“To Be or Not to Be a Doctor"

Authored by: Mary Wall

Art by: Alex Song

1. Introduction.

There’s an age-old adage that goes something like “a new AI development a day, keeps future doctors away.” In a recent episode of Peter Diamandis’ Moonshots podcast, Elon Musk boldly claimed that attending medical school three years from now is “pointless,” implying that artificial intelligence will soon eclipse the need for human physicians. As an undergraduate aspiring to attend medical school, I found this rather concerning. So, I thought I would do my due diligence as a pre-med writer for this journal and investigate the claim myself. Is a future career in medicine truly “pointless”?

2. Current AI Capabilities.

The impact of artificial intelligence on healthcare is undeniable. Today, AI systems can interpret radiologic images with near-expert accuracy, flag subtle abnormalities in pathology slides, predict patient deterioration through continuous vital-sign monitoring, and optimize treatment pathways using vast datasets that exceed human cognitive capacity [1]. Machine-learning models already assist in cancer detection, cardiac risk stratification, and population-level disease forecasting.

AI excels at identifying patterns before disease manifests, tailoring interventions to individual risk profiles, and providing patients with data-driven insights. Yet, medicine has never been solely about pattern recognition [2]. 

In the past few decades, as telehealth gained popularity, people feared it would completely alter the nature of medicine: in-person visits would cease, and virtual visits would become the norm. While telehealth has expanded access to healthcare for underrepresented or at-risk groups, reduced unnecessary emergency room visits, and saved patients time and money, it has not prevented physicians from providing traditional care.

Studies have shown that certain telehealth visits may be insufficient. For instance, in situations such as a patient’s first visit to a physician, a visit that requires conversational nuance from the physician, or a hands-on clinical assessment, telehealth is considered inappropriate [3]. But even more than “hands-on” clinical assessment, just plain and simple physical observation is a tenet of standard medical practice. In “The power of observation in clinical medicine”, Dr. Fabrizia Faustinella shares a case in which a patient complained of fatigue, weight loss, and abdominal pain [4]. The possible sources of these ailments are wide-ranging. Dr. Faustinella diagnosed the patient with adrenal insufficiency. What led her to this conclusion? Her first clue was hyperpigmentation in the patient’s knuckles.

Furthermore, researchers conducted an observational study examining how findings from the physical examination influenced the course of patient care [5]. After reviewing one hundred cases, they found that twenty-six patients had pivotal findings. Seven of these were classified as Class I findings, meaning they were critical observations that directly affected diagnosis or management. These examples illustrate that what clinicians directly observe informs how they apply their clinical knowledge to each patient.

3. Role of a Physician

In What Does It Mean to Be a Physician?, Dr. Thomas Schwenk describes medicine as the unification of science and humanism for the benefit of patients [6]. Artificial intelligence is extraordinarily well-suited for the scientific half of that equation. But humanism, which involves moral judgment, empathy, trust, and responsibility, cannot be automated [7]. 

Medicine is not practiced in controlled environments with perfect inputs. Patients are complex, frightened, inconsistent, and often present ambiguously. They withhold information. They contradict themselves. Identifying the most accurate intervention does not always answer whether or how it should be applied [8]. 

It is also worth remembering that the foundational sciences that pre-medical students study, such as chemistry, biology, and physics, are the very disciplines that enable these technological advances. AI does not emerge in isolation; it is built, trained, validated, and constrained by human expertise. If humans are the architects of artificial intelligence, they must remain stewards of its use.

This is especially true in a field where the stakes are existential. In standard consumer technology, failure is inconvenient. In medicine, failure can be fatal [9]. Regulatory frameworks such as FDA approval, malpractice liability, and ethical oversight exist precisely because healthcare demands accountability [10]. When things go wrong, as they inevitably will, patients want a responsible, well-trained professional, not a black-box system, to be accountable for decisions made [11]. 

Consider this: would you feel comfortable boarding a pilotless commercial flight? Even if autonomous systems outperform humans under ideal conditions, most of us still want a trained pilot in the cockpit when turbulence hits. Medicine is no different [12]. 

