AI, data science and public health
Exploring the promise and challenges of AI and data in public health
This work brings together researchers from public health, mathematics, AI and related fields to build connections and bridge disciplinary gaps. We are interested in how these tools can support public health research, policy and practice, while addressing ethical, social and practical questions, including public trust in how data is used.
Resources and activities
Workshop report: Causal AI and its uses in public health
This report summarises key discussions from a Cambridge Public Health workshop exploring the potential of causal AI in public health, including how it could help researchers better understand cause and effect.
Causal AI for real-world public health decisions
Professor Mihaela van der Schaar
June 2026
This seminar explored how causal AI and digital twins could help test interventions, simulate future scenarios and support better public health decisions.
Public views on AI and health data
We supported public involvement and engagement activity exploring healthcare data, AI and technology, helping researchers understand public priorities, concerns and expectations around trustworthy and inclusive innovation.
Tomorrow’s Health Today: AI and Data Science explained
In April 2025, we co-hosted Tomorrow’s Health Today: AI and Data Science Explained with the UKHSA. The panel discussion, held as part of the Cambridge Festival, explored the real-world uses and limitations of AI in health.