Brief discusses promise, pitfalls of AI use in reducing health disparities

Mitigating artificial intelligence algorithm biases in healthcare is possible with careful design and inclusive data collection; a diverse workforce; and centering ethical considerations, transparency and a collaborative approach, a KFF brief found. AI could be used to identify and correct real-time clinician bias and automate scheduling and billing, reducing staff burnout at safety-net hospitals, which disproportionately treat underserved groups. However, AI could perpetuate racial bias, increasing racial disparities in health outcomes. Research shows AI can result in longer wait times for appointments and under-diagnosis of health conditions for Black and Hispanic people. (KFF brief, 4/30/26)