To read this content please select one of the options below:

Sustainably Developing in a Digital World: harnessing artificial intelligence to meet the imperatives of work-based learning in Industry 5.0

Muneer Al Mubarak (Ahlia University, Manama, Bahrain)

Development and Learning in Organizations

ISSN: 1477-7282

Article publication date: 28 June 2022

Issue publication date: 20 April 2023

642

Abstract

Purpose:

Mainly in terms of human-machine interactions, this paper discusses salient issues related to work-based learning in reference to technologies in the Industry 5.0 era.

Design/methodology/approach:

Several ideas are discussed based on recent thinking in the topic, putting forward visions that are likely to happen with Industry 5.0 revolution with prime focus on human-machine interactions.

Findings:

The review elucidated a plethora of benefits in terms of human-machine interactions inasmuch as technology complements rather than replaces human efforts that includes enhancement of: efficiency and production, job security and skill-upgrading. To engender these benefits, however, legal, psychological, and ethical issues need to be transcended on the managerial level.

Practical implications:

Positive externalities, associated with efficiency and production, are now possible with human-machine interactions without cost in terms of jobs being lost provided that skills are upgraded commensurate with the challenges posed by the new technological era.

Social implications:

People can benefit from life improvements and elevated standards of living stemming from robotics though optimization of the use of technology.

Originality:

This paper presents original ideas on how Industry 5.0 technologies can be harnessed to buoy sustainable development by striking an optimal balance between human and technological capital.

Keywords

Citation

Al Mubarak, M. (2023), "Sustainably Developing in a Digital World: harnessing artificial intelligence to meet the imperatives of work-based learning in Industry 5.0", Development and Learning in Organizations, Vol. 37 No. 3, pp. 18-20. https://doi.org/10.1108/DLO-04-2022-0063

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles