Is AI still scaring off medical students from picking radiology as a specialty? A new study in Academic Radiology found that while prospective radiology trainees don’t seem as worried as they were after radiology AI burst onto the scene in 2015, they still have concerns about how AI will affect the profession.
Radiology has long been seen as the medical specialty most at risk of broader AI adoption, largely because early AI applications focused primarily on image analysis.
- These fears led to a widely publicized dip in radiology residency applications after 2016, the year after IBM Watson debuted at the RSNA show and when AI guru Geoffrey Hinton, PhD, issued his famous advice to stop training radiologists.
But interest in radiology rebounded shortly after that. AI adoption was slower than anticipated, and few hospitals have proven willing to turn over radiologists’ duties to computers.
- Given the changes, how have the attitudes of medical students toward AI evolved in the last 10 years? Researchers decided to survey Canadian medical students and residents to find out.
In all, 401 respondents replied to the survey, of whom 13% had ranked radiology as their top specialty choice, with the following findings…
- Only 2.5% said AI was “extremely influential” in affecting their specialty choice, with 57% saying it had a “slight/moderate impact” and 35% stated “no impact.”
- AI was more important for those ranking radiology in their top three, with 91% saying AI influenced their decision compared to 54% of those uninterested in radiology.
- For those interested in radiology, 33% said AI made them feel discouraged, 13% were encouraged, and 33% reported no AI influence.
- Those who believed AI would reduce radiologist demand were 50% less likely to be interested in a radiology career.
How to interpret the results? The authors felt the findings showed that AI had either no influence or a slight/moderate effect on specialty choice, but the impact was greater in those who were interested in radiology.
- They also saw a “growing polarization” among trainees, in that while many viewed AI as a threat to their job security, some saw it as an opportunity for innovation.
The Takeaway
Medical students have complex and nuanced attitudes toward AI in radiology, as the new study indicates. But the findings suggest that past fears of radiology AI have evolved into a more measured view that better reflects real-world AI adoption.
