Most artificial intelligence applications focus on optimizing their predictions. However, machine learning algorithms should not be focused solely on accuracy but should be evaluated with respect to how they might impact disparities in patient outcomes. AI researchers must explore ways to reduce machine learning bias in healthcare or explain how to create algorithms that specifically alleviate inequalities

To prevent artificial intelligence (AI) from encoding the disparities that exist, algorithms should predict an outcome as if the world were fair.

If designed well, AI may even provide a way to audit and improve the way care is being delivered across populations. Otherwise, we risk these disparities becoming greater and greater.

To learn more about this topic, we recommend reading the article: Operationalising fairness in medical algorithms