Skip to content
Search

Latest Stories

Top Stories

Medical Schools Are Falling Behind in the Age of Generative AI

Medical Schools Are Falling Behind in the Age of Generative AI

"To prepare tomorrow’s doctors, medical school deans, elected officials, and health care regulators must invest in training that matches the pace and promise of this technology," writes Dr. Robert Pearl.

Getty Images, ArtistGNDphotography

While colleges across the nation are adapting their curricula to harness the power of generative AI, U.S. medical schools remain dangerously behind.

Most students entering medicine today will graduate without ever being trained to use GenAI tools effectively. That must change. To prepare tomorrow’s doctors – and protect tomorrow’s patients – medical school deans, elected officials, and health care regulators must invest in training that matches the pace and promise of this technology.


Universities embrace AI as medical schools fall behind

Across the country, colleges and universities are reimagining how they educate students in the age of generative AI.

  • At Duke University, every new student receives a custom AI assistant dubbed DukeGPT.
  • At California State University, more than 460,000 students across 23 campuses now have access to a 24/7 ChatGPT toolkit.

These aren’t niche experiments. They’re part of a sweeping, systems-level transformation aimed at preparing graduates for a rapidly evolving workforce.

Most medical schools, however, have not kept pace. Instead of training students to apply modern tools toward clinical care, they continue to emphasize memorization — testing students on biochemical pathways and obscure facts rarely used in practice.

Early fears about plagiarism and declining academic rigor led many university departments to proceed cautiously after ChatGPT’s release in 2022. But since then, an increasing number of these educational institutions have shifted from policing AI to requiring faculty to incorporate GenAI into their coursework. And the American Federation of Teachers announced earlier this month that it would start an AI training hub for educators with $23 million from tech giants Microsoft, OpenAI, and Anthropic.

Medical education remains an outlier. A recent Educause study found that just 14% of medical schools have developed a formal GenAI curriculum, compared to 60% of undergraduate programs. Most medical school leaders and doctors still regard large language models as administrative aids rather than essential clinical tools.

This view is short-sighted. Within a few years, physicians will rely on generative AI to synthesize vast amounts of medical research, identify diagnostic patterns, and recommend treatment options tailored to the latest evidence. Patients will arrive at appointments already equipped with GenAI-assisted insights.

Used responsibly, generative AI can help prevent the 400,000 deaths each year from diagnostic errors, 250,000 deaths from preventable medical mistakes, and 500,000 deaths from poorly controlled chronic diseases. Elected officials and regulators need to support this life-saving approach.

How medical schools can catch up

In the past, medical students were evaluated on their ability to recall information. In the future, they will be judged by their ability to help AI-empowered patients manage chronic illnesses, prevent life-threatening disease complications, and maximize their health.

With generative AI capabilities doubling every year, matriculating medical students will be entering clinical practice equipped with tools over 30 times more powerful than today’s models. Yet few doctors will have received structured training on how to use them effectively.

Modernizing medical education starts with faculty training. Students entering medical school in 2025 will arrive already comfortable using generative AI tools like ChatGPT. Most instructors, however, will need to build that fluency.

To close this gap, academic leaders should provide faculty training programs before the start of the next academic year. These sessions would introduce educators to prompt engineering, output evaluation, and reliability assessment. These are foundational skills for teaching and applying GenAI in clinical scenarios.

Once faculty are prepared, schools would begin building case-based curricula that reflect modern clinical realities.

Sample Exercise: Managing chronic disease with GenAI support

In this scenario, students imagine seeing a 45-year-old man during a routine checkup. The patient has no prior medical problems, but on a physical exam, his blood pressure reads 140/100.

First, students walk through the traditional diagnostic process:

  • What additional history would they obtain?
  • Which physical findings warrant follow-up?
  • What laboratory tests would they order?
  • What treatment and follow-up plan would they recommend?

Next, they enter the same case into a generative AI tool and compare its output to their own. Where do they align? Where do they differ (and, importantly, why)?

Finally, students design a care plan that incorporates GenAI’s growing capabilities, such as:

  • Analyzing data from at-home blood pressure monitors.
  • Customizing educational guidance.
  • Enabling patients to actively manage their chronic diseases between visits.

This type of training – integrated alongside traditional curriculum – prepares future clinicians to master not just the technology but also understand how it can be used to transform medical care.

A call to government: Empower the next generation of physicians

Medical schools can’t do this alone. Because most physician training is funded through federal grants and Medicare-supported residency programs, meaningful reform will require coordinated leadership from academic institutions, government agencies, and lawmakers.

Preparing future doctors to use GenAI safely and effectively should be treated as a national imperative. Medicare will need to fund new educational initiatives, and agencies like the FDA must streamline the approval process for GenAI-assisted clinical applications.

