Trust at risk: Why public health must lead the use of AI in pandemic preparedness

Comprehensive Summary

This commentary article, presented by O'Connell and Quintyne, examines whether public health institutions should take the lead in governing artificial intelligence (AI) use in pandemic preparedness rather than allowing commercial entities to drive its implementation. To do this, the authors analyze the role of trust in public health practice and how AI integration could either strengthen or undermine that trust during pandemic responses. The authors argue that while AI has already demonstrated advantages in infectious disease modeling, syndromic surveillance, and health system forecasting, its success depends not just on technological capability but on maintaining societal trust in public health institutions. Researchers found that trust operates at multiple interconnected levels including public trust in health authorities, institutional trust between organizations, and professional trust within response teams. This also highlighted that fragmented AI implementation across borders and sectors risks generating inconsistent guidance that could erode trust and compliance during emergencies. The authors finish their claims by explaining that public health professionals must proactively lead AI governance through developing ethical frameworks, conducting applied research to determine where AI adds value, and shaping the digital and legal infrastructure needed for safe AI integration across health systems

Outcomes and Implications

This research is important to the medical field because it highlights the critical need for public health leadership in AI governance before the next pandemic occurs, particularly as commercial interests currently drive much of AI development in healthcare. Trust in health authorities has declined across Europe since COVID-19, and allowing AI to emerge as a commercial determinant of health could further erode this essential foundation of pandemic response. In terms of its clinical importance, understanding how AI-informed decisions could conflict with public health ethical principles like fairness, proportionality, and reciprocity can help prevent systems that undermine the trust-based relationships upon which effective pandemic control measures depend. The authors' call for whole-of-government AI testing through pandemic preparedness exercises suggests that this technology needs validation in realistic scenarios before it can be relied upon during actual emergencies. With public health institutions being statutorily accountable to populations rather than shareholders, they are uniquely positioned to ensure AI aligns with societal values and public interest. While further applied research is needed to identify where AI can effectively add value in pandemic contexts, this commentary lays the foundation for a governance framework that could allow AI to strengthen rather than compromise the collective and ethical foundations of pandemic preparedness in the future.