From disease surveillance to clinical care, artificial intelligence is transforming health. As AI becomes more deeply embedded in decisions affecting population health, a new editorial argues that realizing AI’s full potential requires public health leadership alongside technical innovation.
Dr. Debbie Cheng , assistant dean of data science at Boston University School of Public Health, and lead author of a new peer-reviewed opinion piece published in American Journal of Public Health makes the case that public health leadership is essential to building trustworthy AI in health. Dr. Sandro Galea , dean of the Bursky School of Public Health at Washington University in St. Louis, and Dr. Madhu Mazumdar , director of the Institute for Healthcare Delivery Science at the Mount Sinai Health System in New York City, coauthored the article.
"Public health is a field that has spent decades developing methods to evaluate interventions, monitor impacts, and address inequities," says Cheng, who is also a BU professor of biostatistics and a Hariri Institute Core Faculty member. "Those strengths are highly relevant to AI. It has enormous potential to improve population health, and the greatest opportunity comes when public health expertise helps shape it from the outset."
The editorial asserts that AI should be viewed not only as a technological innovation, but also as a public health opportunity. While AI developers have driven rapid advances, public health brings complementary expertise in understanding how innovations perform in real-world settings, affect different populations, and evolve over time. That perspective broadens how AI should be assessed, looking beyond technical performance to consider trustworthiness, equity, transparency, and population health impact.
The authors highlight examples showing why technical performance alone is not enough. Some AI systems used in dermatology have been shown to perform less accurately on darker skin tones, while other algorithms have underestimated illness severity among lower-income patients because they relied on healthcare costs as a proxy for medical need. Together, these examples illustrate why public health expertise is essential to ensuring AI systems are trustworthy, equitable, and effective across diverse populations.
Beyond evaluating outcomes, Cheng says one of public health's most important contributions is asking critical questions early in the development process: Who benefits? Who might be left behind? What unintended consequences could emerge? Considering these kinds of questions up front, she says, can help ensure AI technologies improve health for everyone.
Cheng is already helping put those principles into practice at Boston University. As founding executive director of the Center for Health Data Science and director of strategy and partnerships for BU's AI Development Accelerator (AIDA), she works with members across the University community to support the responsible integration and adoption of AI in research, education, and administration.
"One of the things I value most about AIDA is the opportunity to bring a public health perspective into conversations about how AI is being adopted across the university," she says. “The best solutions emerge when people from different disciplines learn from one another.”
Looking ahead, Cheng hopes the editorial will encourage greater collaboration among public health researchers, clinicians, educators, and AI developers. One way to achieve that, she says, is by building communities of practice where experts from different disciplines can learn from one another and develop thoughtful approaches to integrating AI into their own work.
More broadly, the authors argue that realizing AI's promise for improving population health will require public health expertise to be embedded throughout the AI lifecycle — from development and implementation to evaluation and long-term governance.
"The future of AI in health will be strongest when technical innovation and public health leadership advance together," Cheng says.
American Journal of Public Health
Commentary/editorial
Not applicable
Trustworthy Artificial Intelligence in Health Requires Public Health Leadership
2-Jul-2026