A professor from University of Rochester (N.Y.) Medical Center said he's worried that sophisticated, costly AI systems would only be implemented in high-resource hospitals, enhancing results for patients who are already relatively well-off.
Jonathan Herington, PhD, assistant professor of health humanities and bioethics at URMC, said AI medical devices are undergoing training using datasets that lack proper representation of Latino and Black patients, according to an Oct. 19 news release from URMC.
Dr. Herington is a member of the AI Task Force of the Society for Nuclear Medicine and Medical Imaging, which recently published recommendations in the Journal of Nuclear Medicine on how to ethically develop and use AI in medicine.
"A concern is that these high-tech, expensive systems would be deployed in really high-resource hospitals, and improve outcomes for relatively well-advantaged patients, while patients in under-resourced or rural hospitals wouldn't have access to them — or would have access to systems that make their care worse because they weren't designed for them," he said.
This implies that the devices may exhibit reduced accuracy when making predictions for individuals from these groups.
"The systems are becoming ever more powerful all the time and the landscape is shifting really quickly," Dr. Herington said. "We have a rapidly closing window to solidify our ethical and regulatory framework around these things."