Is Public Health Still a Good Major in the AI Era?
A parent who knew I teach in a college of public health asked me the question quickly, the way people ask questions they have been carrying for a while: “Is public health still a good major? With AI doing everything now — will there even be jobs?”
I have been asked for some version of these enough times now that I want to write the answer down. It is the second post in a small series on choosing a major in the AI era; the first one, on physics versus biology, is here.
The short answer
Yes. And in some ways, more than before.
But the longer answer matters, because the reason it is still a good major is not the reason most people assume.
Four things AI is doing to public health work
To answer the question well, it helps to separate public health work into four parts. AI is doing different things to each of them, and the major is shaped by all four.
1. The work AI now does for us
AI now drafts standard reports faster than any of us can. It cleans data. It synthesizes hundreds of papers in minutes. It translates surveillance forms across languages. It produces the first version of a community health brochure in seconds.
If a student imagines a public health career built on those tasks, that career has narrowed. But these tasks were never the heart of public health. They were the load that early-career workers carried because someone had to. AI takes that load, and that is mostly fine.
2. The work we have been over-investing in
Some of what public health curricula traditionally emphasized was already a holdover before AI arrived: memorizing tables that any reference tool can retrieve, rehearsing manual calculations a calculator does better, drilling formats over reasoning. AI makes the cost of these habits more visible. The students who graduate strongest now are the ones whose programs have stopped over-investing here and redirected the time elsewhere.
3. The work that becomes more powerful with AI
Some public health work is not replaced by AI but transformed by partnership with it. An epidemiologist who uses AI to scan a thousand surveillance signals and then applies human judgment to the ambiguous ones is doing something neither could do alone. A health communicator who drafts in collaboration with AI and brings cultural fluency to the revision is producing better material than either would in isolation.
This is the part of the major that students should learn to do well. Not AI as shortcut. AI as a reasoning partner whose output you can evaluate, critique, and override when you need to.
4. The work that stays human — and gets more valuable as AI scales
There is a category of public health work that AI does not replace, and that becomes more important precisely because AI is doing more of everything else.
Consider what happens during an outbreak. An AI model can flag an unusual cluster of respiratory illness. It cannot decide whether to recommend a school closure. That decision weighs harm that fall on different people unequally — children who lose instruction, parents who lose income, elders at risk if schools stay open — and the person making it has to be answerable to a community. Accountability is not a computational feature. It is a human one.
Or consider trust. A health department announces a vaccine campaign. Whether people show up depends on whether the messenger is someone the community already trusts. AI can draft the flyer. It cannot be the trusted person.
Or consider framing the right question in the first place. AI is very good at answering questions. It is not good at noticing which questions matter. A public health professional looking at maternal mortality data must decide whether the story is about hospitals, or insurance, or housing, or transportation, or all these together. That “what is this really about” judgment is irreducibly human.
These parts of the work do not go away. They get harder, and they get more valuable.
Why does this means the major still works
A major is a good one in the AI era when most of its core work falls into the third and fourth categories — work that AI amplifies, and work that stays human. Public health is unusually well-positioned on both.
Its center has always been judgment under uncertainty, accountability to communities, and the capacity to ask the right question about a population’s health. Those are the parts that AI cannot do. And the parts where AI helps — surveillance, synthesis, modeling, communication drafting — make a well-trained public health professional more capable, not less.
The students who will struggle are the ones who treat the major as a path to routine technical work. The students who will do well are the ones who treat it as preparation for the judgment that AI cannot replace.
Observer’s Insight
The AI-era question for any major is not “will AI replace this?” It is: what part of this work was always about being human, and what part was a holdover from the time before AI could do the rest? Majors with a strong answer to the first half of that question — public health among them — are not endangered. They are clarifying.
Related
Earlier in this series: Comparing Majors in the AI Era: Physics vs. Biology — on the difference between role-anchored and person-anchored career resilience.
— Min Wu, PhD, Associate Professor, Zilber College of Public Health, University of Wisconsin-Milwaukee
As a member of the Springer Nature Author Affiliate Program, I may earn a small commission from purchases made through this affiliated link to my book. Support the author by checking out my textbook, Artificial Intelligence in Public Health: https://tidd.ly/4mH9389
