Certain components of the food safety plan, like preventive maintenance and environmental monitoring, can benefit from the predictive characteristics of AI; however, the quality of the data fed into the system is critical.

The Institute of Food Technologists (IFT) is rolling out an updated version of its popular, four-session virtual workshop on the food industry applications of Artificial Intelligence (AI), beginning on April 23, 2024.

This article explores the transformative strategies, methods, and approaches of AI technologies in the realm of USDA-FSIS operations, with an introduction of ten major AI systems for different applications and purposes.

Artificial Intelligence (AI), while offering remarkable advancements in various fields, also presents a paradoxical threat, especially when misused. 

This article explores the benefits offered by "beneficial" artificial intelligence (AI) as applied to the food and beverage industry and specifically to food safety practices. It discusses relevant elements of President Biden's October 2023 Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, as well as the Department of Defense's June 2023 Data, Analytics, and Artificial Intelligence Adoption Strategy, and what these documents mean to AI applications in food safety.

With a $5 million grant from the U.S. National Science Foundation (NSF), a multidisciplinary research team is developing sensor-based rapid detection technology, backed by an artificial intelligence (AI) –powered decision support system, to control Salmonella and other foodborne pathogens throughout the poultry supply chain.

A recent publication from the Food and Agriculture Organization of the United Nations (FAO) has provided an in-depth review of early warning systems for food safety risks, an explanation of available open access tools, and the potential applications of Big Data and artificial intelligence (AI) in the field.

This article provides a future-oriented perspective on comprehensive food safety programs that harness multi-layered sensor technology and artificial intelligence (AI). The program described begins with biosurveillance at the producer level and seamlessly extends to the retail food sector.

The advent of artificial technologies like electronic noses, electronic eyes, and electronic tongues has fundamentally reshaped our approach to evaluating food samples, as underscored by their ability to capture intricate sensory attributes. The symbiotic relationship between artificial instruments and machine learning underscores their potential to reshape the food industry, ensuring that the food we relish is not only delectable but also safe and of the highest quality.

The use of artificial intelligence (AI) tools like big data and machine learning for antimicrobial resistance (AMR) surveillance in livestock production shows promise for informing AMR mitigation efforts, according to a recent study led by University of Nottingham researchers.