Process industry disrupted: AI and the need for human orchestration

According to EU policy makers, the introduction of AI within Process Industry will help big manufacturing companies to become more sustainable. At the same time, concerns arise about future work in these industries. As the EU also wants to actively pursue human-centered AI, this raises the question...

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Main Authors: M.W. Vegter, V. Blok, R. Wesselink
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Journal of Responsible Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666659625000010
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author M.W. Vegter
V. Blok
R. Wesselink
author_facet M.W. Vegter
V. Blok
R. Wesselink
author_sort M.W. Vegter
collection DOAJ
description According to EU policy makers, the introduction of AI within Process Industry will help big manufacturing companies to become more sustainable. At the same time, concerns arise about future work in these industries. As the EU also wants to actively pursue human-centered AI, this raises the question how to implement AI within Process Industry in a way that is sustainable and takes views and interests of workers in this sector into account. To provide an answer, we conducted ‘ethics parallel research’ which involves empirical research. We conducted an ethnographic study of AI development within process industry and specifically looked into the innovation process in two manufacturing plants. We showed subtle but important differences that come with the respective job related duties. While engineers continuously alter the plant as being a technical system; operators hold a rather symbiotic relationship with the production process on site. Building on the framework of different mechanisms of techno-moral change we highlight three ways in which workers might be morally impacted by AI. 1. Decisional - alongside the developmental of data analytic tools respective roles and duties are being decided; 2. Relational - Data analytic tools might exacerbate a power imbalance where engineers may re-script the work of operators; 3. Perceptual - Data analytic technologies mediate perceptions thus changing the relationship operators have to the production process. While in Industry 4.0 the problem is framed in terms of ‘suboptimal use’, in Industry 5.0 the problem should be thought of as ‘suboptimal development’.
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spelling doaj-art-813d9d997ca64699ba84ef2ec5f5d4c02025-02-09T05:01:32ZengElsevierJournal of Responsible Technology2666-65962025-03-0121100105Process industry disrupted: AI and the need for human orchestrationM.W. Vegter0V. Blok1R. Wesselink2Ethics Group, IQ healthcare, Radboud University Medical Center, 6500 HB, Nijmegen, the Netherlands; Corresponding author.Philosophy Group, School of Social Sciences, Wageningen University, Hollandseweg 1, 6707 KN, Wageningen, the NetherlandsEducation and Competence Studies, School of Social Sciences, Wageningen University Hollandseweg 1, 6707 KN, Wageningen, the NetherlandsAccording to EU policy makers, the introduction of AI within Process Industry will help big manufacturing companies to become more sustainable. At the same time, concerns arise about future work in these industries. As the EU also wants to actively pursue human-centered AI, this raises the question how to implement AI within Process Industry in a way that is sustainable and takes views and interests of workers in this sector into account. To provide an answer, we conducted ‘ethics parallel research’ which involves empirical research. We conducted an ethnographic study of AI development within process industry and specifically looked into the innovation process in two manufacturing plants. We showed subtle but important differences that come with the respective job related duties. While engineers continuously alter the plant as being a technical system; operators hold a rather symbiotic relationship with the production process on site. Building on the framework of different mechanisms of techno-moral change we highlight three ways in which workers might be morally impacted by AI. 1. Decisional - alongside the developmental of data analytic tools respective roles and duties are being decided; 2. Relational - Data analytic tools might exacerbate a power imbalance where engineers may re-script the work of operators; 3. Perceptual - Data analytic technologies mediate perceptions thus changing the relationship operators have to the production process. While in Industry 4.0 the problem is framed in terms of ‘suboptimal use’, in Industry 5.0 the problem should be thought of as ‘suboptimal development’.http://www.sciencedirect.com/science/article/pii/S2666659625000010AIEthics of technologyMeaningful workProcess industryEUSustainability
spellingShingle M.W. Vegter
V. Blok
R. Wesselink
Process industry disrupted: AI and the need for human orchestration
Journal of Responsible Technology
AI
Ethics of technology
Meaningful work
Process industry
EU
Sustainability
title Process industry disrupted: AI and the need for human orchestration
title_full Process industry disrupted: AI and the need for human orchestration
title_fullStr Process industry disrupted: AI and the need for human orchestration
title_full_unstemmed Process industry disrupted: AI and the need for human orchestration
title_short Process industry disrupted: AI and the need for human orchestration
title_sort process industry disrupted ai and the need for human orchestration
topic AI
Ethics of technology
Meaningful work
Process industry
EU
Sustainability
url http://www.sciencedirect.com/science/article/pii/S2666659625000010
work_keys_str_mv AT mwvegter processindustrydisruptedaiandtheneedforhumanorchestration
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