How Can AI Help Improve Food Safety?

With advances in artificial intelligence (AI) technologies, the development and implementation of digital food systems are becoming increasingly possible. There is tremendous interest in using different AI applications, such as machine learning models, natural language processing, and computer vision to improve food safety. Possible AI applications are broad and include, but are not limited to, (a) food safety risk prediction and monitoring as well as food safety optimization throughout the supply chain, (b) improved public health systems (e.g., by providing early warning of outbreaks and source attribution), and (c) detection, identification, and characterization of foodborne pathogens. However, AI technologies in food safety lag behind in commercial development because of obstacles such as limited data sharing and limited collaborative research and development efforts. Future actions should be directed toward applying data privacy protection methods, improving data standardization, and developing a collaborative ecosystem to drive innovations in AI applications to food safety.

Automated summary

With advancements in AI technologies, the development and implementation of digital food systems are becoming more feasible. AI applications such as machine learning, natural language processing, and computer vision have the potential to enhance food safety in various ways. However, obstacles such as limited data sharing and collaborative research efforts hinder the commercial development of AI technologies in food safety. Future actions should focus on data privacy protection, data standardization, and the establishment of a collaborative ecosystem to drive innovations in AI applications for food safety.