The use of artificial intelligence and machine learning (AI/ML) in healthcare may improve patient care and health outcomes but also brings risks that should worry providers, McGuireWoods associates Allyson Maur and Micaela Enger wrote in the November 2024 edition of Chicago Medicine.
Maur and Enger cited implicit and explicit bias in the data used to train AI/ML models, patient privacy risks, and an overreliance on AI/ML in making clinical decisions as serious issues that government regulators and healthcare providers must address. Patients already use AI/ML to access health information and providers can feel pressure to order unnecessary tests and procedures "because 'Dr. ChatGPT' suggested a rare and unlikely condition," the authors noted.
"[A]s pressure to use AI/ML in healthcare delivery increases, stakeholders and regulators must continue their efforts to balance the risks and benefits while remaining focused on providing care with a human touch," the authors wrote.
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