Health Care AI Systems Are Biased
We need more diverse data to avoid perpetuating inequality in medicine.
This article explains how bias in AI systems is contributing to the exacerbation of racial health disparities. There is a huge issue with the misrepresentation of our data sets, which could result in health systems that do not correctly identify nor treat illnesses in non-white patients. For example, skin-cancer detection algorithms trained on light-skinned individuals, and x-rays trained with gender imbalanced data. It calls for diversity not only within our data sets, but also diversity among the developers and funders of AI tools. High-quality data and diversity training is needed to eliminate biases within the healthcare system.
