Large language models perpetuate racial bias in healthcare

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Large language models perpetuate racial bias in healthcare
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The tendency of four commercial LLMs to perpetuate race-based medical misconceptions.

By Vijay Kumar MalesuOct 24 2023Reviewed by Lily Ramsey, LLM In a recent study published in npj Digital Medicine, a group of researchers assessed the tendency of four commercial Large Language Models to perpetuate race-based medical misconceptions in healthcare through systematic scenario analysis.Background Recent research highlights the efficacy of LLMs in fields like cardiology, anesthesiology, and oncology, offering human-like responses to medical inquiries.

Analyzed LLMs included two versions each of Google's Bard, OpenAI's ChatGPT and GPT-4, and Anthropic's Claude, tested from May to August 2023. Each model's responses were reset after every question to prevent learning from repetition, focusing instead on their inherent response tendencies. Related StoriesNotably, almost all models correctly identified race as a social construct without a genetic basis. However, there were instances, like with Claude, where a model later contradicted this accurate information, referring to a biological basis for race.

Responses to questions about pain thresholds were mixed, with some models, like GPT-4, correctly denying any difference, while others, like Claude, propagated baseless race-based assertions. However, all models respond accurately to questions about racial disparities in brain size, often identifying the notion as harmful and racist.

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