Abstract
This paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through a thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this paper aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. It aim is to analyse these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed.
Highlights
Artificial intelligence (AI) is a term that is frequently being used, often with a degree of confusion about what it means
This is important because it helps us to identify if the values that are discussed in AI ethics guidelines are representative of what the agricultural AI literature finds important
This paper aims to illustrate gaps that are not being discussed in the agricultural AI debate, but are elsewhere
Summary
Artificial intelligence (AI) is a term that is frequently being used, often with a degree of confusion about what it means. We are met with visions of Skynet, terminator-style scenarios of when AI goes wrong, or utopian futures where AI takes away all of the dirty, dangerous, and dull jobs that we are faced with. These are the most extreme versions of the tale, with many film-makers, authors, and scientists, providing insights of the in-between, and more likely, nuanced versions of AI—those that provide benefits and raise a number of concerns, challenges, and issues that we must address head-on. The work being conducted in AI ethics is significant, but it is important to evaluate the nuances and challenges that are unique to different domains and sectors
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