New working group to expand AI focus from medicine to public health

Humane Intelligence and New York University's Centre for Health Data Science have launched a working group focused on the intersection of artificial intelligence and public health. The initiative aims to address areas where AI funding and research have largely concentrated on medical health, with public health needs remaining comparatively underserved.

Sector imbalance

In the past several years, funding for AI applications has expanded rapidly across the health sector. Academic institutions, private foundations, and investors have backed efforts in clinical diagnostics, drug discovery, and streamlining insurance operations. Much of this investment has been directed at clinical and biomedical matters within the medical system.

Areas such as housing, food security, nutrition, education, and preventative measures-key determinants of public health-have not received proportional attention from new AI tools and methods. The comparatively limited support, both in funding and programmatic work, has left public health institutions facing challenges in applying new technologies across populations and environments.

Working group goals

The newly formed AI in Public Health Working Group is designed as an open and collaborative forum. Its aim is to bring together practitioners, researchers, students, and technologists from a range of backgrounds to support research and discussion on AI in the public health space. The working group will focus on multiple core themes, such as advancing understanding of social determinants of health-including living conditions, nutrition, and access to education-and evaluating the suitability of AI tools, particularly in environments with fewer resources.

Another point of attention will be the use of environmental data to inform AI systems, and building technical capacity among public health professionals so they can employ AI effectively and responsibly in their work. The group's scope reflects a broad definition of public health that includes factors operating beyond hospitals and medical clinics. Key discussion topics will cover low- and middle-income countries and resource-constrained settings, recognising differing needs and contexts globally.

Potential funding

The working group also plans to assess the feasibility of creating an AI Public Health Fund. If established, this fund would provide initial capital for research, new projects, and potentially for making grants to other organisations and initiatives. Members of the working group will play a role in setting out the fund's priorities and making recommendations regarding its structure and partnerships.

The group is open to anyone with relevant experience or interest, and members will contribute directly to research, framework development, and strategic direction for both the working group and any eventual fund.

Collaboration highlighted

"AI investments in medical health have increased significantly, but there remain critical gaps when it comes to AI and public health," said Mala Kumar, Interim Executive Director, Humane Intelligence.

The interplay between medical and public health systems became more visible during the COVID-19 pandemic, with effective treatments needing to be accompanied by broad-based public health measures to achieve real-world results.

"Public health operates at the population level, considering environmental, economic, and social factors that shape people's quality of life. We believe this working group can help highlight what is missing, expand the conversation, and build the foundation needed for meaningful progress," said Kumar.

"Public health requires multidisciplinary collaboration," said Kumar. "Bringing together experts in AI, data science, and public health is essential for understanding where AI can be useful, where it may cause harm, and where more evidence is needed. We look forward to working alongside CHDS and a diverse community of practitioners to help address these gaps."