What approach is best for enhancing user health queries with credible information in a generative AI chatbot?

Enhancing user health queries with credible information in a generative AI chatbot requires a focus on the accuracy and reliability of the information provided. Grounding with third-party data from verified medical databases is the most effective approach because these databases are curated by medical experts and are often subject to rigorous validation and peer review.

Using verified medical databases ensures that the information presented to users is based on the latest research and clinical guidelines, which is essential in the healthcare domain where misinformation can have serious consequences. This approach allows the chatbot to provide responses that are not only accurate but also uphold public safety and trust.

In contrast, relying solely on internal company data may leave gaps in expertise or outdate certain information, particularly if the company is not primarily focused on healthcare. Grounding with general internet sources can lead to the incorporation of unreliable or inaccurate information, which is especially risky in the context of health queries where users might depend on the chatbot for critical guidance. Grounding with user feedback, while valuable for improving the chatbot's performance over time, does not address the foundational need for trustworthy information to begin with.