Why Public Health Practitioners Must Lead in the AI Era: Equity, Sustainability, and Literacy

PH practitioner in the world of AI.

 

Why Public Health Practitioners Could Lead the AI Era

Artificial intelligence is rapidly emerging as one of the most transformative forces in global health. Its potential to predict outbreaks, streamline health systems, and provide new insights into disease prevention is immense. Yet, the path forward is still being shaped. AI is not a ready-made solution—it is a powerful tool whose benefits and risks will depend on how society chooses to use it. Public health practitioners, with their focus on equity, prevention, and population well-being, are uniquely positioned to guide this process.

AI as a Determinant of Public Health

Public health has long addressed social and environmental determinants such as income, housing, and access to care. AI now has the potential to join that list. Algorithms are beginning to influence how surveillance detects outbreaks, how resources are distributed, and how information flows during emergencies. These applications offer enormous opportunities but also raise questions about fairness, transparency, and accountability. If public health does not help shape the direction of AI, others will define it in ways that may not prioritize population well-being.

Equity, Prevention, and Trust

The values of public health—equity, prevention, and trust—align directly with the challenges of AI. Practitioners can ensure that AI models are tested across diverse populations and monitored for bias. They can anticipate risks before they scale and design systems that protect vulnerable groups. Just as importantly, public health professionals have experience building community trust, a quality essential when rolling out new technologies in sensitive health contexts. With AI, the potential to either strengthen or erode trust is significant, and public health voices must help guide that outcome.

The Environmental Dimensions of AI

AI’s influence is not limited to data and health outcomes; it also affects the environment, a cornerstone of population health. Large AI models consume vast amounts of electricity and water, raising sustainability concerns.

Consider the evidence. Google reported that in 2021, its data centers used about 450,000 gallons of water per day for cooling (Google Sustainability, 2021). By 2022, that number had reached 5 billion gallons annually, while Microsoft’s water use rose by 34 percent during the same period (Yale E360, 2023). In some cases, facilities in water-stressed regions have been found to consume up to 5 million gallons of drinking water daily, competing with community needs (University of Tulsa, 2023).

Electricity use tells a similar story. The International Energy Agency projects that global electricity demand from data centers could more than double by 2030, reaching 945 terawatt-hours annually—comparable to the consumption of a large industrialized nation (IEA, 2023). For public health, this means that the benefits of AI must be weighed alongside environmental trade-offs that directly affect health outcomes.

AI Literacy in Public Health Education

Harnessing AI’s potential requires more than technical capacity—it demands literacy. Public health schools have a unique opportunity to integrate AI literacy into their curricula, equipping students to critically evaluate, deploy, and govern AI tools. Such training would cover how algorithms are developed, how biases emerge, and how environmental costs shape population health. It would also emphasize governance, transparency, and community engagement. By embedding AI literacy into education, schools can prepare graduates to lead in shaping AI toward equitable and sustainable futures.

From Potential to Leadership

AI is not yet defined—it is unfolding. It could revolutionize public health practice, or it could deepen inequities and strain vital resources. Whether it fulfills its potential depends on who leads its integration. Public health practitioners, with their experience in prevention, equity, and population-level stewardship, are best suited to ensure AI becomes a force for health rather than harm.

A Call to Engage

The AI era is not a distant possibility—it is here. But its direction is still open. Public health must not remain on the sidelines. By engaging now—through education, governance, and community-centered approaches—practitioners can help ensure that AI strengthens health systems, protects resources, and builds trust across societies.

The potential is vast. The leadership must be ours.

References

  • Google Sustainability. (2021). Our commitment to climate-conscious data center cooling. Retrieved from Google Blog
  • Yale Environment 360. (2023). Artificial Intelligence’s growing thirst for energy and water. Retrieved from Yale E360
  • University of Tulsa. (2023). Data centers draining resources in water-stressed communities. Retrieved from University of Tulsa News
  • International Energy Agency. (2023). AI is set to drive surging electricity demand from data centres. Retrieved from IEA

 

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