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

Abstract

<title>Abstract</title> 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-hour window. Responses were double-blinded and evaluated on relevance, clarity, depth, focus, and coherence by ten endometrial cancer experts. Our analysis revealed significant variations across different countries/regions (p &lt; 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p &lt; 0.05), excelling in all evaluation criteria (p &lt; 0.001). Bard also performed better in Nigeria compared to other regions (p &lt; 0.05), consistently surpassing them across all categories (p &lt; 0.001, with relevance reaching p &lt; 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p &lt; 0.001). These findings highlight concerning disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This underscores the need for further research and development to ensure equitable access to reliable medical information through AI technologies.

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