When medical algorithms underestimate minority patients’ pain

A closer look

Handing the ER clipboard to a computer comes with a terrifying dose of digitized prejudice. When hospitals deploy machine learning to triage incoming patients, models trained on historically biased healthcare data often systematically underestimate the severity of symptoms in minority groups. Instead of fixing human error, these algorithmic overlords mathematically lock in medical racism, quietly sending marginalized patients to the back of the waiting room while the software pats itself on the back for efficiency.