Public health meets the AI moment

George Mason’s AI in Public Health Summit examined what artificial intelligence could mean for health equity, education, and the future workforce. 

For a field built to prevent and respond to disruptions, public health now faces a defining new challenge: harnessing the rapidly evolving power of artificial intelligence. 

“There are moments in every profession when it becomes clear that change is not simply coming, that it has already arrived,” said Robert Weiler, senior associate dean for academic affairs at the George Mason College of Public Health. 

That urgency carried through George Mason’s inaugural AI in Public Health Summit, where conversations centered on what generative AI, machine learning, and large language models could mean for the future of research, education, and practice. 

“Today’s meeting is not about AI,” said College of Public Health Dean Melissa Perry. “It’s about the future of public health.” The challenge, she argued, is not simply grasping AI, but preparing future public health professionals to leverage it in ways that benefit humanity. 

To achieve that goal, the College of Public Health convened a brain trust of academics, practitioners, industry leaders, and students from across the country. Helping anchor the discussion was the Association of Schools and Programs of Public Health (ASPPH), whose AI task force is helping shape national conversations around responsible AI adoption in higher education and practice. According to ASPPH representatives, George Mason is “leading in this space” among its 150 member institutions. 

Several themes emerged across the day: 

 We must lead or risk being left behind. 

At this point, the debate has shifted from whether AI belongs in public health to how to use it responsibly and effectively. 

“There’s no escaping it,” said Eduardo Ruiz, chief information officer for ASPPH, pointing to rapid adoption across health care systems, public health agencies, and higher education. 

Arman Latif, chief information officer at the Virginia Department of Health, framed AI as “less of a tool, and more of a shift in mindset” for public health. While ethical, environmental, equity, and philosophical concerns abound, he argued that the field can't ignore a technology with such potential to improve operations and strengthen how agencies serve the public. “To not do it, in itself, is unethical,” he suggested. 

In a field focused on prevention and “upstream thinking,” speakers pointed to the promise of AI to anticipate problems instead of reacting to them: forecasting outbreaks, detecting overdose trends earlier, identifying food insecurity patterns, and uncovering insights buried in massive datasets.  

AI can assist, but humans still decide. 

The summit’s optimism around AI came with a consistent caveat: the technology may support public health work, but it will never replace the people making decisions and serving communities. 

Jamie Atchison, senior director of innovation and strategy at ASPPH, pointed to one of her group’s core recommendations: keep AI human-centered, using it as a tool for decision-makers rather than a replacement for human judgment. 

In disease surveillance, for example, AI may help detect patterns and flag emerging outbreaks, but people still need to interpret findings and take action. AI may also help tailor public health messaging to specific populations, but humans remain responsible for judgment, nuance, and building trust. 

“AI is a non-moral technology,” said Easan Selvan, national director of academic medicine and public health at Microsoft. “Whether or not we decide to use it for good … is incumbent upon” people and institutions, he said.  

 AI is a new social determinant of health. 

If public health gets AI right, speakers argued, the technology could help narrow longstanding health inequities. Get it wrong, and those gaps could deepen. 

“The risks [are] that AI can be an inequity multiplier if we’re not careful, but in fact that is up to us,” Perry said. 

 AI is already influencing many drivers of health, from information access to employment and health services. “We’re really thinking of AI as a determinant of health,” Ruiz said. 

Speakers repeatedly returned to one concern: AI systems reflect the data behind them. So, if that data excludes or underrepresents specific populations, the resulting tools risk reinforcing existing disparities. 

AI could also improve equity, from identifying vulnerable populations earlier to helping smaller health departments and community organizations access tools and data once limited to better-funded institutions. 

Classrooms are adapting in real time. 

Banning AI outright in the classroom has become unrealistic, George Mason faculty and students emphasized during the summit’s student panel. 

“People are going to be using it either way,” said biology student Anika Tahsin Siddiqui, arguing that faculty should set clearer expectations and encourage open conversation around AI use to reduce stigma. 

Students described using AI to learn coding languages, organize notes, create visualizations and presentations, and study for exams. But they pushed back against AI as a substitute for learning itself. 

Bridge-builders, translators, and critical thinkers are in demand. 

While AI literacy is quickly becoming nonnegotiable in public health roles, panelists repeatedly argued that deep technical mastery is not the end goal. Instead, they described a growing demand for “bridge professionals” who can move between worlds: understanding community needs, public health practice, and data systems well enough to connect them. 

“The translator is really key,” said Tabatha Offutt-Powell, vice president for public health data modernization and informatics at the Association of State and Territorial Health Officials. 

“Those who are early to understand, early to use, early to adapt will be the best prepared,” Ruiz said. 

Stay tuned to the College of Public Health for deeper insights from specific panels, as well as recordings of the sessions.