As AI Gets Smarter, Healthcare Education Must Get More Human

By Tamara Rozhon, EdD, Provost, Southern California University of Health Sciences

Artificial intelligence is going to transform healthcare. In many ways, it already has.

AI-enabled technologies are being used to detect and diagnose disease, analyze medical images, support clinical decisions, accelerate research, and make sense of enormous amounts of health data. The U.S. Food and Drug Administration now maintains an extensive list of AI-enabled medical devices authorized for marketing in the United States, and the World Health Organization describes AI as already playing a role in diagnosis and clinical care, drug development, disease surveillance, and health systems management.

For those of us responsible for educating the next generation of healthcare professionals, all of this raises an important question: If AI is changing what healthcare professionals can do, how should it change what and how we teach?

Health sciences education has historically placed enormous value on acquiring knowledge—and rightly so. You cannot be an excellent healthcare professional without knowing your field. But we are rapidly approaching a world in which information is no longer the scarce resource it once was. In an AI-enabled world, the challenge becomes knowing what to make of all the information at our fingertips. Is it relevant? Is the evidence sound? Could something be missing? Is an apparent pattern meaningful? Could it be biased? Does it raise any ethical considerations?

And, critically, does it make sense for my unique patient? The best healthcare requires not just understanding patient data, but understanding patients: their individual circumstances, preferences, goals, aspirations, and all the factors that may be supporting or hindering their health and well-being. At Southern California University of Health Sciences (SCU), this is at the heart of our Whole Health focus: preparing future healthcare professionals to understand the whole person, what matters most to them, and the many factors that shape their health and quality of life. I believe that this human side of care will become more—not less—important as technology grows more sophisticated.

What the blending of artificial and human intelligence looks like will surely vary across healthcare professions. At SCU, our programs span a wide range of conventional and complementary health disciplines, and we expect AI to affect each of them differently. For example:

• In genetics and genomics, researchers are already turning to AI and machine learning to uncover patterns in extraordinarily large and complex datasets—but scientists must still determine whether those patterns are valid and meaningful, and genetic counselors must engage in the profoundly human work of helping patients understand what the findings mean and navigate the potentially life-altering decisions that can follow.
• Physician Assistants are already using AI in clinical practice, with emerging applications ranging from documentation to clinical decision support—but PAs must still use their clinical judgment to evaluate that information in the context of the whole patient and determine what is appropriate for that individual.
• Physical Therapists are exploring AI’s applications for movement analysis, functional assessment, predicting outcomes, clinical decision support, and remote monitoring—but they must still determine what the data mean clinically and how to apply them to a patient’s unique condition, goals, and circumstances.
• Mental health professionals have begun using AI to support administrative tasks, clinical decision-making, and early detection of mental health concerns—but must still evaluate its validity and interpret it within the much more complex context of an individual’s experiences, behaviors, environment, and needs.
• Healthcare leaders are using AI across a range of administrative, financial, operational, and clinical functions—giving them powerful new tools to analyze information and improve performance, while leaving them responsible for weighing the evidence, exercising judgment, and considering how their decisions affect the health and well-being of patients and communities.

As AI becomes increasingly capable of generating, analyzing, and synthesizing information, we need to become much more interested in whether students can understand and critically evaluate it, recognize its potential for bias, error, and other ethical concerns, and apply it in the most human-centered ways possible. That means designing learning experiences and assessments that ask students not simply to produce an answer, but to question it, defend it, and make sound decisions in the context of a real human being. And it means designing clinical experiences that strengthen the distinctly human skills technology cannot replace: listening, empathy, communication, judgment, and connection. At SCU, this is why we believe our commitment to Whole Health is more important than ever; as technology becomes more capable, we must prepare healthcare professionals to use it without ever losing sight of the person it is meant to serve.

Perhaps the greatest challenge for health sciences education, then, is not keeping pace with artificial intelligence. It is developing the human intelligence required to use it well.