Collaborative AI Workflows: Bridging Sectors in One Health Research
Outline
Introduction: The silo problem in health research
Multi-stakeholder data sharing frameworks
AI tools that respect privacy and governance
Spotlight: A successful human-veterinary collaboration
Best practices for interdisciplinary teamwork
Conclusion: Toward a unified One Health community
One Health research promises transformative insights—but only if human, animal, and environmental scientists collaborate seamlessly. Too often, data lives in institutional “silos,” and legal or technical barriers inhibit sharing. Artificial Intelligence (AI) offers not only powerful analytics but also new models for secure, governed collaboration.
At AIA4OneHealth, we champion multi-stakeholder frameworks where governments, NGOs, academic labs, and private-sector partners contribute de-identified data into federated AI platforms. These systems train models across distributed datasets without moving raw data—preserving privacy and meeting diverse regulatory requirements.
Take our recent project on antimicrobial resistance (AMR) surveillance: hospitals, poultry farms, and wastewater treatment plants each fed genomic and phenotypic AMR data into a federated learning network. The resulting AI model achieved a 92 % accuracy in predicting resistance patterns, outperforming any single-sector dataset.
Key to success is establishing clear data-governance policies from day one: who owns what, under which conditions new partners can join, and how results are shared. We also incorporate audit trails and explainable AI techniques so stakeholders understand—and trust—model decisions.
Interdisciplinary teams thrive when communication is structured: regular sprint meetings, shared documentation hubs, and joint training workshops on both domain expertise and AI methods. In our pilot at the Federal University of Agriculture, Abeokuta, weekly “One Health Clinics” bring doctors, veterinarians, ecologists, and data scientists together—fostering mutual learning and co-design of research protocols.
By building collaborative AI workflows that bridge sectors, AIA4OneHealth is laying the groundwork for a truly integrated One Health research ecosystem—one where insights flow freely, innovations scale efficiently, and global health challenges are met with united strength.
