We highly appreciate the insightful research article titled “Assessing the Accuracy of Responses by the Language Model ChatGPT to Questions Regarding Bariatric Surgery” by Jamil S. Samaan et al. [1]. This study offers valuable perspectives on the use of ChatGPT for patient education in the context of bariatric surgery. However, we believe it is essential to highlight certain considerations and limitations to further enrich the discussion.

While ChatGPT presents a promising avenue for disseminating information, it raises ethical concerns regarding patient autonomy. Patients seeking information from AI models may inadvertently be influenced by the responses provided. As these responses are algorithmically generated, patients may not fully grasp the potential biases or limitations inherent in the AI model. Ensuring patients make informed decisions is paramount, and future research should delve into the ethical implications of AI-driven patient education. How can we empower patients to critically evaluate AI-generated information and engage in shared decision-making with healthcare providers?

ChatGPT’s responses are contingent on the phrasing of questions and may not adapt effectively to varying levels of health literacy or different languages. This could inadvertently exclude individuals with limited English proficiency or those who struggle with complex medical terminology [2]. Exploring strategies to enhance language inclusivity and accessibility is crucial to ensure that AI tools do not exacerbate healthcare disparities.

The deployment of AI models like ChatGPT in healthcare necessitates a robust regulatory framework. As these models evolve and gain prominence, questions regarding their classification as medical devices, liability in case of misinformation, and adherence to healthcare regulations become pertinent. Future research should engage with legal and regulatory experts to navigate these complex issues effectively.

The study highlights instances where ChatGPT provided incorrect information. While this underscores the need for caution, it also underscores the potential for continual model improvement. Research should explore strategies for real-time model refinement, such as feedback loops with healthcare professionals to correct inaccuracies promptly.

In conclusion, the study by Samaan et al. provides a critical foundation for the integration of AI models like ChatGPT into healthcare contexts. However, as we venture into this transformative territory, it is essential to address ethical concerns, enhance accessibility, establish a robust regulatory framework, and prioritize continual model improvement. These considerations will be instrumental in realizing the full potential of AI in patient education and care.