Nutritional intelligence in the food system: Combining food, health, data and AI expertise

Transformative change is needed across the food system to improve health and environmental outcomes. As food, nutrition, environmental and health data are generated beyond human scale, there is an opportunity for technological tools to support multifactorial, integrated, scalable approaches to address the complexities of dietary behaviour change. Responsible technology could act as a mechanistic conduit between research, policy, industry and society, enabling timely, informed decision making and action by all stakeholders across the food system. Domain expertise in food, nutrition and health should always be integrated into both the development and continuous deployment of AI-powered nutritional intelligence (NI) to ensure it is responsible, accurate, safe, useable and effective. Dietary behaviours are complex and improving diet-related health outcomes requires socio-cultural-demographic considerations within the design and deployment of NI tools. This article describes existing examples of NI within the food system and future opportunities. Human-in-the-loop approaches with food, health and nutrition experts involved at all stages including data acquisition, processing, output validation and ongoing quality assurance are essential to ensure evidence-based practice. The same ethical considerations should apply in this domain as in any other (e.g. privacy, inclusivity, robustness, transparency and accountability) and responsible practice must encompass rigorous standards and alignment with regulatory frameworks. Critical today and in the future is accessibility to appropriate high-quality food compositional data sets, which include up-to-date information on commercially available products that reflect the constantly evolving food landscape to realise the potential of responsible AI to help address the existing food system challenges.