Despite intelligent machines’ limitations, they will continue to play a bigger role in health care.
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Although intelligent machines are increasingly operating complex manufacturing systems and replacing humans on factory floors, they have not made significant inroads in health care. The sector’s most advanced machines, from ultra-high-resolution imaging instruments to surgical robots, are still fully controlled by humans.
But as robotic and artificial-intelligence (AI) systems become more advanced, will they eventually render doctors and nurses obsolete, with patients consulting a computer instead? The short answer is: not anytime soon. Health-care professionals will certainly become increasingly dependent on machines; but technology will augment, not replace, their abilities, and doctors will remain in charge of medical practices.
In his 2009 book The Innovator’s Prescription, Harvard Business School’s Clayton Christensen identified a spectrum of medical practices that range between “intuitive” and “precision.” Intuitive medicine describes when a doctor interprets a patient’s symptoms to arrive at a diagnosis and prescribe a treatment, the efficacy of which is often uncertain. Precision medicine – which should not be confused with personalized medicine – describes a rules-based process by which standardized treatments with predictable outcomes are applied to known health conditions.
According to Christensen, most of the medicine practiced today is closer to the intuitive side of the spectrum, and only a few diseases, primarily infections, can be treated using precision medicine. In fact, at the moment, the concept of precision medicine is incorrectly applied to improve only the outcomes of intuitive medicine, instead of identifying the causal mechanisms of diseases. As long as this is true, human know-how and engagement will remain integral to health care.
Treating unspecific symptoms without a prescribed roadmap requires effective decision-making and trust, which is a significant hurdle for machines. After millions of years of evolution, humans have developed a capacity for contextual intuition that enables trained doctors to make sensible and timely decisions in uncertain, data-scarce environments. Even the most sophisticated AI systems that we have today would need to be improved significantly in order to mimic this ability.
Communicating with patients poses an even greater challenge for machines. Explaining the many nuances of a mysterious disease such as cancer requires emotional intelligence and the ability to build trust with patients by delivering information effectively. Doctors also must exhibit cultural humility, so that they can take into account a patient’s social background when administering care. For the foreseeable future, machines probably will not be able to match humans in helping chronically ill patients whose prognosis remains uncertain.
Still, despite intelligent machines’ limitations, they will continue to play a bigger role in health care, even in the realm of intuitive medicine. Owing to their superior analytic power, machines are already providing more data upon which physicians base their diagnostic and treatment decisions. Machines are increasingly monitoring patients as well, helping to prevent human errors in hospitals and pharmacies. Soon, many more ancillary functions such as admissions, scheduling, and discharges will be automated.
But, again, until the scope of precision medicine surpasses that of intuitive medicine, health-care professionals will continue to make medical decisions and interpret the data. So, what are the prospects for such a shift?
Up until the mid-nineteenth century, bacterial and viral diseases were treated through intuitive medicine, because nobody had isolated the cause of patients’ symptoms. Then, Louis Pasteur and other scientists developed the germ theory, microscopes improved, and scientists began to identify the sizes and shapes of microbes.
Over the past century, our scientific understanding of germs has improved so much that every virus and bacteria can now be quickly diagnosed and isolated. This has enabled health-care professionals to switch from practicing intuitive medicine to precision medicine, where they can apply standardized processes that predictably cure diseases. With simple and inexpensive methods, we have eradicated deadly diseases such as polio and smallpox. More recently, researchers discovered an Ebola vaccine that provides 100% protection against the virus.
One day, when we have gained a similar level of understanding of the biochemistry and physiology of the human body, precision medicine will be applied to all disease categories. We will be able to determine every disease’s cause and progression precisely, and machines will operate with more autonomy, within a standardized environment, to provide the exact treatment that every patient needs.
Just as rules-based processes have laid the groundwork for self-driving vehicles, rules-based precision medicine will steadily increase the importance of automated super-machines in health care. It already feels routine to be prescribed antibiotics for an infection. Eventually, patients will have the same confidence in machines to administer their care; and as our understanding of diseases improves, personal interactions will become less necessary.
We shouldn’t expect machines to replace health-care professionals for some time, but new technologies will continue to be introduced into the sector’s evolving landscape, and we should welcome them. Practicing more precision medicine than intuitive medicine will make health care simpler, more accessible, and less expensive. By understanding patients’ diseases precisely, we can push medicine one step closer to its ultimate goal: patient-centered care of the finest quality.