AI in medicine needs to be carefully deployed to counter bias – and not entrench it

https://www.npr.org/sections/health-shots/2023/06/06/ [login to see] /artificial-intelligence-racial-bias-health-care
Doctors, data scientists and hospital executives believe artificial intelligence may help solve what until now have been intractable problems. AI is already showing promise to help clinicians diagnose breast cancer, read X-rays and predict which patients need more care. But as excitement grows, there's also a risk: These powerful new tools can perpetuate long-standing racial inequities in how care is delivered.

"If you mess this up, you can really, really harm people by entrenching systemic racism further into the health system," said Dr. Mark Sendak, a lead data scientist at the Duke Institute for Health Innovation.

These new health care tools are often built using machine learning, a subset of AI where algorithms are trained to find patterns in large data sets like billing information and test results. Those patterns can predict future outcomes, like the chance a patient develops sepsis. These algorithms can constantly monitor every patient in a hospital at once, alerting clinicians to potential risks that overworked staff might otherwise miss.