Author: Maysoon Almasarweh
Oftentimes, when people think about the future of AI, they think of shows like The Jetsons, a widely popular cartoon from the 1960s that depicts a middle-class family in the year 2062. The family is shown living in a world of flying cars and robots who do everything for them. Though certainly an entertaining concept, this is purely fiction. In reality, the potential applications of AI are much more commonplace. Artificial intelligence has come a long way over the years, from the Curiosity rover that was placed on Mars back in 2012 to the widely utilized chatbots of today. As time goes on, society has come to rely on this artificial intelligence more and more. With its rapid advancement, AI is slowly but surely being implemented into professional areas such as marketing, education, banking, and—very soon—medicine. Institutions like Stanford University and Massachusetts Institute of Technology (MIT) have been researching new assistive AI technologies specifically tailored to medicinal care. It is through this research that such technologies have proven themselves to be incredibly accurate when diagnosing conditions and recommending treatments for patients. In light of the precision of the AI technology currently being tested, it would be beneficial to incorporate artificial intelligence into the medical field after the technology is developed further. However, there are several areas in which these AI doctors are lacking that prevent them from completely replacing their human counterparts, such as human connection and empathy.
AI technology has proven itself to be an accurate tool for diagnosing and treating patients. This statement has been greatly supported by several scientific studies, one of which was conducted by Dr. Adam Rodman from Beth Israel Deaconess Medical Center in Boston, who specializes in internal medicine—a medical specialty that focuses on the process of diagnosing and treating complex diseases in adults. In his study, Dr. Rodman compared an AI chatbot’s accuracy in diagnosing medical conditions from past case reports using the patient symptoms provided compared to human doctors who received the same reports. The results of the experiment showed the chatbot earning an average score of 90 percent correct diagnoses, while the doctors’ scores had a mean of 74 percent correct (Kolata). The difference between these scores is astounding, as AI chatbots were 16 percent more accurate than humans when diagnosing various conditions. This level of accuracy is particularly important when treating illnesses with overlapping symptoms like Lyme disease and chronic fatigue syndrome. AI is able to differentiate between such conditions more easily than humans can—which, in some cases, can be the difference between life and death. By utilizing AI in clinical care, patients can receive a quicker diagnosis and more effective treatment than that of human doctors alone. Not only can AI detect and treat disease in individual cases more efficiently than humans, but they can also benefit the field of medicine on a larger scale. In fact, biology and AI researcher in the Mayo Clinic System’s Department of Molecular Pharmacology and Experimental Therapeutics, Dr. Hu Li, Ph.D., suggests that medical professionals will be able to use “‘informed AI algorithms to solve scientific questions, better understand diseases, and guide individualized medicine,’” (Mayo Clinic). Through the intervention of assistive AI algorithms, clinicians and medical researchers may be able to devise new and improved care plans that better suit each patient. This technology can revolutionize clinical care by furthering the existing abilities of medical professionals as well as carrying out tasks more efficiently than humans. Incorporating assistive AI into traditional medical care can drastically improve the healthcare industry as a whole in terms of precise clinical treatment.
AI technology can not only be used to improve diagnosis and treatment processes, but it can also prevent doctor burnout. The rates of burnout in doctors are concerningly high and have much to do with the great amounts of stress clinicians are consistently put under. Michael J. Hasselberg, an associate professor of psychiatry and clinical nursing at the University of Rochester, explains that this stress could be attributed to an unreasonably large workload. He suggests that much of “the burnout that is happening on the clinical side is from all of [the] documentation burdened on [clinicians]” (Rochester Business Journal). The average doctor’s workload can prove to be incredibly overwhelming at times, leaving time for little else. Menial tasks like documentation, though crucial to providing patients with appropriate care, take copious amounts of time and energy away from physicians. According to Haselberg, AI can remedy this by taking over such tasks for doctors. AI can provide doctors with the assistance necessary to improve not only their performance at work but also their mental health. Mental health struggles are a serious issue within the medical field. Many physicians find themselves lacking in both time and support when it comes to caring for their patients, making depression and suicide common occurrences amongst medical professionals. Dr. Pamela Wible bore witness to several of these suicides as the daughter of a pathologist and a psychiatrist who eventually became a doctor herself. Throughout her time in medical school and her residency, she saw several colleagues take their own lives. She is now a therapist that works primarily with physicians and has raised concerns about doctor burnout. In a Newsweek article by Alexis Kayser, Wible speaks on her experiences and observations regarding the mental health of medical professionals:
Wible hears “I wish” statements from physicians all the time: “I wish I could take a lunch break. I wish I could use the bathroom. I wish I could go home to my family.” Maybe those extra five minutes saved per visit can add up, but Wible said the doctors’ wish lists go on. “I wish I had labor law protection… I wish I were treated like a human being.” (Kayser)
AI can provide critical support to doctors suffering from burnout. When doctors hand off documentation to assistive AI systems, they are able to dedicate more of their time to other aspects of their lives. In the time it would take them to write up an administrative report, they could be spending time with their loved ones or dedicating some time to rest after a long day. Doctors are human too; they require certain amounts of rest and support in order to properly function, just as any other person would. The utilization of AI in documentation and organization is the first step to improving the mental health of medical professionals.
