Accelerating health disparities research with artificial intelligence

Accelerating health disparities research with artificial intelligence

23 January 2024 | B. Lee Green, Anastasia Murphy, Edmondo Robinson
The article "Accelerating Health Disparities Research with Artificial Intelligence" by B. Lee Green, Anastasia Murphy, and Edmondo Robinson discusses the potential of artificial intelligence (AI) to address health disparities. Health disparities, which are rooted in systemic biases and structural inequalities, are a pressing issue that transcends professional boundaries. AI, with its ability to analyze large datasets and uncover hidden patterns, offers a transformative tool to dissect the multifactorial causes of these disparities. However, the authors also highlight several challenges, including data bias, the need for equitable algorithm design, diverse representation in AI development teams, ethical standards, and maintaining a human-centric approach in healthcare. They recommend inclusive data collection, ethical guidelines, diverse representation, and continuous oversight to ensure that AI is used effectively and responsibly to reduce health disparities and achieve health equity. The article calls for a collaborative effort to leverage AI's potential while addressing these challenges to create a more equitable healthcare system.The article "Accelerating Health Disparities Research with Artificial Intelligence" by B. Lee Green, Anastasia Murphy, and Edmondo Robinson discusses the potential of artificial intelligence (AI) to address health disparities. Health disparities, which are rooted in systemic biases and structural inequalities, are a pressing issue that transcends professional boundaries. AI, with its ability to analyze large datasets and uncover hidden patterns, offers a transformative tool to dissect the multifactorial causes of these disparities. However, the authors also highlight several challenges, including data bias, the need for equitable algorithm design, diverse representation in AI development teams, ethical standards, and maintaining a human-centric approach in healthcare. They recommend inclusive data collection, ethical guidelines, diverse representation, and continuous oversight to ensure that AI is used effectively and responsibly to reduce health disparities and achieve health equity. The article calls for a collaborative effort to leverage AI's potential while addressing these challenges to create a more equitable healthcare system.
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[slides and audio] Accelerating health disparities research with artificial intelligence