In this episode of Food Safety Matters, we speak to Christian Ararat, a seasoned food safety and quality professional with a global perspective, about a range of topics, including auditing, traceability, certifications, exporting to the U.S., and artificial intelligence (AI). We also hear from Joseph Corby, the recipient of Food Safety Magazine’s 2025 Distinguished Service Award, about his illustrious career and advocacy work.
On the morning of Thursday, May 15, food safety professionals from across the country will gather for one of the Food Safety Summit's most anticipated events—the 13th Annual Town Hall session titled, "A Candid Dialogue on the Future of Food Safety."
In an April 25 speech, UK Food Standards Agency (FSA) Chief Executive Katie Pettifer described efforts FSA is taking to improve meat industry regulation, including supporting the adoption of new technologies, negotiating international trade agreements, addressing inspector and veterinarian workforce shortages, evaluating inspection charge discounts, and tackling food crime.
According to FOODAKAI’s Global Food Recall Index, the first quarter of 2025 has seen significant increases in food product recalls across the dairy, poultry, and produce categories internationally.
Using EU Rapid Alert System for Food and Feed (RASFF) data, researchers have developed an integrated artificial intelligence (AI) framework for conducting food safety risk assessments, and demonstrated its usefulness in decreasing the ambiguity of risk management decisions.
This episode of Food Safety Five discusses newly published CDC data about the pathogens causing foodborne illness and contributing factors of outbreaks, as well as research by CDC, USDA, and FDA scientists exploring the use of AI analysis of whole genome sequencing data for foodborne illness source attribution.
A project funded by the Center for Produce Safety is developing an identification and deterrent system for high-risk birds in produce fields based on sound surveillance and artificial intelligence (AI). The tool would automatically deploy interventions to drive away birds that are more likely to spread foodborne pathogens.
Researchers from CDC, FDA, and USDA trained an artificial intelligence (AI) machine learning model to conduct food source attribution for human cases of salmonellosis by analyzing whole genome sequencing (WGS) data for Salmonella isolates. The model showed promise, estimating that the majority of salmonellosis cases are caused by chicken and vegetables
In a new study, the UK Health Security Agency (UKHSA) evaluated the ability of artificial intelligence (AI) to detect foodborne illness outbreaks by analyzing online restaurant reviews. Although several challenges were identified that must be overcome before AI can be used routinely in epidemiological investigations, UKHSA believes the approach shows promise.
