At the intersection of technological optimism and structural inequality, researchers are raising a quiet but urgent warning: artificial intelligence, promoted as a remedy for longstanding disparities in women's health, may instead crystallize the very biases embedded in the medical systems that trained it. Published in npj Women's Health, their analysis reveals how machine learning models built on binary gender frameworks can launder flawed assumptions into the appearance of objective truth, while surveillance-driven health apps extract intimate data from vulnerable populations under the guise
AI in women's health risks encoding old biases without structural reform
Transgender, intersex, and gender-diverse people face disproportionate exposure to discriminatory medical practices and inadequate care, risks that AI adoption could worsen.