Manning, L., Brewer, S., Craigon, P. , Frey, J., Gutierrez, A., Jacobs, N., Kanza, S., Munday, S., Sacks, J. and Pearson, S. (2023) Reflexive governance architectures: considering the ethical implications of autonomous technology adoption in food supply chains. Trends in Food Science & Technology, 133 . pp. 114-126. ISSN 0924-2244
Full content URL: https://doi.org/10.1016/j.tifs.2023.01.015
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Item Type: | Article |
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Item Status: | Live Archive |
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.
Keywords: | data, ethical aspects, ethical outcomes, reflective governance, reflexive governance, AI, food supply |
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Subjects: | G Mathematical and Computer Sciences > G700 Artificial Intelligence G Mathematical and Computer Sciences > G440 Human-computer Interaction G Mathematical and Computer Sciences > G790 Artificial Intelligence not elsewhere classified |
Divisions: | College of Science > Lincoln Institute for Agri-Food Technology |
ID Code: | 53439 |
Deposited On: | 15 Feb 2023 11:42 |
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