Medicine is like no other profession. At least, not like other legal professionals.
In a quiet, brightly lit room, the doctor asks the patient to undress, reveal a secret, and allow himself to be stabbed with a needle or knife. In medicine, they lay the foundation for deep interpersonal relationships.
In a profession built on intimate relationships, medicine now faces unprecedented challenges. It’s generative AI. Patients are growing concerned about artificial intelligence tools like ChatGPT and their emergence in the medical field.
According to a recent Pew Research poll, the majority of patients fear:
- Their healthcare providers rely too heavily on AI to diagnose diseases and recommend treatments (60%).
- Their AI will make them lose their personal connection with their healthcare provider (57%).
Earlier this month, I looked at some of the technical concerns patients expressed about AI, including issues like security, privacy, and bias. In this follow-up article, we examine the ethical issues that arise as physicians increasingly rely on new AI technologies.
Human vs Machine vs Ethics
Researchers can objectively measure many areas of clinical performance. For example, you can test how accurately radiologists interpret mammograms and chest x-rays for pneumonia. Then you can compare those results to a computer application that performs the same task.
While these scientific measures are important, medical practice is not always quantifiable. Patients often turn to medical professionals with problems for which there are no objective or “right” answers.
The moral principles that govern individual behavior and the ethics that shape physician decisions are (and continue to be) hotly debated. In fact, the American Medical Association maintains a vast code of ethics, spanning 11 chapters and containing 161 opinions on the proper conduct of modern medical practitioners.
On those pages, and in the profession itself, rational people disagree on a wide range of medical ethical topics. How are organs best allocated to people in need of transplants? What are the indications for using unproven treatments for life-threatening diseases?
There are no clear right or wrong answers to these questions. Patients rely on their physicians to navigate these ethical uncertainties. Now they fear generative AI will erode and undermine that personal connection.
This fear is understandable. But I am optimistic that the application of generative AI will improve healthcare, facilitate ethical decision-making, and even strengthen the bond between doctors and patients. But getting there requires a shift in thinking.
Machine: bad. Hito: Good.
As humans, we tolerate mistakes made by other humans, but much less forgiveness for the equivalent mistakes made by machines.
As an example, imagine flipping a switch and suddenly all cars in the US are self-driving cars. Cars on the road do not have steering wheels, accelerators, or brake pedals. There is no way for humans to seize control.
Now, let’s assume that in the first year of this grand experiment, 10,000 people died due to technical failures. Under these circumstances, do you think the media and most Americans would see the transition from human-driven cars to self-driving cars as a success? is not difficult. Based on the coverage of self-driving car accidents so far, we can predict that the internet and our televisions will be littered with gory images of crashes. Millions of Americans will demand that humans take back control of all vehicles.
Getting lost in the commotion is an important fact. human error.
These deaths are well known to organizations such as Mothers Against Drunk Driving (MADD) and are mourned by grieving families. But man-made genocide is largely ignored unless the victim is someone we know. We blame the drunk driver and her distracted teen for the reckless accident, and assume we never hurt anyone ourselves. But when you read an article about a self-driving car crashing into a pedestrian, you conclude that the technology has a fatal flaw.
As generative AI takes on a larger role in healthcare, these same pro-human, anti-tech biases are likely to surface.
“But I love doctors.”
When pollsters asked patients who they trusted, nurses (71%), health care workers they knew (70%) and doctors (67%) topped the list. In contrast, overall, only 34% to 44% of the US public express confidence in the healthcare system.
As humans, we put our trust in people, not systems. Unfortunately, the data contradict our trust in health professionals: Nearly one in four of her hospitalized patients experiences a medical error, resulting in tens of thousands of people dying each year. dead in need. Similarly, neglected prevention and suboptimal treatment of chronic diseases result in hundreds of thousands of preventable heart attacks, strokes and cancer deaths in the United States each year.
We accept human malpractice in the same way we accept human traffic deaths, despite objective evidence that clinicians are not perfect. We believe that our doctors do not make the same mistakes other doctors do (and do so without supporting data and evidence). But I fear that the introduction of generative AI will harm us.
Overcoming these fears requires a shift in both mindset and time. But the future of medicine looks even brighter. Here’s what we have to look forward to:
1. Repair the rift in the doctor-patient relationship
Whereas in the past physicians were well-known and widely respected members of close-knit communities, today’s physician-patient relationship is intermittent and impersonal. Given the medical problems facing patients today, this is a problem.
More than 60% of adults have chronic diseases that affect their daily health. And more than ever, patients will benefit from continuous monitoring and prompt medical intervention. A follow-up visit is scheduled every 6 months.
Generative AI offers the solution. ChatGPT can act as a medical assistant in the patient’s home rather than the doctor’s office, helping to provide a more continual care experience. Combining AI technology with home monitoring devices enables daily monitoring and alerts patients and physicians when measurements deviate from clinical plans. AI helps patients get the care they need quickly and conveniently.
2. More consistent diagnosis and treatment
Studies show that there is a significant gap between the quality of care patients need and the care they receive most frequently in the United States.
As an example, half of adults in the United States have high blood pressure, also known as hypertension, which puts them at an increased risk of heart attack and stroke. For the overwhelming majority of these patients, the problem can be successfully controlled with affordable and available medications.
Yet nationally, only 60% of hypertensive patients have their blood pressure adequately controlled. Compare this to some medical groups, where over 80% of patients have elevated blood under control . difference? Successful medical groups incorporate advanced IT systems and use evidence-based approaches to improve screening, monitoring, and treatment. So rather than fear the future of generative AI, Americans can hope for fewer strokes, heart attacks, and kidney failure.
Already, tools like Glass AI 2.0 help doctors create differential diagnoses and clinical plans in seconds, allowing them to spend more time with their patients. Moreover, as AI technology becomes adept at voice-enabled documentation, clinicians will be further freed up to spend most of their time focusing on the patient in front of them (rather than the computer).
Finally, when doctors are uncertain about a diagnosis or treatment, ChatGPT can be a trusted and fast source of medical expertise. Her medical knowledge doubles every 73 days, so no doctor can keep up with the pace of change. But with generative AI, it is possible. When a patient has an uncommon problem, doctors have instant access to the latest journal articles and case reports about the disease.
3. Personalized care with more ethical considerations
Doctors often provide poor guidance when it comes to helping people make end-of-life choices and decide whether to undergo high-risk procedures. Many clinicians are reluctant to discuss palliative care or acknowledge the futility of additional treatment. For them, telling a patient that there is nothing they can do feels like a failure.
Research shows that patients only want the truth about their disease and prognosis. And research shows that people who choose palliative care actually live longer than futile end-of-life care.
Generative AI will not replace doctors in counseling patients to make painful decisions, but it will allow them to consider a wider range of possibilities, broaden their analytical frameworks, and provide greater insight than if doctors worked alone. It helps us reach good conclusions.
Eliminate existential threats
In an oft-cited study, AI researchers and other experts were asked, “How likely is it that humans will not be able to control future advanced AI systems, causing human extinction?” I was. The median response was 10%.
Disruptive technologies always face serious concerns, and ChatGPT is no exception. Generative AI will impact the doctor-patient relationship and replace humans in many tasks. However, physicians spend more time with patients, resulting in less physician burnout and improved patient satisfaction. Also, the next generation of his ChatGPT will improve quality outcomes, make healthcare access more convenient for patients, and reduce healthcare costs. Yes, this technology created risks, but it also made the promise of better health exponentially greater for all.
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