内蒙古以数据驱动构建食品安全风险防控网

Core Viewpoint - Inner Mongolia is implementing a project titled "Food Safety Risk Analysis and Countermeasures Research" guided by the "Four Strictest" requirements, aiming to enhance food safety regulation through data-driven decision-making and artificial intelligence technology [1][2] Group 1: Food Safety Regulation - The project aims to transition food safety regulation from experience-based judgment to data-driven decision-making by utilizing nearly five years of market supervision data [1] - A three-step methodology of "foundation consolidation - intelligent judgment - closed-loop management" is being employed to improve food safety risk prevention capabilities [1] Group 2: Data Utilization - The market supervision department is analyzing 980,000 data entries from various regulatory activities, including sampling inspections, daily checks, administrative enforcement, and complaint reports [1] - Artificial intelligence technology is being integrated to create "risk profiles" for various business types and key products, allowing for precise risk identification [1] Group 3: Risk Management - The regulatory approach includes targeted supervision based on a risk warning list, ensuring that management cycles and operational mechanisms are deeply integrated [1] - The feedback loop from regulatory results and data will facilitate model optimization, establishing a closed-loop management system characterized by "data warning, precise intervention, and continuous improvement" [1]