The long road to fairer algorithms

An algorithm deployed across the United States is now known to underestimate the health needs of black patients1. The algorithm uses health-care costs as a proxy for health needs. But black patients' health-care costs have historically been lower because systemic racism has impeded their access to treatment -- not because they are healthier. This example illustrates how machine learning and artificial intelligence can maintain and amplify inequity. Most algorithms exploit crude correlations in data.