- AI experts have listed the challenges facing the use of AI in healthcare as large language models become a thing
- A Nigerian AI expert, Agbolade Omowole, the founder of the Global AI Ethics Conference, disclosed the biases in AI
- He noted that the biases exist due to human factors, constituting challenges in AI adoption in the healthcare sector
Large language models (LLMs) like ChatGPT represent a transformative AI capability with profound potential for the healthcare sector. By ingesting and contextualising massive datasets, LLMs can aid clinicians in diagnosis, treatment selection, medical research, and more. However, using these systems requires addressing significant technical hurdles spanning data quality, model interpretability, robust testing, and data privacy.
The predictive prowess of healthcare LLMs hinges on their training data, which encompasses electronic medical records, clinical literature, treatment guidelines, and more.
