By Trisha Nagin
Artificial Intelligence (AI) scribing technology has been praised as a revolutionary tool in modern healthcare. It can be seen as an answer to the long-standing problem of physician burnout caused by documentation. By listening in on doctor-patient conversations and generating clinical notes automatically, the technology is designed to save time, increase efficiency, and allow clinicians to focus more on patient care. But beneath the surface of this innovation lies an uncomfortable truth: in many hospitals, AI driven scribes could be quietly reshaping medical education.
For students, residents, and trainees, the process of writing notes isn’t just administrative work. It’s a core part of learning to be a healthcare provider. The act of translating clinical encounters into documentation is one of the ways medical trainees learn to organize their thoughts, prioritize information, and sharpen their diagnostic reasoning. Notes can be seen as reflections of a student’s clinical judgment and understanding, and when that process is handled by AI, the student’s role begins to shrink. Instead of writing, they observe. Instead of synthesizing, they skim. The educational opportunity is hollowed out in the name of efficiency. Students lose not only the chance to write, but the chance to listen. They can become passive observers in an environment where active engagement is supposed to be the foundation of their education.
The ethical implications are hard to ignore. Hospitals function as both care centers and learning environments. When efficiency-focused technologies diminish student learning opportunities, we must confront difficult questions: Who truly benefits from these systems, and which future generations of healthcare providers might be sacrificed in the process?
In fact, when observing the use of AI scribes from the core medical ethical framework, justice demands equitable access to opportunities within medicine, yet removing entry-level clinical roles disproportionately harms students who rely on these roles for both experience and income. This deepens existing inequities in education, privileging those with alternative forms of access. At the same time, non-maleficence, which is the obligation to do no harm, extends beyond patient care to include the developmental needs of future physicians. Replacing students with AI scribes may streamline physician workflow, but it deprives students of formative experiences essential to clinical reasoning, empathy, and communication. In prioritizing efficiency over education, hospitals risk doing unintentional harm by stunting the growth of future clinicians. Within teaching institutions, the ethical imperative must include safeguarding the spaces where learning and professional identity take root.
Additionally, the erosion of hands-on involvement in medicine carries profound consequences. Many aspiring medical professionals first enter healthcare as scribes, which are positions that typically don’t require certification, making them vital entry points into clinical experience. If AI eliminates these roles, students lose more than income; they lose irreplaceable opportunities to develop clinical instincts. These aren’t merely technical skills but habits of mind formed through consistent practice and reflection. Without this foundational experience, clinical reasoning development is compromised from the start.
Ultimately, the success of AI in healthcare will depend not only on what it can do, and how medical education can be reshaped and redirected in ways that are not replaced by AI. One critical area of growth is the integration of quality improvement (QI) training, not just for medical students and residents, but for undergraduates as well. By engaging undergraduates in QI initiatives, institutions can provide hands-on clinical experience that strengthens care delivery and supports overburdened clinical workflows. Involving students early in projects that streamline processes, reduce errors, and enhance patient outcomes fosters a generation of healthcare professionals who are systems-minded problem solvers. Another clinical opportunity lies in patient navigation, a component of value-based care. Students can serve as patient navigators to help guide individuals through complex healthcare systems, ensuring they receive timely and appropriate care.
AI scribes undoubtedly hold promise in reducing clinician burden and improving workflow efficiency. But in the rush to innovate, we must not lose sight of what is at stake: the training and development of the next generation of healthcare providers. Technology should enhance education, not eclipse it. The future of medicine depends not only on cutting-edge tools, but on the cultivation of thoughtful, well-trained, and empathetic clinicians. By investing in educational alternatives like quality improvement initiatives and patient navigation roles to name a few we can preserve essential learning opportunities while embracing the benefits of AI. The challenge is not choosing between efficiency and education, instead finding harmony between them. In doing so, we ensure that technological progress supports, rather than supplants, the growth of future healthcare providers.
Author: Trisha Nagin
Affiliation: Department of Medicine, UCLA Health, University of California, Los Angeles, CA
Competing Interests: None to declare