JMIR Publications

ABSTRACT

The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during health emergencies. This paper explores the utility and implications of generalist Conversational AI (CAI)- advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. Specific focus is on using generalist CAI within messaging services, emphasizing its potential to enhance public health communication. We highlight the evolution and current applications of AI-driven messaging services, including their ability to provide personalized, scalable, and accessible health interventions. Specifically, we discuss the integration of large language models (LLMs) and generative AI in mainstream messaging platforms, which may potentially outperform traditional online information retrieval systems in public health contexts. We report a critical examination of the advantages of generalist CAI in delivering health information, with a case of its operationalization during the COVID-19 pandemic, and the strategic deployment of these technologies in collaboration with public health agencies. Additionally, we address significant challenges and ethical considerations, such as AI biases, misinformation, privacy concerns, and the required regulatory oversight. We envision a future with leveraging generalist CAI in messaging apps, proposing a multi-agent approach to enhance the reliability and specificity of health communications. We hope this commentary initiates the necessary conversations and research towards building evaluation approaches, adaptive strategies, and robust legal and technical frameworks to fully realize the benefits of AI-enhanced communications in public health, aiming to ensure equitable and effective health outcomes across diverse populations.