---
title: "America’s Largest City Hospital System Ready to Start Replacing Radiologists With AI, Its CEO Says"
description: "The CEO of New York Health and Hospitals said he's ready to start replacing highly trained X-ray experts with AI as soon as it's legal."
date: "2026-04-04"
modified: "2026-04-04"
authors:
  - name: "Joe Wilkins"
    job_title: "Correspondent"
    link: "https://futurism.com/authors/jwilkins"
url: "https://futurism.com/artificial-intelligence/hospital-ceo-ai-radiology"
categories:
  - "Artificial Intelligence"
  - "Ethics"
  - "Health & Medicine"
  - "Medical"
  - "Treatments"
---

# America’s Largest City Hospital System Ready to Start Replacing Radiologists With AI, Its CEO Says

![A person lying down with their head secured in a medical device, featuring red laser lines projected across their scalp, likely for precise imaging or treatment. The individual is covered with a blue medical drape, and a healthcare professional is adjusting the device around the person's head. The setting appears clinical, with a focus on the head and laser alignment.](<https://futurism.com/wp-content/uploads/2026/04/hospital-ceo-ai-radiology.jpg>)
*Getty / Futurism*

Just weeks after the [largest nurses strike](<https://www.nysna.org/press/after-41-days-historic-nurse-strike-ends>) in New York City history, the CEO of NYC Health and Hospitals has a bold vision for a future where AI, not human radiologists, examines and diagnoses X-rays.

At a panel held by *Crain's New York Business*, Mitchell Katz, president and CEO of New York's 11-hospital public benefit corporation, made overt gestures of his desire to replace highly trained radiology experts with visual language AI models, [*Radiology Business* reported](<https://radiologybusiness.com/topics/artificial-intelligence/ceo-americas-largest-public-hospital-system-says-hes-ready-replace-radiologists-ai>).

"We could replace a great deal of radiologists with AI at this moment, if we are ready to do the regulatory challenge," Katz said at the panel.

One example he gave, according to *Radiology*, would affect women's healthcare in particular, by automating breast cancer screening with AI tools. By sidelining radiologists until an AI system flags a reading as abnormal, Katz declared, hospitals could achieve "major savings."

Mohammed Suhail, a radiologist at North Coast Imaging in San Diego, told *Radiology* that Katz's comments are "undeniable proof that confidently uninformed hospital administrators are a danger to patients," and are "easily duped by AI companies that are nowhere near capable of providing patient care."

"Any attempt to implement AI-only reads would immediately result in patient harm and death, and only someone with zero understanding of radiology would say something so naive," Suhail continued. "But in some sense, they're correct: hospitals are happy to cut costs even if it means patient harm, as long as it's legal."

Indeed, a growing body of research suggests that AI in the X-ray room is a disaster waiting to happen.

In a [yet-to-be-peer-reviewed study](<https://arxiv.org/abs/2603.21687>), Stanford researchers found that AI chest X-ray tools built on [frontier AI models](<https://hdsr.mitpress.mit.edu/pub/xdukxlpp/release/2>) can ace medical benchmark tests without ever seeing actual images of X-rays. Rather than admit that the images are missing, the highest scoring AI systems would engage in what amounts to a cheap parlor trick: constructing an elaborate explanation for findings on X-rays it never had access to in the first place.

This situation goes a step above mere AI hallucinations into what the researchers call an AI "mirage." Unlike the [generative AI errors](<https://futurism.com/artificial-intelligence/google-ai-overviews-dangerous-health-advice>) we've come to expect, the AI mirage is incredibly rational from start to finish. The issue is that these mirages aren't based on anything, meaning usual [hallucination safeguards](<https://www.wired.com/story/reduce-ai-hallucinations-with-rag/>) aren't enough to deter them.

"In this epistemic mimicry, the model simulates the entire perceptual process that would have led to the answer," the Stanford scientists wrote. "This helps explain why reasoning traces, on their own, cannot certify visual reasoning: the trace may be fluent, coherent, and apparently image-based while being anchored to no image at all."

On top of reinforcing previous research suggesting visual language AI models are [functionally blind](<https://anhnguyen.me/2024/vlms-are-blind/>), this study has major implications for any hospital turning to AI to trim its radiology unit — not to mention any patient unlucky enough to be on the receiving end of a medical imaging mirage.

**More on AI in healthcare:** *[ChatGPT Health Is Staggeringly Bad at Recognizing Life-Threatening Medical Emergencies](<https://futurism.com/future-society/chatgpt-health-bad-medical-emergencies>)*

## Author
At Futurism, I focus on the intersection of technology and power — examining the economics, history, and politics behind today’s dystopian headlines. As a writer, I’m interested in topics ranging from AI’s impact on labor to startups nobody asked for. My prior work includes bylines in Jacobin, Verso, and Blue Labyrinths. My work for Futurism has been cited by publications including Forbes, The Guardian, MIT Technology Review, Time, The Nation, Mother Jones, The Verge, and Wired. I grew up in Michigan, attending Central Michigan University as well as Ball State University, where I earned a master of music. I now live in Brooklyn with my girlfriend and our cat Ziti. On weekends, you can find me hunched over a cold pint arguing geopolitics with the other transplants.

### Author social links  
[Bluesky](<https://bsky.app/profile/joeonhere.bsky.social>)