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Book (stand-alone)Technical bookArtificial intelligence for food safety
A literature synthesis, real-world applications and regulatory frameworks
2025Also available in:
No results found.Artificial Intelligence (AI) is increasingly applied in food safety management, offering new capabilities in data analysis, predictive modelling, and risk-based decision-making. A review of the literature identifies three primary areas of application: scientific advice, inspection and border control, and operational activities of food safety competent authorities. Five country examples with the real-world use cases illustrate diverse uses of AI tools, including pathogen detection, import sampling prioritization, and language models for regulatory data processing. Regulatory frameworks, as well as voluntary governance, addressing AI in the public sector are emerging worldwide. National and international initiatives often highlight the importance of data governance, transparency, ethical considerations, and human oversight. Challenges such as biased data, explainability, and data governance gaps appear across different contexts, along with potential risks from deploying AI systems prematurely. Access to high-quality, interoperable data and collaboration among stakeholders can support effective integration of AI technologies. AI readiness often depends on understanding specific problems to be addressed, current capacities, and the quality of available data. Human oversight and continuous evaluation contribute to maintaining trust in AI systems. Collaborative efforts involving academia, the private sector, and international organizations help build shared knowledge and resources for AI development in food safety. Overall, AI presents opportunities to enhance resilience, efficiency, and responsiveness in food safety systems. Careful consideration of governance, data management, and multi-stakeholder cooperation can shape AI’s contribution to achieving sustainable and equitable outcomes in agrifood systems. -
BookletManual / guideGuide to formulating gendered social norms indicators in the context of food security and nutrition 2022
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At present, there is no standard or validated set of social norms indicators for food security and nutrition, and there is a general lack of clear and practical guidance and examples of such indicators for these sectors. Seeking to contribute to filling this gap, this guide will assist with formulating indicators to measure changes in gendered social norms in the context of food security and nutrition. It also offers an initial set of example indicators that programme implementers can draw on to assess social norms change in the context of food security and nutrition programmes. It draws from existing indicators from literature and programme experiences around measuring social norms, including in other sectors, and creates original indicators as well. This guide is designed for programme formulators and implementers, and monitoring and evaluation specialists responsible for creating and implementing M&E frameworks and systems for food security, agriculture and nutrition programmes. -
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