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AI-Mediated Interactive Health Messaging for Community Health Promotion in Low- and Middle-Income Countries

Imad Elhajj of the Humanitarian Engineering Initiative of the American University of Beirut in Lebanon will use Large Language Models (LLMs) to develop an interactive community health promotion platform with a chatbot that provides accurate health messages and real-time responses to queries on platforms like WhatsApp to vulnerable populations in Lebanon and Jordan. They will process texts from trusted websites, documents, and other text repositories, such as UNICEF and the WHO, into smaller text segments. These segments will then be converted into fixed-length vectors that capture their semantic meaning and contextual relationships. To generate answers, the GPT-3.5/4 model will retrieve the relevant vectors based on the user's query and use them together with the context taken from the conversation history. They will first evaluate the platform internally to ensure the relevancy, coherence and accuracy of the generated messages, and then conduct a pilot study with a small representative group from the target communities.

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