Development of an AI-mediated Knowledge Surveillance System for Environmental Health

Development of an AI-mediated knowledge surveillance system for environmental health: The system is to automatically detect, process, structure, and make accessible relevant information from internal and external sources for policymakers and experts. It supports the monitoring of scientific literature, policy documents, reports, regulations, and other knowledge sources, translating them into usable document sheets and syntheses. The focus is on four central themes within environmental health: Substances of Very High Concern, Climate and Health, Healthy Public Space, and One Health. Knowledge will be organized according to the source-exposure-burden-effect chain (BBBE). The solution requires a human-in-the-loop approach with quality controls and human validation. It must comply with requirements for privacy, information security, AI governance, GDPR, and the EU AI Act, integrate with the Microsoft and Windows environment of the Department of Care, and be coordinated with the BID and CIT departments to ensure a secure, scalable, and sustainably manageable solution applicable to other teams.

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