BECOMING a huge AI cheerleader probably wasn’t on your 2026 bingo card.
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BECOMING → become → card
But there was Kennedy on Tuesday, speaking in his capacity as the secretary of health and human services, talking about the potential of artificial intelligence to help pinpoint what’s wrong with people when they are sick or injured.
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they → be → people
“It would be malpractice for a doctor to make a diagnosis, or to make a prescription, without at least checking AI,” Kennedy said at a MAHA Action conference in Washington.1
MAHA, of course, stands for “Make America Healthy Again,” the movement that Kennedy has been leading, which is known for its hostility to all things artificial.
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which → make → things
But Kennedy doesn’t see AI as yet another way for science to disrupt the natural order.
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science → see → order
Rather, he said to the MAHA attendees, AI will let average people challenge the establishment of doctors and scientists, and make up their own minds about what constitutes good medical care.
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what → say → care
As an example, Kennedy suggested how people could have used AI during the COVID pandemic, when public health officials promoted vaccination as a way to protect the elderly and others with weaker immune systems.
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officials → suggest → systems
“If somebody tells you that a vaccine will prevent transmission and infection, or you need to take it to protect your grandmother, AI may say it actually doesn’t do that,” Kennedy said.
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Kennedy → tell → that
Or to put it more bluntly, as Kennedy did later, AI would “free us from medical tyranny.”
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AI → put → tyranny
It might surprise you to hear I think Kennedy is right about the potential of AI to transform medicine, and in a good way.
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Kennedy → surprise → way
Some of the most promising possible uses of AI—assuming it doesn’t, you know, extinguish humanity—lie in its ability to help providers make more accurate diagnoses.
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providers → assume → diagnoses
The immense value of AI systems in making diagnoses in fields where they can be trained on enormous datasets has been widely recognized over the past few years; for example, in diagnostic imaging, by training on vast numbers of x-rays, CT scans, MRIs, and ultrasounds, AI systems can detect diagnostic patterns too subtle or complex for even experienced clinicians to detect consistently.
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clinicians → make → patterns
The potential value of AI is also growing in fields like cancer treatment, where the sheer volume of relevant clinical information is so great—and changing so quickly—that even the most capable oncologists can’t keep it all in their heads.
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oncologists → grow → heads
“The data are pretty good that AI is more accurate than physicians at creating a differential diagnosis,” Ezekiel Emanuel, the University of Pennsylvania oncologist, bioethicist, and author, told me over email.
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Emanuel → create → email
He and two collaborators recently generated some controversy by suggesting in a Journal of the American Medical Association article that medical decision-making by AI alone was frequently superior to decision-making by doctors who merely consult AI.
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who → generate → AI
But, Emanuel told me, you don’t even have to believe that to see the upside potential.
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you → tell → potential
“In many cases there is not going to be a need to check with AI,” Emanuel said.
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Emanuel → be → AI
All physicians have had ‘tough cases’ that do not exactly fit with symptoms or lab tests that puzzle them.”
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that → have → them
AI could also boost health care by operating as a force multiplier: It can enable professionals without the full training of a doctor to provide front-line medical care in places where doctors are in short supply.
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doctors → boost → supply
Experts have talked for years about tapping that potential as a way to help some of the most impoverished parts of the world—or even impoverished parts of the United States.
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Experts → talk → States
And in the past few months, Mehmet Oz, administrator of the Centers for Medicare and Medicaid Services, has been touting AI’s potential as a way to address provider shortages in rural areas.
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Oz → tout → areas
The reason AI can do all of that is that it excels at gathering, digesting, and applying information—including scientific data.
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it → do → data
And this characteristic makes it useful for debunking charlatans, cranks, and conspiracy theorists, including those peddling unfounded claims about the dangers of vaccines.
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it → make → vaccines
In other words, it’s a terrific fact-checker for Kennedy, as I discovered myself last week.
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I → ’ → myself
INSPIRED BY HIS CALL TO USE AI, I went ahead and asked Claude (Anthropic’s AI assistant) to analyze some of Kennedy’s more memorable statements.
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I → inspire → statements
I used the professional, paid version, because it provides access to more capable AI models that can produce more accurate results, and I started with one of Kennedy’s favorite claims: that the scientific community hasn’t seriously investigated links between vaccines and autism.
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community → use → vaccines
Kennedy has cited this alleged failing to justify his agenda of unwinding federal support for vaccines.
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Kennedy → cite → vaccines
A version of the statement now even appears on the website of the Centers for Disease Control and Prevention.
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version → appear → Control
To get an accurate read on it, I fed Claude a recent version of Kennedy’s linkage between vaccines and autism—one he gave just a few weeks ago during a speech to Children’s Health Defense, the organization that he led from 2015 to 2023 and that has done as much as any to undermine faith in vaccines.
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that → get → vaccines
Here was the quote, which refers to eighteen vaccines the CDC has been recommending for children:
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CDC → refer → children
We have no idea what the risk profile is for these products.
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profile → have → products
And you know that means we can’t really make the kind of risk-benefit analysis that my agency is supposed to do.
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agency → know → that
Claude’s verdict:
The first misleading claim was on the number of doses (which Kennedy inflated).
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Kennedy → inflate → which
The second was about the supposed lack of placebo testing, which Kennedy says all the time and which—as infectious-disease experts like Stanford University’s Jake Scott have noted repeatedly—is simply not true.
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experts → suppose → Scott
As for the third claim, that “there was no safety study,” here’s Claude’s take:
This is the most clearly false part, and it goes further than the placebo claim.
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it → be → claim
Head-to-head trials against existing vaccines collect safety data, and so does post-licensure surveillance.
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surveillance → exist → data
The HHS website itself says every authorized or approved vaccine goes through safety testing, including clinical trials and monitoring after reaching the market.
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vaccine → say → market
The 2013 [Institute of Medicine] report on the schedule, which Kennedy cited in this same speech, found no evidence that the schedule is unsafe.
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schedule → cite → evidence
The kernel of truth in Kennedy’s argument (which Claude duly noted) is that scientists don’t typically test new versions of old vaccines against placebos.
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scientists → note → placebos
They test new vaccines against the existing vaccines.
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They → test → vaccines
As Claude went on to say, that’s because testing against a placebo in those cases would be unethical—you’d be knowingly exposing children to a dangerous, potentially deadly disease like measles—and is unnecessary because studies have already shown the original vaccine to be safe.
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vaccine → go → measles
…and 45 more, not listed.
The Aporia
