Global Big Data Conference

Can broader datasets help developers avoid accidentally perpetuating deep-rooted biases in vital institutions like healthcare and education? AI in healthcare has a bias problem. Last year, it came to light that six algorithms used on an estimated 60-100 million patients nationwide were prioritizing care coordination for white patients over black patients for the same level of illness. The algorithm was trained on costs in insurance claims data, predicting which patients would be expensive in the future based on who was expensive in the past. Historically, less is spent on black patients than white patients, so the algorithm ended up perpetuating existing bias in healthcare.