In a study, which findings were published in BMJ, researchers explored whether or not LLMs bridge or exacerbate the digital divide in accessing accurate health information.
Researchers identified the issue stemming from the LLM tool's language bias, having been trained less on such low-resource languages (or those languages with little available digital resources) as Vietnamese, results in low quality responses in languages it is less exposed to.
The researchers proposed improving LLM's translation capabilities for diverse languages and creating and sharing open-source linguistic data and tools to promote AI language inclusivity, hence addressing the current limitations of LLM-driven healthcare communication.
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