We and AI, PO Box 76297
© We and AI 2020
AI racial bias has extended directly into vital aspects of patient care. With greater rates of misdiagnosis and underdiagnoses of skin cancers in the non-white populations, this is a prime example of AI systems adding to the global burden of health disparities which significantly impact minority groups.
The solution to tackling poorer health outcomes due to AI bias comes down to training these systems using equal exposure to all patient populations (different skin types in the case of skin cancer detection). This will help improve the accuracy in providing diverse patient care using efficient health prediction and recognition technologies.