Public health students are learning how AI can benefit disease surveillance, analyze data and build their workforce skills.
Photo by Dragos Condrea, courtesy iStockphoto
“Academic public health has a responsibility to prepare students — and the current workforce — to engage with AI thoughtfully and ethically and in ways that advance equity, promote sustainability and protect communities.”
— Laura Magaña
Across the U.S., AI is moving from theory to practice in public health classrooms, reshaping how the future workforce is trained.
In Washington D.C., public health students at the George Washington University interact with customized AI “agents” that are programmed to simulate professional roles and guide students through real-world scenarios. In Chicago, students at Northwestern University explore how algorithms and data tools can shape everything from disease surveillance to community health. At the University of Memphis, graduate students engage in mapping AI policies across public health schools and analyzing job postings to identify the skills and competencies employers want in an AI-ready workforce.
“The potential of AI in public health education is boundless, promising to deliver more responsive, engaging and impactful education in line with the evolving global health landscape,” researchers wrote nearly two years ago in a review in Frontiers in Public Health.
The prediction has become a reality. Research shows AI-powered tools are increasingly being used to personalize lessons, run immersive simulations of outbreaks and help students analyze real-world health data. At the same time, experts warn that educators, technologists and policymakers must carefully ensure that AI strengthens, rather than replaces, the human side of learning and public health practice.
“Like the early days of the internet, this is a moment of learning by doing, with a focus on preparing the public health workforce for tools already shaping practice,” Courtney Queen, PhD, associate dean for strategic partnerships at Texas Tech University Health Sciences Center's Julia Jones Matthews School of Population and Public Health, told The Nation's Health.
Queen said students are learning to use AI transparently and critically, as support for tasks such as synthesizing public data, drafting summaries and exploring scenarios, “while retaining responsibility for verification, interpretation and judgment.”
That approach, she said, reinforces core public health competencies, including data literacy, ethical reasoning and accountability. AI is also used at the administrative and faculty level to support curriculum development, competency alignment, needs assessment and planning to help educators analyze information more efficiently and consistently, Queen said.
AI-powered tools are being used to personalize lessons, run immersive simulations of outbreaks and help students analyze real-world health data.
Photo by Gorodenkoff, courtesy iStockphoto
But human expertise must remain at the center, with clear guardrails around acceptable use to allow both students and educators to experiment thoughtfully, she cautioned.
On the Caribbean island of Grenada, that same learning-by-doing approach also shows up at St. George's University, where public health graduate students actively employ generative AI solutions, said Kerry Mitchell, PhD, chair and associate professor in the Department of Public Health and Preventive Medicine.
“Our program tries not to place too much emphasis on specific tools,” Mitchell told The Nation's Health. “We believe students will find the tools they need to solve problems and likely may be steps ahead of faculty and educational institutions in the latest technology.”
Classes typically encourage the use of tools such as ChatGPT, but some courses push students to use retrieval-augmented generation, an AI framework that searches outside sources, such as trusted databases, documents or websites, for relevant knowledge before generating answers. The systems can pull in fresh, credible data without being limited to what a large language model such as ChatGPT has “learned” during training.
To ensure the conversations are grounded in student experience, Mitchell said the school recently launched a “pulse” survey at the end of each term, asking students to express their opinions on AI technology and share how they use or plan to use it in their learning and practice.
“We believe that with continued open discussion and a clear understanding of the underlying technology, our students and faculty will be equipped to identify the most suitable tool when needed, but do so within the framework of responsible and ethical use, aligning with core foundational public health principles,” Mitchell said.
But as AI reshapes assignments, simulations and classrooms, educators warn it could overshadow the core mission of public health. While generative AI can rapidly produce products that can meet specific assignment criteria, it may deny students the opportunity to develop foundational knowledge and skills, according to Andrew Wiss, PhD, EdM, assistant dean for academic innovation at the George Washington University's Milken Institute School of Public Health.
Some universities are offering training to faculty to build their digital AI skills, which they can use with their students.
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“Amid all this transformation, it's important to remember that generative AI hasn't changed the requirements for academic success,” Wiss told The Nation's Health. “It's essential that students continue doing the hard work of developing foundational competencies before they will be ready to partner with generative AI tools.”
Missing too many of such opportunities, especially in their foundational coursework, could result in not having the building blocks required to develop complex skills in more advanced courses and master program-level competencies, Wiss said.
