As artificial intelligence becomes more integrated into healthcare, questions about liability take center stage.
Instead of sitting behind a laptop during patient visits, the pediatrician directly faces the patient and parent, relying on an ambient artificial intelligence scribe to capture the conversation for the electronic health record . A geriatrician doing rounds at the senior living facility plugs each patient’s medications into an AI tool, checking for drug interactions.
Narrow AI can improve diagnostic speed and accuracy for other specialties, too, including dermatology and ophthalmology, Pearl said. “It’s less clear to me if it will be very beneficial in primary care, neurology, and psychiatry, areas of medicine that involve a lot of words.” In those specialties, some may use generative AI as a repository of resources. In clinical practice, ambient AI is also used to create health records based on patient/clinician conversations.
Generative AI can provide ideas. Pearl shared a story about a surgeon who was unable to remove a breathing tube that was stuck in a patients’ throat at the end of a procedure. The surgeon checked ChatGPT in the operating room, finding a similar case. Adrenaline in the anesthetic restricted the blood vessels, causing the vocal cords to stick together. Following the AI information, the surgeon allowed more time for the anesthesia to diffuse.
Some, including Pearl, believe AI will actually lower the malpractice risk. Having more data points to consider can make doctors’ jobs faster, easier, and more accurate. “I believe the technology will decrease lawsuits, not increase them,” said Pearl.: Providers should understand the tool they’re deploying, what it provides, how it was built and trained , how it was tested, and the guidelines for how to use it or not use it, said Srivastava. Evaluate each tool, use case, and risk separately.
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