20 October 2025
Doctors share top concerns of AI surrogates aiding life-or-death decisions.
For more than a decade, researchers have wondered whether artificial intelligence could help predict what incapacitated patients might want when doctors must make life-or-death decisions on their behalf.
It remains one of the most high-stakes questions in health care AI today. But as AI improves, some experts increasingly see it as inevitable that digital “clones” of patients could one day aid family members, doctors, and ethics boards in making end-of-life decisions that are aligned with a patient’s values and goals.
Ars spoke with experts conducting or closely monitoring this research who confirmed that no hospital has yet deployed so-called “AI surrogates.” But AI researcher Muhammad Aurangzeb Ahmad is aiming to change that, taking the first steps toward piloting AI surrogates at a US medical facility.
“This is very brand new, so very few people are working on it,” Ahmad told Ars.
Ahmad is a resident fellow working with trauma department faculty at the University of Washington’s UW Medicine. His research is based at Harborview Medical Center in Seattle, a public hospital in the UW Medicine health system. UW Medicine is integrated with “one of the world’s largest medical research programs” to pursue its mission of improving public health outcomes, UW’s website says.
UW wasn’t specifically seeking a fellow to experiment with AI surrogates, Ahmad told Ars. But since his project proposal was accepted, he has spent most of this year “in the conceptual phase,” working toward testing the accuracy of AI models based on Harborview patient data.
The main limitation of this testing, Ahmad said, is that he can only verify the accuracy of his models if patients survive and can later confirm that the model made the right choice. But this is just the first step, he said. The accuracy testing could then expand to other facilities in the network, with the aim of developing AI surrogates that can accurately predict patient preferences about “two-thirds” of the time.
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