Reflexive governance architectures: Considering the ethical implications of autonomous technology adoption in food supply chains
Reflexive governance architectures: Considering the ethical implications of autonomous technology adoption in food supply chains
Background: The application of autonomous technology in food supply chains gives rise to a number of ethical considerations associated with the interaction between human and technology, human-technology-plant and human-technology-animal. These considerations and their implications influence technology design, the ways in which technology is applied, how the technology changes food supply chain practices, decision-making and the associated ethical aspects and outcomes. Scope and approach: Using the concept of reflexive governance, this paper has critiqued existing reflective food-related ethical assessment tools and proposed the structural elements required for reflexive governance architectures which address both the sharing of data, and the use of artificial intelligence (AI) and machine learning in food supply chains. Key findings and conclusions: Considering the ethical implications of using autonomous technology in real life contexts is challenging. The current approach, focusing on discrete ethical elements in isolation e.g., ethical aspects or outcomes, normative standards or ethically orientated compliance-based business strategies, is not sufficient in itself. Alternatively, the application of more holistic, reflexive governance architectures can inform consideration of ethical aspects, potential ethical outcomes, in particular how they are interlinked and/or interdependent, and the need for mitigation at all lifecycle stages of technology and food product conceptualisation, design, realisation and adoption in the food supply chain. This research is of interest to those who are undertaking ethical deliberation on data sharing, and the use of AI and machine learning in food supply chains.
AI, Data, Ethical aspects, Ethical outcomes, Food supply, Reflective governance, Reflexive governance
114-126
Manning, Louise
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Brewer, Steve
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Craigon, Peter J.
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Frey, Jeremy
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Gutierrez, Anabel
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Jacobs, Naomi
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Kanza, Samantha
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Munday, Samuel
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Sacks, Justin
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Pearson, Simon
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1 March 2023
Manning, Louise
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Brewer, Steve
31941fc0-da27-4375-b62f-03a6b2a4bb94
Craigon, Peter J.
2690596e-30e1-4cf5-b798-9d9abf9e531e
Frey, Jeremy
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Gutierrez, Anabel
62705e2a-7501-40bc-a84e-6619e71f2d6b
Jacobs, Naomi
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Kanza, Samantha
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Munday, Samuel
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Sacks, Justin
ddc2d702-f1bf-4301-98e7-490ef0cd2008
Pearson, Simon
4dd66ce4-43df-4077-95ae-6ba202a7861b
Manning, Louise, Brewer, Steve, Craigon, Peter J., Frey, Jeremy, Gutierrez, Anabel, Jacobs, Naomi, Kanza, Samantha, Munday, Samuel, Sacks, Justin and Pearson, Simon
(2023)
Reflexive governance architectures: Considering the ethical implications of autonomous technology adoption in food supply chains.
Trends in Food Science & Technology, 133, .
(doi:10.1016/j.tifs.2023.01.015).
Abstract
Background: The application of autonomous technology in food supply chains gives rise to a number of ethical considerations associated with the interaction between human and technology, human-technology-plant and human-technology-animal. These considerations and their implications influence technology design, the ways in which technology is applied, how the technology changes food supply chain practices, decision-making and the associated ethical aspects and outcomes. Scope and approach: Using the concept of reflexive governance, this paper has critiqued existing reflective food-related ethical assessment tools and proposed the structural elements required for reflexive governance architectures which address both the sharing of data, and the use of artificial intelligence (AI) and machine learning in food supply chains. Key findings and conclusions: Considering the ethical implications of using autonomous technology in real life contexts is challenging. The current approach, focusing on discrete ethical elements in isolation e.g., ethical aspects or outcomes, normative standards or ethically orientated compliance-based business strategies, is not sufficient in itself. Alternatively, the application of more holistic, reflexive governance architectures can inform consideration of ethical aspects, potential ethical outcomes, in particular how they are interlinked and/or interdependent, and the need for mitigation at all lifecycle stages of technology and food product conceptualisation, design, realisation and adoption in the food supply chain. This research is of interest to those who are undertaking ethical deliberation on data sharing, and the use of AI and machine learning in food supply chains.
Text
TIFS Reflexive accepted
- Accepted Manuscript
More information
Accepted/In Press date: 22 January 2023
e-pub ahead of print date: 29 January 2023
Published date: 1 March 2023
Additional Information:
Funding Information:
This research augments the Food Standards Agency (FSA) funded work led by the University of Lincoln to create a Data Trust Framework related to food safety (Brewer et al. 2021). The working group that contributed to this paper is joint funded by the Internet of Food Things Network+ (Grant Number: EP/R045127/1) and the Artificial Intelligence and Augmented Intelligence for Automated Investigation for Scientific Discovery Network+ (AI3SD) (Grant Number: EP/S000356/1).
Funding Information:
This research augments the Food Standards Agency (FSA) funded work led by the University of Lincoln to create a Data Trust Framework related to food safety ( Brewer et al., 2021 ). The working group that contributed to this paper is joint funded by the Internet of Food Things Network + (Grant Number: EP/R045127/1 ) and the Artificial Intelligence and Augmented Intelligence for Automated Investigation for Scientific Discovery Network + (AI3SD) (Grant Number: EP/S000356/1 ).
Publisher Copyright:
© 2023 The Authors
Keywords:
AI, Data, Ethical aspects, Ethical outcomes, Food supply, Reflective governance, Reflexive governance
Identifiers
Local EPrints ID: 478930
URI: http://eprints.soton.ac.uk/id/eprint/478930
ISSN: 0924-2244
PURE UUID: b44b59c2-9285-4f37-830a-2301380ddd78
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Date deposited: 14 Jul 2023 16:43
Last modified: 17 Mar 2024 03:55
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Contributors
Author:
Louise Manning
Author:
Steve Brewer
Author:
Peter J. Craigon
Author:
Anabel Gutierrez
Author:
Naomi Jacobs
Author:
Samuel Munday
Author:
Justin Sacks
Author:
Simon Pearson
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