Youth For Public Health

Recently, I went into a Wendy’s drive thru and was surprised when an AI voice took my order. It reminded me of something my dad mentioned about the hospital where he works. They’ve started using “AI doctors” to give quick medical advice when the hospital staff are very busy. He said the system was impressive and surprisingly knowledgeable, but also warned that it sometimes gave careless suggestions that could be risky if people only listened to AI. That mix of potential and caution is exactly why today’s post dives into AI in public health. So in today’s post, we will talk about how AI in public health is helping, where it’s flawed and what we should keep in mind and know as it starts to become more common. Today, this post will look at information from Gao, Chen, and Huang’s systematic review, Opportunities and challenges of artificial intelligence in public health, published in Frontiers in Public Health in 2026, which analyzes 136 studies on AI’s impact, risks and governance needs in modern public health systems. 

AI is already reshaping public health in huge ways. According to Gao, Chen and Huang’s systematic review, AI has “significantly enhanced the efficiency of epidemic surveillance, emergency response, health communication and clinical decision support.” Tools like EPIWATCH help public health teams act faster by scanning huge amounts of online information to spot early signs of outbreaks. AI also speeds up diagnosis by analyzing medical images quickly and accurately, which “effectively alleviated the burden on frontline healthcare workers.” Besides those benefits, AI has also helped improve the everyday tasks needed in public health. From personalized health education to smarter/better communication systems that contribute to more accessible information. 

However, the same article makes it clear that AI comes with real flaws we can’t ignore. The authors warn that especially for marginalized communities, algorithmic bias and poor quality data can lead to “amplified structural inequalities in healthcare resource allocation.” Also, because AI systems rely on huge amounts of personal health information, privacy risks are also a major concern. Also, the article reveals that communities with histories of data exploitation like some North American Indigenous groups show “deep mistrust toward AI monitoring systems.” Even when the technology works well, public acceptance often depends on whether people feel the system respects their rights and privacy.

As AI becomes more common in public health agencies, clinics and hospitals, the article argues that we need to approach it with caution, and make sure to be responsible. The authors emphasize that AI is a “major socio-technical transformation” that changes how decisions are made and who holds power. In other words, AI can absolutely strengthen public health but only if we are aware of its limits, and make sure the technology serves everyone fairly, not just those with the best access or the most resources.