Few if any radiologists will be replaced by AI in 2025.
Mostly true True in substance, wrong in a detail.
Prediction: Statements about events outside the person's control, checked once they fell due: did they come true?
The second judge would not resolve this claim; the verdict shown is the first judge's.
What would count as true or false
A prediction for the end of 2025. True: by 31 Dec 2025, no or very few radiologists have actually been replaced by AI. That means no meaningful documented layoffs or eliminated radiologist positions attributed to AI, and workforce data (e.g., radiologist employment and demand figures, ACR or RCR workforce reports) show steady or growing demand. Mostly true: there are a handful of isolated reported cases of radiologist roles cut because of AI, but no aggregate decline. Mixed: there is some measurable, attributable reduction in radiologist roles in some systems or countries, but it is not widespread. Mostly false: a substantial number of radiologist positions are documented as replaced by AI. False: there is widespread documented replacement, with AI systems reading studies autonomously in place of radiologists at scale and radiologist employment falling as a result.
Set before the research began.
Evidence (4)
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E1 AI Didn’t Replace the Radiologist. It Replaced the Junior One - HKU Centre for AI, Management and Organization HKU Centre for AI, Management and Organization (CAMO) · 3 June 2026
“By using AI for first-round image reading and centralizing the remaining review into 16 regional centers with experienced specialists, it reduced the number of radiologists from 400 to 160 while maintaining the image volume and reading accuracy.”
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E2 AI Didn’t Replace the Radiologist. It Replaced the Junior One - HKU Centre for AI, Management and Organization HKU Centre for AI, Management and Organization (CAMO) · 3 June 2026
“Yet, a recent investigation published in 2025 in The New York Times reveals that the Mayo Clinic has increased its radiology staff by 55% in the past decade.”
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E3 AI isn't replacing radiologists Understanding AI (guest post by Deena Mousa, originally Works in Progress) · 1 October 2025
“But demand for human labor is higher than ever.”
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E4 2025 clinical radiology workforce census report | The Royal College of Radiologists The Royal College of Radiologists
“As our Fellows and members are acutely aware, there are growing shortfalls in clinical radiology.”
Reasoning
Independent sources point to strong and growing demand for radiologists. A 2025 analysis says demand for human labour is "higher than ever" (E3), the RCR's 2025 census reports growing shortfalls in clinical radiology (E4), and a New York Times report cited in E2 says Mayo Clinic grew its radiology staff by 55% over a decade. Against that, a university case study documents one organisation that reduced its radiologists from 400 to 160 after using AI for first-round image reading together with centralised review in 16 regional centres (E1). That is a single reduction at one organisation, and the material does not show whether it occurred by the end of 2025; the other evidence points to strong demand and shortfalls rather than a decline across the workforce (E2, E3, E4), which the report reads as fitting "mostly true".
Cite this claim
Gary Marcus, “Few if any radiologists will be replaced by AI in 2025.” (said 1 January 2025). Verdict: mostly true. Reliability API, claim c_d29fdd3ad695, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_d29fdd3ad695
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
More prediction claims by Gary Marcus
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Resolved true
“Less than 10% of the work force will be replaced by AI.”
Less than 10% of the workforce will be replaced by AI in 2025, probably less than 5%.
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Mostly true
“Some of its advice will be head-scratchingly bad.”
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Mostly true
“GPT-5 will surely be better, a lot better than GPT-4.”
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Resolved true
“GPT-5 really is about to drop, no foolin’.”
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Resolved true
“It will still make a significant number of shake-your-head stupid errors, in ways that are hard to fully predict.”
GPT-5 will still make a significant number of obvious errors that are hard to predict.
Verdicts are made automatically; how verdicts are made.