Disparities in medical recommendations from AI-based chatbots across different countries/regions.

Gumilar, Khanisyah E.; Indraprasta, Birama R.; Hsu, Yu-Cheng; Yu, Zih-Ying; Chen, Hong; Irawan, Budi; Tambunan, Zulkarnain; Wibowo, Bagus M.; Nugroho, Hari; Tjokroprawiro, Brahmana A.; Dachlan, Erry G.; Mulawardhana, Pungky; Rahestyningtyas, Eccita; Pramuditya, Herlangga; Putra, Very Great E.; Waluyo, Setyo T.; Tan, Nathan R.; Folarin, Royhaan; Ibrahim, Ibrahim H.; Lin, Cheng-Han

This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-h window. Responses were evaluated in a double-blinded manner on relevance, clarity, depth, focus, and coherence by ten experts in endometrial cancer. Our analysis revealed significant variations across different countries/regions (p < 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p < 0.05), excelling in all evaluation criteria (p < 0.001). Bard also performed better in Nigeria compared to other regions (p < 0.05), consistently surpassing them across all categories (p < 0.001, with relevance reaching p < 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p < 0.001). These findings highlight disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This emphasizes the necessity for more research and development to guarantee equal access to trustworthy medical information through AI technologies.

Scientific Reports, 2024, Vol 14, Issue 1, p1

2045-2322

Academic Journal

10.1038/s41598-024-67689-0