Artificial intelligence and ethics within the food sector:: developing a common language for technology adoption across the supply chain
Artificial intelligence and ethics within the food sector:: developing a common language for technology adoption across the supply chain
Background: The use of artificial intelligence (AI) is growing in food supply chains. The ethical language associated with food supply and technology is contextualised and framed by the meaning given to it by stakeholders. Failure to differentiate between these nuanced meanings can create a barrier to technology adoption and reduce the benefit derived.
Scope and approach: The aim of this review paper is to consider the embedded ethical language used by stakeholders who collaborate in the adoption of AI in food supply chains. Ethical perspectives frame this literature review and provide structure to consider how to shape a common discourse to build trust in, and frame more considered utilisation of, AI in food supply chains to the benefit of users, and wider society.
Key findings and conclusions: Whilst the nature of data within the food system is much broader than the personal data covered by the European Union General Data Protection Regulation (GDPR), the ethical issues for computational and AI systems are similar and can be considered in terms of particular aspects: transparency, traceability, explainability, interpretability, accessibility, accountability and responsibility. The outputs of this research assist in giving a more rounded understanding of the language used, exploring the ethical interaction of aspects of AI used in food supply chains and also the management activities and actions that can be adopted to improve the applicability of AI technology, increase engagement and derive greater performance benefits. This work has implications for those developing AI governance protocols for the food supply chain as well as supply chain practitioners.
Accessibility, Accountability, Artificial intelligence, Explainability, Interoperability, Responsibility
33-42
Manning, Louise
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Brewer, Steve
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Craigon, Peter
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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
ddc2d702-f1bf-4301-98e7-490ef0cd2008
Pearson, Simon
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1 July 2022
Manning, Louise
79a27caa-92fe-46c4-9c69-71b134a60764
Brewer, Steve
31941fc0-da27-4375-b62f-03a6b2a4bb94
Craigon, Peter
2690596e-30e1-4cf5-b798-9d9abf9e531e
Frey, Jeremy
ba60c559-c4af-44f1-87e6-ce69819bf23f
Gutierrez, Anabel
62705e2a-7501-40bc-a84e-6619e71f2d6b
Jacobs, Naomi
e72a8a32-6a96-495d-832b-79e3e553e166
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Munday, Samuel
d2246425-2b7c-478e-a934-b7e3c6aee384
Sacks, Justin
ddc2d702-f1bf-4301-98e7-490ef0cd2008
Pearson, Simon
4dd66ce4-43df-4077-95ae-6ba202a7861b
Manning, Louise, Brewer, Steve, Craigon, Peter, Frey, Jeremy, Gutierrez, Anabel, Jacobs, Naomi, Kanza, Samantha, Munday, Samuel, Sacks, Justin and Pearson, Simon
(2022)
Artificial intelligence and ethics within the food sector:: developing a common language for technology adoption across the supply chain.
Trends in Food Science & Technology, 125, .
(doi:10.1016/j.tifs.2022.04.025).
Abstract
Background: The use of artificial intelligence (AI) is growing in food supply chains. The ethical language associated with food supply and technology is contextualised and framed by the meaning given to it by stakeholders. Failure to differentiate between these nuanced meanings can create a barrier to technology adoption and reduce the benefit derived.
Scope and approach: The aim of this review paper is to consider the embedded ethical language used by stakeholders who collaborate in the adoption of AI in food supply chains. Ethical perspectives frame this literature review and provide structure to consider how to shape a common discourse to build trust in, and frame more considered utilisation of, AI in food supply chains to the benefit of users, and wider society.
Key findings and conclusions: Whilst the nature of data within the food system is much broader than the personal data covered by the European Union General Data Protection Regulation (GDPR), the ethical issues for computational and AI systems are similar and can be considered in terms of particular aspects: transparency, traceability, explainability, interpretability, accessibility, accountability and responsibility. The outputs of this research assist in giving a more rounded understanding of the language used, exploring the ethical interaction of aspects of AI used in food supply chains and also the management activities and actions that can be adopted to improve the applicability of AI technology, increase engagement and derive greater performance benefits. This work has implications for those developing AI governance protocols for the food supply chain as well as supply chain practitioners.
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Glossary TIFS accepted
- Accepted Manuscript
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More information
Accepted/In Press date: 23 April 2022
e-pub ahead of print date: 30 April 2022
Published date: 1 July 2022
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 ).
Keywords:
Accessibility, Accountability, Artificial intelligence, Explainability, Interoperability, Responsibility
Identifiers
Local EPrints ID: 473946
URI: http://eprints.soton.ac.uk/id/eprint/473946
ISSN: 0924-2244
PURE UUID: 6f9466e8-bf56-452f-a93f-046085547bf7
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Date deposited: 06 Feb 2023 17:36
Last modified: 17 Mar 2024 03:55
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Contributors
Author:
Louise Manning
Author:
Steve Brewer
Author:
Peter Craigon
Author:
Anabel Gutierrez
Author:
Naomi Jacobs
Author:
Samuel Munday
Author:
Justin Sacks
Author:
Simon Pearson
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