Artificial intelligence and ethics within the food sector: Developing a common language for technology adoption across the supply chain. (July 2022)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence and ethics within the food sector: Developing a common language for technology adoption across the supply chain. (July 2022)
- Main Title:
- Artificial intelligence and ethics within the food sector: Developing a common language for technology adoption across the supply chain
- Authors:
- Manning, Louise
Brewer, Steve
Craigon, Peter J.
Frey, Jeremy
Gutierrez, Anabel
Jacobs, Naomi
Kanza, Samantha
Munday, Samuel
Sacks, Justin
Pearson, Simon - Abstract:
- 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,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. Highlights: AI applications are increasingly being adopted in food supply chains. AI empowers decision-making, but its use must be framed by ethical considerations. Benefits/risks of using AI are constantly evaluated in the AI development cycle. Improving explainability, interpretability and accessibility enables transparency. Responsibility and accountability relate to governance structures for use of AI. … (more)
- Is Part Of:
- Trends in food science & technology. Volume 125(2022)
- Journal:
- Trends in food science & technology
- Issue:
- Volume 125(2022)
- Issue Display:
- Volume 125, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 125
- Issue:
- 2022
- Issue Sort Value:
- 2022-0125-2022-0000
- Page Start:
- 33
- Page End:
- 42
- Publication Date:
- 2022-07
- Subjects:
- Responsibility -- Accessibility -- Explainability -- Accountability -- Interoperability -- Artificial intelligence
Food industry and trade -- Periodicals
Food -- Biotechnology -- Periodicals
664.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09242244 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tifs.2022.04.025 ↗
- Languages:
- English
- ISSNs:
- 0924-2244
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9049.593000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 21752.xml