As artificial intelligence takes on a more prevalent role in radiology, many professionals hesitate to fully embrace the technology, with some believing legal burdens could outweigh its benefits.
In a recent editorial published in the American Journal of Roentgenology Jonathan L. Mezrich, MD, with the department of diagnostic radiology and biomedical imaging at the Yale School of Medicine, discussed the potential legal ramifications of integrating AI into daily radiologic practice and how practitioners should prepare.
“Formidable legal obstacles threaten AI’s impact on the specialty and, if unchanged, have the potential to preclude the future success of this emerging industry,” Mezrich said.
Mistakes in radiology, whether made by a human or an algorithm, are inevitable, the doctor suggests. But when mistakes lead to patient injuries patients have the right to seek restitution. This could come in the form of medical malpractice, vicarious liability and products liability.
When computer-aided detection systems are utilized as decision support tools by radiologists, Mezrich points out that the law then considers AI to be an instrument of the radiologist, rather than a colleague. Since the human reader ultimately makes the final determination in these cases, any mistakes made are legally tied to the radiologist.
“Laws relating to AI autonomy are not yet established; this uncertainty creates an inherent bias toward limiting AI’s role to that of a tool and holding the human user ─ the radiologist ─ primarily responsible,” the doctor explained.
Similar legal consequences could occur when AI acts as an assistant, rather than a tool. In this scenario, the radiologist would act as a supervisor who oversees the assistant. And similar to when human subordinates make an error, the supervisor is responsible for any adverse outcomes and the courts can designate a human being as the liable party.
But how does malpractice work when an autonomous algorithm is the party at fault? Mezrich notes that in these situations the facility hosting the algorithm would be responsible for any errors made on behalf of the AI, and that this would fall under “enterprise” liability, which is yet another legal consideration institutions must contemplate when integrating AI into daily practice.
“Legal complexities increase with an increase in autonomy,” the doctor discloses. “The legal hurdles and complexities are substantial and, depending on how they are handled, could lead to untapped technological potential.”
You can view the entire editorial here.
In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She joined Innovate Healthcare in 2021 and has since put her unique expertise to use in her editorial role with Health Imaging.