AI Chatbots Impacting Healthcare: Racism Concerns

November 6, 2023

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"AI Chatbots Impacting Healthcare: Racism concerns"

by Garance Burke and Matt O'Brien

Published on

TechXplore

AI in Healthcare Art

Key Takeaways

  • A new study by Stanford researchers warns that popular chatbots powered by AI perpetuate racist medical ideas.
  • These chatbots, such as ChatGPT and Google's Bard, responded with misconceptions and falsehoods about Black patients, reinforcing harmful stereotypes.
  • This could worsen health disparities for Black patients and amplify medical racism.
  • The chatbots failed to respond accurately to medical questions about kidney function, lung capacity, and skin thickness.
  • Experts are concerned about the real-world consequences of these inaccuracies and the impact on health disparities.
  • Medical professionals increasingly use chatbots for daily tasks, and some patients rely on them for self-diagnosis.
  • Both OpenAI and Google have stated that they are working to reduce bias in their models and emphasize that chatbots are not a substitute for medical professionals.
  • AI models have potential in healthcare settings, but ethical implementation and addressing biases are crucial.

Summary of "AI Chatbots Impacting Healthcare: Racism concerns"

A study led by Stanford researchers cautions that popular AI-powered chatbots perpetuate racist medical ideas, which could worsen health disparities for Black patients. These chatbots, such as ChatGPT and Google's Bard, responded with misconceptions and falsehoods about Black patients, reinforcing harmful stereotypes. The study found that the chatbots failed to accurately answer medical questions about kidney function, lung capacity, and skin thickness. Experts are concerned about the real-world impact of these inaccuracies on health disparities and medical racism. While some medical professionals use chatbots for daily tasks, it is essential to note that they are not a substitute for medical professionals. OpenAI and Google have stated that they are working to reduce bias in their models. Ethical implementation and addressing biases are crucial for successfully using AI in healthcare settings.

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