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    Home » AI’s Role in Modern Public Health: Surveillance, Information, and Trust
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    AI’s Role in Modern Public Health: Surveillance, Information, and Trust

    techgeekwireBy techgeekwireMarch 4, 2025No Comments4 Mins Read
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    AI Advances Public Health Capabilities

    From ambient listening to advanced diagnostics, care providers are already using artificial intelligence to improve healthcare outcomes. But the benefits of AI extend far beyond clinical settings. Public health and policy experts are discovering valuable applications for AI. If approached responsibly, compliantly, and strategically, AI can be a powerful tool in disease surveillance, combating misinformation, crafting personalized treatment plans, fraud detection, and cybersecurity, among other areas.

    Person using the computer at home
    Person using the computer at home

    Above: AI can provide solutions across many areas of public health.

    It’s important to acknowledge that every technology has its risks, and for AI, these primarily involve data privacy and security, as well as the trustworthiness of information and the potential for biases.

    Public Health Use Cases for AI

    AI can efficiently analyze large, complex data sets that are generated from electronic health records, demographic data, medical sensors, health journals, and even social media. The analysis is completed far faster and with greater accuracy than a team of statisticians could achieve. This analysis opens up a wide range of use cases for public health, including:

    Disease Surveillance and Prediction

    During the COVID-19 pandemic, governments around the world employed AI models to predict outbreaks and monitor the spread of the virus, which facilitated the deployment of timely interventions. The Centers for Disease Control and Prevention, for instance, has been using AI to track COVID-19 since 2023. While the pandemic was globally devastating, the ability to forecast potential hotspots may have helped prevent even worse outcomes. AI for disease surveillance can also help track emerging threats such as the H5 bird flu, and other, more familiar diseases. Every year, scientists and government agencies rely on disease surveillance to decide which strains of influenza will be most threatening, and this information is used in the development of vaccines. Departments of public health in many states are actively engaged in disease surveillance. By introducing AI capabilities, they can vastly improve their ability to track, forecast, and hopefully prevent dangerous disease outbreaks and ultimately save lives.

    Distribution of Public Health Information

    During the pandemic, states like South Carolina set up contact centers to address constituents’ questions and concerns. As a companion technology, or in some cases as a replacement, cities and states can now deploy AI chatbots that can help field some of these questions while acting as a trustworthy source of information. Jurisdictions can use chatbots and retrieval-augmented generation to ensure that everyone receives the same answers to the same questions, helping to maintain consistency and control over the information being shared. Deploying chatbots allows for interactive conversations, enabling users to easily engage and get the answers they need without waiting for human agents. It is even possible to provide proactive messaging alerts sent via a chatbot that can then field and answer questions via text.

    Addressing Security, Privacy, and Trust Concerns

    Health data is highly sensitive, and agencies must maintain HIPAA compliance and other standards. It’s important to remember that healthcare organizations have stored and transmitted HIPPA-protected electronic data for decades, including through telehealth and mobile health applications. AI is the next iteration of this. Just as you wouldn’t expose sensitive data to software that is not HIPAA-compliant, you wouldn’t put healthcare data into non-HIPAA-compliant large language models (or give the public the opportunity to do so). HIPAA-compliant LLMs, such as Nabla, AWS HealthScribe, and Google Cloud’s Vertex AI Search feature, do exist.

    As you investigate AI for public health use cases, there are three core considerations that will help maintain HIPAA compliance and avoid the spread of misinformation or acting on biases:

    1. Leverage the right technology: Ensure you allocate a sufficient budget and resources to implement the necessary tools.
    2. Implement Necessary Safeguards: Determine whether you can afford and implement the necessary safeguards, especially when using cloud environments or third-party services.
    3. Extensive User Training: Train users extensively.

    Finally, trust is paramount when leveraging AI. Communities must have confidence in an AI-powered public health initiative, which requires transparency around AI’s use as well as methodical data governance. Otherwise, you risk implementing the best technology with the best capabilities only to lose the community’s trust. Introducing AI into public health initiatives is a significant undertaking. Jurisdictions must move forward with utilizing AI to support public health initiatives safely and responsibly.

    AI Chatbots Artificial Intelligence data privacy Disease Surveillance public health
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