Paper short abstract:

The paper takes a multifaceted approach to addressing food insecurity, stressing local engagement and collaboration. It calls for AI solutions that are inclusive, culturally relevant, and supportive of community resilience.

Paper long abstract:

The discourse surrounding Artificial Intelligence (AI) 's role in transforming future food systems encompasses a broad spectrum of topics. These include the application of AI in food production, distribution, and consumption to mitigate food insecurity, as well as broader considerations regarding the potential disruption of existing local food systems by AI. There is a discernible consensus divide between those who advocate for detailed deliberation and those who emphasize the broader implications of AI on future food systems. While some stakeholders underscore the necessity of thorough discussions and meticulous planning, others are more concerned with the potential consequences and disruptions AI might introduce to existing food systems. This dichotomy underscores the need for a balanced perspective integrating detailed analysis with a comprehensive understanding of AI's impact on food systems.

This paper adopts a multifaceted approach to address the complex issue of food insecurity, emphasizing the importance of local engagement and collaboration, highlighting the necessity for AI solutions that are inclusive, culturally relevant, and supportive of community resilience. It underlines the importance of synthesizing existing evidence to understand how to foster collective environments that cultivate trust-building behaviors and attitudes. Additionally, the paper proposes a forward-looking research agenda to develop these collective settings further and enhance our understanding of the underlying dynamics. Investing in these areas can create more resilient and trustworthy food systems that effectively address food insecurity.