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Explore cultural bias in medical large language models through a focused research presentation examining how AI systems may perpetuate healthcare disparities across different cultural contexts. Learn about the methodology and findings from researchers Charles Nimo, Irfan Essa, and Michael Best as they investigate the performance of medical LLMs when applied to African healthcare scenarios. Discover the implications of cultural bias in AI-powered medical systems and understand the challenges of developing culturally sensitive healthcare technologies. Gain insights into the intersection of artificial intelligence, healthcare equity, and representation in AI systems through this 16-minute conference talk from the Association for Computing Machinery's session on Bias & Representation in AI Systems.
