Article

Philosophical approaches to managing generative AI agents as artificial persons at work

Details

Citation

Kane TB (2025) Philosophical approaches to managing generative AI agents as artificial persons at work. Journal of Business Analytics, 8, pp. 250-266. https://doi.org/10.1080/2573234x.2025.2482652

Abstract
The Fourth Industrial Revolution is expected to disrupt economic and social systems nationally, internationally and globally. It is clear that two of the distinguishing disruptors of the Fourth Industrial Revolution have been in business uses of Generative Artificial Intelligence and Cyberphysical Systems across the Internet of Things. This paper offers Business Analysts new analytical tools for guiding business strategy in these times. The contribution of the paper lies in adapting Beer’s Viable System Model for use in the Fourth Industrial Revolution, by inserting into its classic format contributions from three profoundly significant philosophers of society, of being, and of language. Firstly, by presenting any institutional viable systems as intentional artificial persons at work within the bounds of a Hobbesian social contract. Secondly, it demonstrates how the Viable System Model can adopt Heideggerian phenomenology to explore the ontological characteristics of generative AI agents. Finally, Wittgenstein language games are employed to explore the intentional behaviours of artificial persons with respect to their allotted social contract. The tools offered are proposed to aid national governance, business management and to ensure decorous living conditions for natural and artificial persons alike during this exciting new industrial revolution.

Keywords
Word; generative AI; cyberphysical systems; cybernetics; management discourse

Journal
Journal of Business Analytics: Volume 8

StatusPublished
FundersStirling Enterprise Park
Publication date31/03/2025
Publication date online31/03/2025
Date accepted by journal08/03/2025
URLhttp://hdl.handle.net/1893/37455
PublisherInforma UK Limited
ISSN2573-234X
eISSN2573-2358

People (1)

Dr Tom Kane

Dr Tom Kane

Senior Lecturer in Business Analytics, Management, Work and Organisation

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