Though the prospects of AI technology are largely positive with its high accuracy and varied uses within a clinical setting, human interaction and bedside manner remain as vital components of quality clinical care. Thus, it is imperative that the capabilities of artificial intelligence be used hand in hand with those of human doctors. While accuracy is crucial to providing patient care, there are several other factors that determine the quality of one’s care—factors that AI is unable to encapsulate. The qualities possessed solely by human doctors, such as interpersonal connection, “empathetic bedside manner, inquisitive thinking, compassion, and genuine care [are] and always will be essential to healthcare” (Schaar). Patients not only expect but also require attentive care when receiving medicinal treatment. The basic human emotions of compassion and empathy help guide patients to a steady recovery. In my training as a UCSF hospital volunteer, the importance of patience and kindness when interacting with patients has been emphasized repeatedly, as a negative environment may inhibit the recovery process. As volunteers, we are encouraged to interact with the patients we are assigned to, forming bonds of mutual respect and trust. The same can be said for doctors, who must establish similar relationships with their patients in order to continually provide them with quality care. In fact, the National Institutes of Health state that the implementation of “precision medicine plans requires communication between physician and patient to ensure positive outcomes.” Proper doctor-patient communication is not simply a matter of relaying information. When—for example—clinicians are delivering a grave diagnosis, they must be able to lead the conversation with empathy and complete understanding. This level of communication also pertains to the quality of a doctor’s bedside manner, which would be nothing without the human elements of humanity and sensitivity that are not present in artificial intelligence. AI cannot mimic the qualities of compassion and responsiveness that medical professionals constantly utilize in clinical care settings. In light of this, artificial intelligence should be used exclusively as a tool for physicians to employ in a healthcare setting, not their replacement.
Aside from a lack of overall emotional expression, there are several other limitations that prevent AI from being fully implemented into healthcare practices at this point in time. Opponents of assistive AI in clinical care have expressed concern regarding the protection of patient information. The American Medical Association cites some of these security concerns in a recent article, claiming that applying artificial intelligence to clinical care “will introduce new ethical obligations for [healthcare] providers who might wish to share patient data or sell it to others” (Banja). These proposed concerns are entirely valid, as, much like the data collection and data tracking of cellular devices, large companies are likely to pay top dollar for access to patient data in order to create targeted advertisements. Now, it is certainly one thing for a company to know that someone was recently browsing for a new pair of yoga pants, but it is an entirely different situation if they are aware someone has been diagnosed with a terminal illness. There is a clear line that must be drawn when it comes to a patient’s medical information. This is precisely why it is imperative that AI technology be developed further before being applied to patient care. Thus, it is the responsibility of those currently developing these systems “to devise a system of data governance that protects the interests of patients, provides access for researchers, distributes the fruits of success fairly, and wins the confidence of the public” (The Independent). Despite its many potential uses, AI technology can not yet be implemented into the health care system. Utilizing this technology requires the creation of new safeguards and regulations that protect the interest of the patient. These measures will likely entail receiving consent from patients in order for research institutions to be able to gain—limited—access to their medical information to further their understanding of certain areas of study. It is of the utmost importance that the patient is able to determine the extent to which their information is utilized, if at all. In addition, as this technology progresses, the need for protection policies like the Health Insurance Portability and Accountability Act (HIPAA) may arise at the federal level. Until these needs are met, it would be unwise to apply these algorithms to the healthcare industry.
AI is an incredibly powerful tool. It can be relied on to correctly diagnose various conditions and advise treatment accordingly. The various capabilities of assistive AI systems not only improve the quality of patient care but also lighten the heavy workloads of clinicians—which can potentially counteract the rising rates of doctor burnout. In combination with the aid of human intervention and the implementation of safeguards to protect patient information, artificial intelligence can revolutionize the healthcare industry in the coming years. The marriage of artificial intelligence and industry can be applied to areas beyond medicine. Several other industries, such as manufacturing and customer service, are actively incorporating artificial intelligence into their respective fields. Some examples of such applications include quality control and predictive AI systems designed for factory settings and AI chatbots used to interact with customers. AI is the future—that much is true— and although this particular future may not include flying cars or robot maids, it is up to mankind to determine how far it will take us.
Works Cited
Al-powered Personalised Medicine Could Revolutionise Healthcare (and No, We’re Not Putting ChatGPT in Charge); Artificial Intelligence Can’t Replace Human Professionals but It Could Transform the Way They Treat Diseases Such as Cancer, and save LivesMihaela Van Der Schaar Is Director of the Cambridge Centre for Al in Medicine at the University of Cambridge.” The Guardian (London, England), 26 June 2023. Gale General OneFile, link. Accessed 29 Jan. 2025.
Banja, John. “How Might Artificial Intelligence Applications Impact Risk Management?” The AMA Journal of Ethic, vol. 22, no. 11, Dec. 2020, pp. E945-951. link
Kayser, Alexis. “Is AI the Cure to Doctor Burnout? Is Generative AI the Cure to Doctor Burnout That Will Allow Physicians to Focus on What Matters Most–their Patients?” Newsweek, vol. 183, no. 8, 27 Sept. 2024. Gale General OneFile, link. Accessed 29 Jan. 2025.
Kolata, Gina. “A.I. Chatbots Defeated Doctors at Diagnosing Illness.” The New York Times, 17 Nov. 2024, link
National Institutes of Health. (n.d.). Ai may help improve doctor-patient communication. U.S. National Library of Medicine. link
Mayo Foundation for Medical Education and Research. (2024, April 15). Mayo researchers invented a new class of Al to improve cancer research and treatments – mayo clinic news network. Mayo Clinic. link
“Rochester Health Professionals Weigh in on Benefits of Generative Al.”Rochester Business Journal, 4 Sept. 2024. Gale General OneFile, link. Accessed 29 Jan. 2025.
“When Artificial Intelligence Is Used in Healthcare, Patients Will Need Greater Protections.” The Independent (London, England), 8 Feb. 2018, p. 33. Gale General OneFile, link. Accessed 29 Jan. 2025.
Edited By: Tammy Zhen
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