Groups release statement on ethical use of AI in radiology

Artificial intelligence has tremendous potential for increasing the efficiency and accuracy of radiology. However, the technology also has “inherent pitfalls and biases” that must be addressed.

That’s the contention of the American College of Radiology, European Society of Radiology, Radiological Society of North America, Society for Imaging Informatics in Medicine, European Society of Medical Imaging Informatics, Canadian Association of Radiologists and American Association of Physicists in Medicine—all of which jointly published a statement on the ethical use of AI in radiology.

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A technician looks at scanned imagery in the control room of the diagnostic imaging area at the Hong Kong Integrated Oncology Centre in Hong Kong, China, on Tuesday, Nov. 3, 2015. Equipped with biopsy facilities, body scanners, and quiet 'VIP' chemotherapy rooms, the Hong Kong Integrated Oncology Centre is the first of a string of such facilities that TE Asia Healthcare Partners, a portfolio company funded by TPG Capital, is planning in Asia. Photographer: Xaume Olleros/Bloomberg

“Widespread use of AI-based intelligent and autonomous systems in radiology can increase the risk of systemic errors with high consequence and highlights complex ethical and societal issues,” according to the international multi-society statement. “The radiology community should start now to develop codes of ethics and practice for AI that promote any use that helps patients and the common good and should block use of radiology data and algorithms for financial gain without those two attributes.”

The statement focuses on the ethical considerations of data, algorithms and practice. For each of those areas, the radiology organizations offered a list of questions that should be answered when an AI model is implemented.

According to the groups, the ethical use of AI in radiology should promote well-being and minimize harm. They also emphasize that it must ensure that benefits and harms are distributed among stakeholders in a just manner that respects human rights and freedoms, including dignity and privacy.

In addition, the statement proposes that AI in radiology be appropriately transparent and highly dependable, curtailing bias in decision making while ensuring that responsibility and accountability remain with human designers or operators.

“With the prospect of integration of AI into radiology research and clinical practice, it is incumbent upon the radiology community to develop codes of ethics and practice to guide the utilization of this powerful technology and ensure the privacy and safety of patients,” says co-author Matthew Morgan, MD, a member of the RSNA Radiology Informatics Committee and associate professor and director of IT and quality improvement in breast imaging in the Department of Radiology and Imaging Sciences at the University of Utah.

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