Guidance on Ethics of Artificial Intelligence in Radiology
The radiology community should act right away to develop codes of ethics for artificial intelligence (AI), the authors of a consensus statement urge.1
“AI raises novel ethical challenges,” says Raym Geis, MD, FACR, the paper’s lead author and a clinical adjunct associate professor of radiology at National Jewish Health.
The authors of the statement were concerned that ethical guidelines are lagging behind the progress AI has made in the field of radiology. “We wanted to start what we hope will become a rich discussion of ethics of AI in radiology. We will likely be interfacing with AI in our daily practice in the near future,” Geis explains. Many people on the clinical side of radiology ask questions about how AI can be used in ways that put patients first.
“One concern is that benefits and potential harms are distributed equally across all populations,” Geis notes.
He gives this example: An AI tool is used to diagnose tuberculosis on chest X-rays. “You train it for the U.S., and it works well for people here,” Geis says. However, in a developing country with more patients presenting with significant HIV and low T4 counts, many may have florid TB without typical findings on X-ray. Therefore, the AI may call it normal.
AI also could be used to predict who will not show up to undergo their CT scan. Then, clinics could send a rideshare service to pick up the patient. “But what if instead you double-book that appointment time? Then, if the patient actually does show up, they’ll have to wait,” Geis says.
Data privacy for medical images is another example. “There are no standards for how to de-identify medical images as much as possible,” Geis observes. “Techniques are still evolving for how to accomplish that.”
The statement is not prescriptive about regulation or codes of conduct, or how ethical practice actually will be ensured. “It will probably be a combination of federal regulation, educating the public as well as clinical and technical participants, and placing as many barriers as possible against unethical behavior,” Geis predicts.
REFERENCE
- Geis JR, Brady AP, Wu CC. Ethics of artificial intelligence in radiology: Summary of the Joint European and North American multisociety statement. J Am Coll Radiol 2019;16:1516-1521.
The authors of a consensus statement urge the radiology community to act right away to develop codes of ethics for artificial intelligence.
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