Noting that a lack of expertise can lead to unintentional errors, bias and faulty methodologies in the complex work that public health professionals engage in, Wiss said the school has adapted the Transparency in Learning and Teaching framework to provide students with assignment-specific guidance on how generative AI could be used to support their learning — and when it should be avoided. The goal is to ensure they continue on the pathway to developing essential knowledge and skills.
In addition to the framework, the school has implemented several novel applications of generative AI tools, including custom “agents” serving as self-directed learning partners for students, and a platform developed in-house by Wiss and a team of graduate students that lets students have conversations with AI agents from different health professions. The simulations help students become more practice-ready for job roles, Wiss said.
“This really ends up being a moment of opportunity for schools of public health to truly personalize learning for students and where each individual learner is,” Wiss said.
Faculty becoming next experts in AI
The shift is not limited to students. Across academia, faculty and administrators are becoming learners themselves as universities experiment with how artificial intelligence should be taught in the classroom.
At Northwestern University, a six-week professional development course invites instructors to design a generative AI–powered assignment, test it with their students and study what unfolds. The course is meant to build digital AI skills among faculty while keeping questions of responsibility and ethics in view. No prior AI experience is required of faculty to be admitted to the course.
Andrew Naidech, MD, MSPH, Master of Public Health program director at Northwestern University's Feinberg School of Medicine, used the project to shape an assignment for his data visualization class.
“We saw a wide range of results, showing students opportunities and pitfalls,” said Naidech, noting the university has a data-protection agreement with Microsoft CoPilot.
The exercise showed AI could produce a polished first pass and jog students' memory on forgotten code, but it also introduced errors and unnecessary detail, Naidech told The Nation's Health. In the end, many students said they preferred building visualizations themselves, turning to AI as a thinking partner rather than a stand-in.
Questions about where AI fits in classrooms, competencies and the future public health workforce are now moving onto the national stage. The Association of Schools and Programs of Public Health, for example, has convened a task force aimed at defining how the technology should guide, rather than remake, how students are trained.
Public health students are learning how to ethically and thoughtfully use AI.
Photo courtesy FatCamera, iStockphoto
“Academic public health has a responsibility to prepare students — and the current workforce — to engage with AI thoughtfully and ethically and in ways that advance equity, promote sustainability and protect communities,” ASPPH President and CEO Laura Magaña told The Nation's Health.
For task force chair Ashish Joshi, PhD, MBBS, MPH, dean of the School of Public Health at the University of Memphis, the initiative represents a chance to turn a patchwork of campus experiments into a shared conversation among academia, industry, practice and research. The opportunity exists to wrestle with unsettled questions of how curricula should evolve, what competencies belong at the core of public health training and how to prepare students for roles that may not yet exist.
Among Joshi's long-term visions for the task force is a national best practices hub or incubator that includes case studies, examples and simulations to give educators a clear picture of what already exists. To build that baseline, he and a team of graduate students recently completed what he calls the first landscape analysis of AI policies across ASPPH's 150-plus member schools. The team has mined hundreds of webpages and documents to identify about 18 policies among member schools and programs.
“To the best of my knowledge, this is the first such landscape analysis of the entire policies and guidelines that are available in the use of AI in this domain,” Joshi said.
Similarly, a companion project looks outward, analyzing dozens of job postings on sites such as Glassdoor and Indeed to map the skills and competencies that employers may be seeking.
Joshi views the project as a way to help schools align classroom learning with the skills needed in a rapidly evolving public health field.
“At least if we know what jobs exist — what are the preferred and essential qualifications they're looking for? — we have some benchmarks,” Joshi told The Nation's Health.
But the real test of AI in public health education will come long after students leave the classroom.
What students learn in school about AI is only the beginning, said Rubin Pillay, PhD, MD, MBA, MSc, assistant dean in the School of Medicine at the University of Alabama at Birmingham.
“Education cannot stop at graduation,” Pillay told The Nation's Health. “We need micro-credentialing and just-in-time training platforms, powered in part by AI itself, to help the current workforce continually upskill — from the sanitarian using an AI inspection tool to the health director evaluating an AI vendor contract.”
For more on ASPPH's Leadership: Task Force for Responsible and Ethical Use of Artificial Intelligence, visit https://aspph.org/ai-for-public-health.
This article was edited post publication.
- Copyright The Nation’s Health, American Public Health Association
