This presentation explores the possibilities of artificial intelligence in public health through a people-first, problem-driven lens. Drawing on ECDC’s experience of applying AI and automation across the epidemic intelligence cycle, it presents practical examples in screening, validation, analysis and risk assessment. It also examines what can happen when automated outputs are wrong and lack human oversight. The presentation argues that effective and responsible AI requires human-centered design, multidisciplinary collaboration, and safeguards spanning technology, people and governance. It invites participants to consider: which public health decision could AI improve, for whom, and how will they know?

Population behaviors shape the course of public health crises, from infectious disease outbreaks to natural disasters. In this talk, I will describe our work using AI and data science to estimate population behaviors during crises and simulate behaviors under potential public health interventions. I will first discuss human mobility. During the pandemic, we inferred dynamic mobility networks from location data, encoding the hourly movements of subpopulations with 5.4 billion data points, which we used to model the spread of COVID-19 and to measure behavioral responses to mobility restrictions. In recent work, we developed generative AI techniques to simulate realistic mobility trajectories, capturing fine-grained differences across demographic groups. I will then discuss vaccine uptake, which we inferred in real time using AI methods and aggregated web search logs. Finally, I will shift from using AI to study population behaviors to studying how people increasingly turn to AI to make sense of public health crises, and how we can audit AI responses in these high-stakes contexts.

The 3rd National Policy Roadmap for AI in Healthcare delivers a renewed policy agenda for AI in Healthcare.It describes the critically needed next steps for a co-ordinated national approach to the orderly butenergetic adoption of AI.AI is opening new pathways to a smarter, more efficient, and more adaptive health system. From new digital ‘front door’ virtual health services, the algorithmic interpretation of imaging and pathology data, triage, resource allocation, clinical documentation to the personalisation of therapy, AI today is being used both by consumers and clinicians and is touching many aspects of healthcare.AI is also a major disrupter, presenting both opportunities and threats. In the last two years it has become clear that the pace of industry growth far exceeds our current capabilities to ensure the technology is safe and effective. It is becoming clear that system disruption is arriving fast. A handful of ‘hyperscaling’ international companies dominate the AI market. For Australia’s healthcare system to remain sustainable and resilient, it will need to shift gears, and quickly, from catching up with overseas industry, to moving ahead and defining our own pathway. If there is to be wholesale change to healthcare, then it must be on our terms.