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Rise of the machines: a critical consideration of automated leadership decision making in organizations

Parry, Kenneth, Cohen, Michael and Bhattacharya, Sukanto 2016, Rise of the machines: a critical consideration of automated leadership decision making in organizations, Group & organization management, vol. 41, no. 5, pp. 571-594, doi: 10.1177/1059601116643442.

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Title Rise of the machines: a critical consideration of automated leadership decision making in organizations
Author(s) Parry, KennethORCID iD for Parry, Kenneth orcid.org/0000-0002-4175-0583
Cohen, MichaelORCID iD for Cohen, Michael orcid.org/0000-0001-6587-2879
Bhattacharya, SukantoORCID iD for Bhattacharya, Sukanto orcid.org/0000-0001-6587-2879
Journal name Group & organization management
Volume number 41
Issue number 5
Start page 571
End page 594
Total pages 24
Publisher Sage
Place of publication London, Eng.
Publication date 2016
Keyword(s) Social Sciences
Psychology, Applied
Management
Psychology
Business & Economics
decision making
organizational leadership
artificial intelligence
SHARED LEADERSHIP
INTELLIGENCE
COEVOLUTION
SYSTEMS
DESIGN
Summary Machines are increasingly becoming a substitute for human skills and intelligence in a number of fields where decisions that are crucial to group performance have to be taken under stringent constraints—for example, when an army contingent has to devise battlefield tactics or when a medical team has to diagnose and treat a life-threatening condition or illness. We hypothesize a scenario where similar machine-based intelligent technology is available to support, and even substitute human decision making in an organizational leadership context. We do not engage in any metaphysical debate on the plausibility of such a scenario. Rather, we contend that given what we observe in several other fields of human decision making, such a scenario may very well eventuate in the near future. We argue a number of “positives” that can be expected to emerge out of automated group and organizational leadership decision making. We also posit several anti-theses—“negatives” that can also potentially emerge from the hypothesized scenario and critically consider their implications. We aim to bring leadership and organization theorists, as well as researchers in machine intelligence, together at the discussion table for the first time and postulate that while leadership decision making in a group/organizational context could be effectively delegated to an artificial-intelligence (AI)-based decision system, this would need to be subject to the devising of crucial safeguarding conditions.
Language eng
DOI 10.1177/1059601116643442
Field of Research 150399 Business and Management not elsewhere classified
1503 Business And Management
1701 Psychology
Socio Economic Objective 970115 Expanding Knowledge in Commerce
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, The Author(s)
Persistent URL http://hdl.handle.net/10536/DRO/DU:30083799

Document type: Journal Article
Collection: Department of Management
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