This month, the Trump administration encouraged U.S. companies and nonprofits to develop AI training programs for schools, educators, and students. Leading tech companies — including Nvidia, Amazon, and Microsoft — quickly signed on.

If medical school deans demonstrate similar openness to innovation, we can expect policymakers and industry leaders to invest in medical education, too.

But if medical educators and government leaders hesitate, for-profit companies and private equity firms will fill the void. And they will use GenAI not to improve patient care but primarily to increase margins and drive revenue.

As deans prepare to welcome the class of 2029 (and as lawmakers face the growing costs of American health care), they must ask themselves:

Are we preparing students to practice yesterday’s medicine or to lead tomorrow’s?

Dr. Robert Pearl, the author of “ ChatGPT, MD,” teaches at both the Stanford University School of Medicine and the Stanford Graduate School of Business. He is a former CEO of The Permanente Medical Group.

Read More

Fox News’ Selective Silence: How Trump’s Worst Moments Vanish From Coverage
Why Fox News’ settlement with Dominion Voting Systems is good news for all media outlets
Getty Images

Fox News’ Selective Silence: How Trump’s Worst Moments Vanish From Coverage

Last week, the ultraconservative news outlet, NewsMax, reached a $73 million settlement with the voting machine company, Dominion, in essence, admitting that they lied in their reporting about the use of their voting machines to “rig” or distort the 2020 presidential election. Not exactly shocking news, since five years later, there is no credible evidence to suggest any malfeasance regarding the 2020 election. To viewers of conservative media, such as Fox News, this might have shaken a fully embraced conspiracy theory. Except it didn’t, because those viewers haven’t seen it.

Many people have a hard time understanding why Trump enjoys so much support, given his outrageous statements and damaging public policy pursuits. Part of the answer is due to Fox News’ apparent censoring of stories that might be deemed negative to Trump. During the past five years, I’ve tracked dozens of examples of news stories that cast Donald Trump in a negative light, including statements by Trump himself, which would make a rational person cringe. Yet, Fox News has methodically censored these stories, only conveying rosy news that draws its top ratings.

Keep ReadingShow less
U.S. Flag / artificial intelligence / technology / congress / ai

The age of AI warrants asking if the means still further the ends—specifically, individual liberty and collective prosperity.

Getty Images, Douglas Rissing

Liberty and the General Welfare in the Age of AI

If the means justify the ends, we’d still be operating under the Articles of Confederation. The Founders understood that the means—the governmental structure itself—must always serve the ends of liberty and prosperity. When the means no longer served those ends, they experimented with yet another design for their government—they did expect it to be the last.

The age of AI warrants asking if the means still further the ends—specifically, individual liberty and collective prosperity. Both of those goals were top of mind for early Americans. They demanded the Bill of Rights to protect the former, and they identified the latter—namely, the general welfare—as the animating purpose for the government. Both of those goals are being challenged by constitutional doctrines that do not align with AI development or even undermine it. A full review of those doctrines could fill a book (and perhaps one day it will). For now, however, I’m just going to raise two.

Keep ReadingShow less
An illustration of AI chat boxes.

An illustration of AI chat boxes.

Getty Images, Andriy Onufriyenko

In Defense of ‘AI Mark’

Earlier this week, a member of the UK Parliament—Mark Sewards—released an AI tool (named “AI Mark”) to assist with constituent inquiries. The public response was rapid and rage-filled. Some people demanded that the member of Parliament (MP) forfeit part of his salary—he's doing less work, right? Others called for his resignation—they didn't vote for AI; they voted for him! Many more simply questioned his thinking—why on earth did he think outsourcing such sensitive tasks to AI would be greeted with applause?

He's not the only elected official under fire for AI use. The Prime Minister of Sweden, Ulf Kristersson, recently admitted to using AI to study various proposals before casting votes. Swedes, like the Brits, have bombarded Kristersson with howls of outrage.

Keep ReadingShow less
shallow focus photography of computer codes
Shahadat Rahman on Unsplash

When Rules Can Be Code, They Should Be!

Ninety years ago this month, the Federal Register Act was signed into law in a bid to shine a light on the rules driving President Franklin Roosevelt’s New Deal—using the best tools of the time to make government more transparent and accountable. But what began as a bold step toward clarity has since collapsed under its own weight: over 100,000 pages, a million rules, and a public lost in a regulatory haystack. Today, the Trump administration’s sweeping push to cut red tape—including using AI to hunt obsolete rules—raises a deeper challenge: how do we prevent bureaucracy from rebuilding itself?

What’s needed is a new approach: rewriting the rule book itself as machine-executable code that can be analyzed, implemented, or streamlined at scale. Businesses could simply download and execute the latest regulations on their systems, with no need for costly legal analysis and compliance work. Individuals could use apps or online tools to quickly figure out how rules affect them.

Keep ReadingShow less