4. Conclusion

The future of healthcare is not physician versus AI. It is physicians with AI. Artificial intelligence can take over routine tasks such as charting and data analysis, allowing physicians to devote their time to clinical judgment, patient communication, and the uniquely human aspects of care that technology cannot replace. Far from making doctors obsolete, AI will raise expectations for what physicians must be able to do [13].  

In fact, this may be the most exciting time in history to pursue medicine. We are on the cusp of curing diseases once thought untreatable, personalizing treatments with unprecedented precision, and shifting healthcare from reactive to preventive [14].  So to the pre-meds enduring the pain that is Cornell chemistry and wondering if their effort will matter, don’t fret. As long as people care deeply about their health and that of those they love, there will be a need for thoughtful, compassionate, and well-trained physicians.

References

1. Dai, J., Xu, H., Chen, T., et al. (2025). Artificial intelligence for medicine 2025: Navigating the endless frontier. The Innovation Medicine, 3, 100120.

2. Sooknanan, J., & Seemungal, T. (2019). Not so elementary—the reasoning behind a medical diagnosis. Medical Education Projects, 8. https://doi.org/10.15694/mep.2019.000234.1

3. Cole, T. R., Crooks, V. A., Sorensen, J., et al. (2025). “Nothing is going to replace an in-person visit”: Canadian long-term care providers’ and recipients’ perspectives on when telehealth for physician visits is not appropriate. BMC Digital Health, 3, 77. https://doi.org/10.1186/s44247-025-00219-8

4. Faustinella, F. (2020). The power of observation in clinical medicine. International Journal of Medical Education, 11, 250–251. https://doi.org/10.5116/ijme.5fb9.1c9b

5. Reilly, B. M. (2003). Physical examination in the care of medical inpatients: An observational study. The Lancet, 362(9390), 1100–1105. https://doi.org/10.1016/S0140-6736(03)14464-9

6. Schwenk, T. L. (2020). What does it mean to be a physician? JAMA, 323(11), 1037–1038. https://doi.org/10.1001/jama.2020.014

7. Reeves, K. A. (2025). Updating the definition for humanism in healthcare: Kind, safe, and trustworthy. SAGE Open Medicine. https://doi.org/10.1177/23743735251340506

8. Li, Y., Jie, X., Ruan, W., Zhang, X., Zhu, H., Gao, Y., Du, C., & Liu, R. (2026). Beyond idealized patients: Evaluating LLMs under challenging patient behaviors in medical consultations. arXiv preprint. https://doi.org/10.48550/arXiv.2603.29373

9. Sears, R. (2025). Artificial intelligence in healthcare: No longer optional but neither is patient safety. American Journal of Healthcare Strategy, 1(3), 1–10. https://doi.org/10.61449/ajhcs.2025.15

10. Jost, T. S. (1988). The necessary and proper role of regulation to assure the quality of health care. Houston Law Review, 25, 525–558.

11. Riedl, R., Hogeterp, S. A., & Reuter, M. (2024). Do patients prefer a human doctor, artificial intelligence, or a blend, and is this preference dependent on medical discipline? Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1422177

12. Ong, A. Y., Merle, D. A., Pollreisz, A., Wagner, S. K., Sevgi, M., Keane, P. A., Huemer, R., Oehling, J., Jäger, M., & Huemer, J. (2026). Flight rules for clinical AI: Lessons from aviation for human–AI collaboration in medicine. npj Digital Medicine, 9. https://doi.org/10.1038/s41746-026-02410-1

13. Coker, E., Lockspeiser, T., & Hilgenberg, S. L. (2026). Artificial intelligence healthcare industry expert perspectives: How artificial intelligence will impact physician roles and medical education. Academic Pediatrics, 26(3). https://doi.org/10.1016/j.acap.2026.103225

14. Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2021). Precision medicine, AI, and the future of personalized health care. Clinical and Translational Science, 14(1), 86–93. https://doi.org/10.1111/cts.12884

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