By Sara Gerke and Chloe Reichel
Recently, Google announced a new direct-to-consumer (DTC) health app powered by artificial intelligence (AI) to diagnose skin conditions.
The company met criticism for the app, because the AI was primarily trained on images from people with darker white skin, light brown skin, and fair skin. This means the app may end up over-or under-diagnosing conditions for people with darker skin tones.
This prompts the questions: How can we mitigate biases in AI-based health care? And how can we ensure that AI improves health care, rather than augmenting existing health disparities?