By KIM BELLARD
It took some time for the news to percolate to me, but last month the University of Texas San Antonio announced that it was creating the “nation’s first dual program in medicine and AI.” That sure sounds innovative and timely, and there’s no question that medical education, like everything else in our society, is going to have to figure out how to incorporate AI. But, I’m sorry to say, I fear UTSA is going about it in the wrong way.
UTSA has created a five year program that will result in graduates obtaining an M.D. from UT Health San Antonio and a Master of Science in Artificial Intelligence (M.S.A.I.) from UTSA. Students will take a “gap year” between the third and fourth year of medical school to get the M.S.A.I. They will take two semesters in AI coursework, completing a total of 30 credit hours: nine credit hours in core courses including an internship, 15 credit hours in their degree concentration (Data Analytics, Computer Science, or Intelligent & Autonomous Systems) and six credit hours devoted to a capstone project.
“This unique partnership promises to offer groundbreaking innovation that will lead to new therapies and treatments to improve health and quality of life,” said UT System Chancellor James B. Milliken.
“Our goal is to prepare our students for the next generation of health care advances by providing comprehensive training in applied artificial intelligence,” said Ronald Rodriguez, M.D., Ph.D., director of the M.D./M.S. in AI program and professor of medical education at the University of Texas Health Science Center at San Antonio. “Through a combined curriculum of medicine and AI, our graduates will be armed with innovative training as they become future leaders in research, education, academia, industry and health care administration. They will be shaping the future of health care for all.”
Dhireesha Kudithipudi, a professor in electrical and computer engineering who was tasked with helping develop the university’s AI curriculum, told Preston Fore of Fortune:
In lots of scenarios, you might see AI capabilities are being very exaggerated—that it might replace physicians and so forth. But I think our line of inquiry was guided in a different way, in a sense how we can promote this AI physician interaction-AI patient interaction, bringing humans to the center of the loop, and how AI can enhance care or emphasize more patient centric attention.
OK, fabulous. But, you know, computers have been integral to healthcare for decades, especially the past 15 years (due to EMRs), and we don’t expect doctors to get Masters in Computer Science. We’re just happy when they can figure out how to navigate the interfaces.
To be honest, I was expecting more from UT.
Last January I wrote about how they were doing an online M.S.A.I., creating what they said “will be the first large-scale degree program of its kind and the only master’s degree program in AI from a top-ranked institution to be priced close to $10,000.” It didn’t even require an undergraduate degree. That, I said at the time, was the kind of thinking medical schools should be doing.
But, instead, UTSA has made the medical school experience longer and more expensive, even though the U.S. medical education system is perhaps the longest and most expensive in the world. No other country leaves its new doctors with such staggering medical school debt. So, yeah, let’s add a year and another degree’s cost to that process.
Don’t get me wrong: I’m as big an advocate of AI in healthcare as you’ll find, and medical school is no exception. I’ll give UTSA credit for doing something about AI; I just don’t think they’ve really seized the moment. I fear they’re trying to be relevant to the present instead of preparing to jump to the future.
Right now, medical educators need to be thinking: what does the practice of medicine look like in an AI world? What will those doctors need to know, what will they need to know how to do, and what can they expect their various AI to do for them/assist them with? Those aren’t questions that any of us really know the answers to, but even current results with AI indicate that it is going to be immensely helpful. It will know more, what it knows will be more current, and it will be able to sift through masses of data to produce cogent summaries and recommendations. Doctors in 2040, perhaps even 2030, won’t know how they ever got along without it.
So medical education needs to change just as radically. Medical school should be shorter. It should focus much less on memorization than on where to find and apply answers. It should teach students how and when to rely on AI, and how to make that collaboration most productive. Forget the stethoscopes and medical flashlights; doctors are going to be “carrying around” AI first and foremost. Similarly, VR and AR are going to be ubiquitous.
Practicing medicine in 2030 is going to be much different than practicing even in 2020 was, and practicing in 2040 or 2050 – well, I don’t think our 20th century medical schools are preparing themselves or their students for that.
People like Charles Prober, M.D. have been advocating for over ten years for “lectures without lecture halls” – a.k.a “a flipped classroom model” — in which memorization is emphasized less, and “in which students absorb an instructor’s lecture in a digital format as homework, freeing up class time for a focus on applications.” Medical schools have been slow to adopt those ideas, so I’m not expecting they’ll be quick to jump on how to revolutionize themselves via AI. But they need to — or be superseded by entities that do.
I’ve been calling for a new Flexner Report for years now. Medical education isn’t working for doctors and it’s not working for patients. We have way too many types of medical education, not the least of which is the now meaningless distinction between M.D. and D.O., and they all take too long, cost too much, yet don’t adequately prepare graduates for the world or the healthcare system in which they’ll be delivering care. Now add AI to that mix…
The beginning of the 21st century would have been a good time to rethink medical education from first principles, but AI now puts us on the precipice of societal change that makes such a reformation not just overdue but essential.
Kim is a former emarketing exec at a major Blues plan, editor of the late & lamented Tincture.io, and now a regular THCB contributor.