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 archi-tectures 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 con-ceptualisation, 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.

Automated summary

This paper criticizes existing reflective food-related ethical assessment tools and proposes the structural elements required for reflexive governance architectures in the application of autonomous technology in food supply chains. The findings suggest that considering the ethical implications in real-life contexts is challenging, and a more holistic approach can inform ethical considerations and the need for mitigation at all lifecycle stages of technology and food product in the supply chain. This research is of interest to those engaged in ethical deliberation on data sharing, AI, and machine learning in food supply chains.