Tutorial Mission & Objectives
Artificial intelligence is transforming public health, offering new ways to access information, generate insights, and support decision-making. This tutorial provides digital health professionals – including researchers, infection control experts, nurses, and doctors – with a practical introduction to generative AI and its applications in public health.
Participants will explore how AI can enhance information retrieval and decision support by leveraging domain-specific knowledge through custom AI assistants. The session covers fundamental concepts such as retrieval-augmented generation (RAG) and prompt engineering, along with practical risks like AI-generated misinformation.
A hands-on component will allow attendees to apply these concepts, working with curated public health documents to customise and deploy a retrieval-based AI system. This tutorial is designed for digital health professionals seeking to understand and apply AI tools in their daily work, ensuring AI-driven insights are relevant, reliable, and support human decision-making.
Intended Audience
This tutorial is designed for digital health professionals who want to understand and apply AI
in their work, including:
- Public health researchers
- Epidemiologists and infection control experts
- Healthcare policymakers
- Clinicians, nurses, and frontline healthcare professionals
- Health data analysts and informaticians
- AI and digital health innovators interested in practical applications
Participants should have a general understanding of digital health tools but don’t need prior
AI expertise.
Expected Outcomes
By the end of the tutorial, participants will:
- Understand the fundamentals of generative AI, retrieval-augmented generation (RAG), and prompt engineering
- Identify the strengths, limitations, and risks of AI-driven decision support
- Gain hands-on experience customising and deploying an AI assistant using public health data
- Develop practical strategies for integrating AI tools into research, policy, and clinical decision-making
- Recognise the importance of human oversight in AI-driven insights
- Leave with a framework for safely and effectively using AI in their professional practice
Format and Schedule
| Time | Session | Description |
|---|---|---|
| 00:00 00:40 | Lecture: AI in Public Health | Introduction to generative AI, retrieval-augmented generation (RAG), and prompt engineering. Discussion of strengths, limitations, and misinformation risks. |
| 00:40 01:20 | Hands-on Workshop | Participants work with curated public health documents to customise and deploy a retrieval-based AI system. Guided exercises help tailor AI models for professional use cases. |
| 01:20 01:30 | Q&A and Wrap-Up | Final discussion on best practices, implementation challenges, and future AI applications in public health. |
SPEAKERS:
Dr David Gerouville-Farrell
Dr David Gerouville-Farrell is an AI strategist and product leader with 20+ years of experience spanning digital health, game based learning and AI transformation in the public and private sector. He led the UK’s first public-facing LLM service in central government and has contributed to national AI policy. His work includes using digital tools to convey complex concepts like antibiotic resistance, climate change, and health behaviour change. Spanning roles from technical implementation to governance and public speaking, he enjoys helping people solve problems and making AI practical, effective, and accessible.