Understanding AI Bias in Healthcare: Why Black Patient Must Educate Themselves

Artificial Intelligence (AI) is revolutionizing the healthcare sector, enhancing diagnostic precision, personalizing treatment strategies, and streamlining administrative operations. However, for Black patients, AI presents significant challenges that could deepen existing racial disparities in healthcare. The biases entrenched within AI algorithms can adversely affect diagnostics, treatment suggestions, and predictive modeling, resulting in misdiagnoses, inadequate care, and systemic disregard for the health requirements of Black individuals.AI technologies rely on historical patient data, which frequently reflect longstanding racial inequities. Research indicates that AI frameworks used to project healthcare requirements often disproportionately benefit white patients, mistakenly suggesting that Black patients need less medical attention based on historical expenditure trends. Furthermore, AI systems developed from predominantly white data struggle to provide accurate diagnoses for Black patients, particularly in fields such as dermatology and radiology. Consequently, rectifying these biases is crucial. Black patients should advocate for diversity in AI training datasets, demand transparency regarding AI operations, and actively engage in clinical trials to promote equitable healthcare advancements.