Exploring the intersection of public health and generative AI

After the COVID-19 pandemic exposed devastating weaknesses in the nation’s under-resourced public health infrastructure, interest in bulking up population-level defenses is at an all-time high. 

Public health officials and their private sector partners are seeking new ways to leverage emerging technologies – not only to combat the next big infectious disease threat, but to manage the whole range of socioeconomic disparities and healthcare access issues that also fall under their purview. 

Generative AI (gen AI) has quickly come to the forefront as a promising tool, says a team from consulting firm ICF and Google, including former National Coordinator for Health IT Karen B. DeSalvo who is now Google’s Chief Health Officer. 

In a new commentary published in Health Affairs, the team cites generative AI as a “transformative” technology for public health, and a key tool for achieving the goals of the Public Health 3.0 model, a strategic roadmap for meeting the growing needs of the 21st century population. 

“To fully realize Public Health 3.0, public health departments need to explore ways to integrate technology and new generative AI capabilities that have garnered public attention during the past two years. We believe that generative AI will provide transformative opportunities for public health officials to approach their work,” the authors write. 

“The emergence of new AI tools comes at a pivotal moment as those in the governmental public health sector are revamping their data systems based on lessons learned from the COVID-19 pandemic. There is an opportunity for public health to use technology in ways that support innovation and contribute to improved organizational systems and processes to improve health outcomes.” 

Three areas of promise for integrating generative AI into public health

The term “generative AI” describes a number of different technologies designed to create “new” content from the inspiration of existing training data, such as images, videos, audio, and text that mimics human-level creativity and intelligence.  

While these technologies are still a work in progress, they’re getting more sophisticated every day and have the potential to assist with several different high-priority areas within the public health sphere, writes the team. 

Fostering communication and education

At the top of the list is public communication and education. Informing the public about health risks is a major part of the public health mission statement, but limited resources make it difficult to communicate with target audiences through all of the channels now available to them. 

“Generative AI has the potential to offer a more personalized experience,” the authors point out. “Some experts have argued for the importance of precision public health, and generative AI will provide tools to meet the specific information needs of individuals and the public at large.” 

Gen AI can quickly and affordably create materials at multiple literacy levels and in different languages. Using widely available gen AI tools, public health officials can even personalize these materials to different geographies, cultures, or age groups and easily share them across multiple media formats. 

AI tools can also assist with speedy and effective communication via chatbots or other interfaces, increasing access around the clock for members of the public while reducing pressure on officials who may not have the staffing to support help lines in times of increased need. 

Creating organizational efficiencies

Just like their peers across the healthcare community, public health officials are eager to use gen AI to improve administrative efficiencies and organizational performance.  

“Public health uses a bureaucratic system of checks and balances and public accountability based on specific regulations and laws. This system offers transparency to the public, but it can lead to extensive clerical burden for staff at all levels,” acknowledges the team. “Generative AI has the potential to reduce this clerical burden by summarizing and automating administrative tasks, organizing large amounts of data, and providing analytic support to free up valuable time for staff to engage in work at the top of their professional capacity.” 

Gen AI can help by rapidly reviewing large volumes of public commentary, summarizing background materials to assist with policy writing, speeding up the process of writing code, and streamlining data analysis for reporting requirements. 

In an era when nearly half of public health officials have left their roles and few qualified professionals are available to replace them, gen AI could play a critical part in keeping the nation’s fragile public health infrastructure running. 

Uncovering novel insights and predictions

In light of the COVID-19 pandemic, prediction and early detection of new threat vectors is more important than ever. Public policy must stay one step ahead of emerging issues, but it take a long time and a lot of resources to gather and analyze all the relevant data using traditional methods. 

Generative AI can cut the time and investment required in this process by extracting more actionable insights from challenging data sources, such as unstructured free-text data.   

“For example, unstructured notes on medical examiners’ case reports, social media activity, and news reports are all potential useful text signals that are currently inaccessible at a population level,” said the authors. “New multimodal models are emerging that will be able to integrate additional data modalities such as imaging, genomics, environmental, and geographic data into models. Generative AI can make these data types available to increase understanding of health in novel ways and through new analytic techniques.” 

Architecting the public health infrastructure of the future

The experts acknowledge that there will be many challenges to integrating gen AI into the public health sphere, especially since the environment is highly fragmented at the state and local levels.  

Securing public trust in these technologies will be a crucial first step, especially since skepticism of science and public health information is alarmingly high among some communities. To ensure trust, developers and officials must ensure that AI algorithms are fair and unbiased, and that leaders prioritize health equity at every stage of development and deployment. 

“Senior leadership will need to identify generative AI use cases that create the greatest public value and make investments into people, processes, and technology. Regulatory frameworks for AI are actively evolving, and officials will need to understand the risks and benefits of generative AI to advocate for rules that maximize the public’s health,” the team said. 

Despite the potential bumps in the road, public health officials have an imperative to adopt generative AI and other cutting-edge technologies to further their mission of ensuring equitable opportunities for better health across all of society. 

“Public health can use AI to build on the progress of previous public health advancements,” the authors conclude. “In doing so, it is also important that public health not fall further behind as technologies advance, widening the innovation gap vis-à-vis other sectors of the economy. Public health should embrace these technological advancements and support new innovation to improve health opportunities for all.” 

Jennifer Bresnick is a journalist and freelance content creator with a decade of experience in the health IT industry.  Her work has focused on leveraging innovative technology tools to create value, improve health equity, and achieve the promises of the learning health system.  She can be reached at jennifer@inklesscreative.com.