

Participants

The Accounting, Organizations and Decision-Making initiative is driven by a team of experienced professors. 

The team includes: 

Christian Huber, Associate Professor (Principal Organizer) - Department of Operations Management 

Elise Berlinski, Assistant Professor - Department of Operations Management 

Jan Mouritsen, Professor - Department of Operation Management 

 

The page was last edited by: Department of Operations Management // 05/25/2023