Diabetes self-management and education (DSME) is an integral part of diabetes care and has been shown to improve glycemic control, reduce complications, and increase quality of life (1).The traditional model in which clinicians and diabetes educators share responsibility for patient education faces challenges such as reduced access to care during the pandemic and a shortage of trained educators.Artificial intelligence (AI) solutions are increasingly recognized to have a strong use case in DSME (2).Smart conversational agents ("chatbots") have shown potential as tools for direct patient engagement and education (3).While previous generations of chatbots delivered structured output based on preset queries and responses, modern natural-language AI models are designed to accept unstructured or nonstandardized inputs and provide human-like responses.These models draw on a large repository of humangenerated textual content to produce responses statistically likely to match the query.While chatbots may be able to augment patient care by providing ondemand answers to patient questions, they are based on language patterns rather than objective databases and may provide patients with authoritativesounding information that is inaccurate.ChatGPT is a chatbot developed by OpenAI based on the GPT3 large language model.It is readily accessible by the general public and has gained popular traction.It has recently been shown to be able to pass the U.S.
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Sng et al. (2023) studied this question.