Essay about robots replacing humans in medical fields.

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From simplest tool to the most advanced Robots, the human has been curious to search for means to outperform himself, and the result is the advancement in technology and science that was hardly imaginable hundred years ago. It is hard to categorize the incentives of individuals and organizations to pursue it, however, one with an utmost priority is and has been survival and health. This particular focus has improved average lifespan of humans drastically. Nevertheless, a human supervisory rule has never been compromised. Then again, robots have been replacing humans, and it has never been slowed down. Humans are intelligent and they have designed tools to do their jobs more efficiently, yet can humans be replaced by robots completely? In almost all physical or analytical works, robots are replacing humans, so why they have not yet replaced doctors? In this essay, the possibility of this matter in medical procedures is discussed; critical roles of a physician are investigated, and they will be compared to that of an automated system. Two unique requirements in the jobs of physicians, meaning accuracy and decision making in diagnosis, monitoring, and performing operations on the body, will be discussed.

Nowadays, if one has a common cold, he would visit a doctor, and the doctor, based on defined procedural assessments, prescribes appropriate medicines. Nonetheless, if certain symptoms were not conclusional, the doctor, other than acting on the acquired individual intuitions, simply is unable to conclude a certain diagnosis. That is why further analyses are needed, which are commonly performed by means of machines that produce visual results for the physician. However, if a system were able to consider all the required diagnostic procedures, visualization is not even required, and the system is capable of making assessments and produce instructions without the involvement of human. An unsupervised system of diagnosis does not exist, yet it has been moving towards it. Some even provide free easy-to-use online diagnosis, e.g. WebMD Symptom Checker (1) that is limiting possible diagnoses with a visual interface. Making diagnoses is fairly a straightforward process because many of the symptoms are known, and researchers are constantly updating the list. Furthermore, comparing to Human-centered designs (HCD), fully automated systems have higher availability and are cost-effective. These incentives make it more likely that we see fully automated diagnosis systems in the near future.

We talked about diagnosis based on the detected symptoms, but when a patient is at constant risk, having a nurse or a doctor on call is needed, however, it is not feasible for most people to pay for this. The closest thing we have now is emergency services consisting of call centers, ambulances, and emergency rooms, but sometimes, it might be too late. In most of the medical emergencies, the first moments are critical. One answer could be ubiquitous sensors that read vital signals of a patient and send it to a remote station. IoT approach, in this case, is to accumulate data, and report critical situations. Nevertheless, it is impractical to have a doctor or a nurse constantly monitor all the signals from all the patients, even in a remote center. Besides, humans make mistakes, and they are unable to monitor all the indicators. The solution might be replacing human observant with machines; however, the question is how far a machine can replace humans. In this stage, we are in need of an expert system rather than a general knowledge-based system. This approach requires employing certain techniques that are generalized under concepts of Machine Learning (2). With the data gathered by the aforementioned sensors in medical IoT networks, it is expected that machines get better at decision making; however, for now, the policies are aligned with HCD approaches, because of either ethical reasons or prevention of unexpected results.

After diagnosing the disease, sometimes operations are required. Life-threatening risks are always part of surgical operations. Even one small mistake can be terminal. Surgeons’ experience and decision-making abilities in critical moments are what make the difference. Although all of the certified surgeons must pass several tests to be qualified, humans are prone to make mistakes. On the contrary, this is not the case with machines. They certainly need maintenance, but emotions and distractions have no effects on their performance. To that end, each year a substantial amount of money is allocated to develop new systems. Each year, a new system is emerging that can improve a surgeons’ efficiency and accuracy. FDA has already a section defined as Computer-Assisted Surgical Systems that Robotically-assisted surgical (RAS) devices are one type of these systems. (3) As a consequence, the methods of operations are also changing. The nature of operations is leaning toward non-invasive surgeries, which is an indication of reliance of surgeons on those machines. That being said, still, the role of the human expert in most of the surgeries is not eliminating, and the closest place that we have reached is performing surgeries without the presence of a human. Case in point, we can mention surgical robot Da Vinci. (4)

In conclusion, The robots and intelligent systems have already begun the process of replacement. If one wants to know if or when the machine will replace the physician completely, he should wait and see. However, there are some incentives that can guarantee this trend steadily continues. Robots are far cheaper than humans, and annually, governments allocate a considerable amount of their budget to health care, and of course with getting a better healthcare longevity of the population also increases and they can count on higher retirement age, therefore it is expected that they welcome more investments in the field. New amount of research in technical fields, especially in machine learning is emerging, and it is not limited to universities only; giant companies like Alphabet and Amazon are investing in considerable amount in developing new methods in machine learning, and it is expected that we gradually get a more human-like thinking in robots too, and of course without the errors. Of course with the evident outcomes, it is certain that these investments would also increase. Complete replacement of humans in medical areas by the robot is probably at the time when statistically it is proven that robots are performing better in all aspects, and of course, aside from a good result, ethical views are also considered. Until then, the human supervisory role will be present.