In 2011, IBM computer Watson won first prize in the American TV quiz show “Jeopardy.” Watson spent three seconds finding the right answer to every single question he was asked, and in those three seconds the computer went through hundreds of processes all at once. Watson can not only understand the questions, he can also quickly find the correct answers and then proceed to communicate these. When winning “Jeopardy”, Watson had to understand and analyze references and metaphors, such as “feeling blue.” His victory in “Jeopardy” has great entertainment value and of course it became a hit on YouTube (link to video). But behind the “brains” lies three years of intense efforts by 20 researchers, who developed a technology called DeepQA. The aim was to create a new generation of technology that could find answers in unstructured data, and in a much more efficient way than previous technology has managed. The revolutionary aspect of Watson is that it can understand the world much the same way that humans do, through senses, learning and experience.
How can we take advantage of this in the health care industry?
Health is the most exciting area that Watson is able to revolutionize and earlier this year he helped solving a medical mystery. Doctors at a hospital in Tokyo had tried for a really long time to find the right treatment for a woman with leukemia, but every effort to combat the disease failed. When IBM’s genius computer Watson took over, he only used ten minutes to study the patients’ medical records and cross checked this information with over 20 million oncological reports. Watson concluded that the woman did not have the type of leukemia that doctors initially thought, but rather a very rare variant which required a different type of treatment than the one she had been receiving, according to Siliconangle.
Understands “common” language
Computers have long been of assistance in the health sector, but one of the biggest challenges until now has been that the machines do not understand natural language. Due to the fact that Watson understands this and can respond to it, it is no longer necessary to translate research articles, treatment guidelines, patient records and hospital records, textbooks, notes and emails to structured computer language. A doctor can ask Watson a question and describe the patient’s symptoms and other relevant factors. Watson will then analyze the information from the doctor and combine it with the latest research results and examine all available sources. When Watson is done with the analysis, a list will come up with potential diagnoses, together with an estimate that shows the validity of each diagnosis.
This new technology may revolutionize the health care industry as we know it today. However, will it ever become so good that it can replace the human medical professions?
Sources:
http://researcher.watson.ibm.com/researcher/view_group.php?id=2099
http://siliconangle.com/blog/2016/08/05/watson-correctly-diagnoses-woman-after-doctors-were-stumped/
http://www.ibm.com/smarterplanet/us/en/ibmwatson/health/
It is impressive to see the evolution of robotics and the way they are taking over many jobs in industries worldwide. It is fair to say that the technology for ‘robot doctors’ is evolving at a formidable pace and that it will tremendously affect the traditional profession. The question is how will this happen and will it ever become a fully automated industry?
It is imperative to firstly understand the limitations of this technology. A doctor’s job doesn’t end with a diagnosis or even a surgery, it involves a high level of care and understanding that a robot lacks completely. A doctor has to be able to give bad news to his patients, will a robot ever be able to replace this? Imagine a robot trying to calm down a kid who is depressed from being all day long inside a hospital because of a complex disease. Imagine a stage 4 cancer patient being told that there is no hope left by a robot. It doesn’t feel quite right does it?
So where do robots fit into the equation? To answer that, one must simply look at the current situation. Hospitals are already filled with robots such as the Da Vinci robot (one of the most successful and widely accepted robots used in surgery), these robots are not fully automated, they are controlled by the surgeon and therefore complement the professional’s work, they do not eliminate the need for a doctor.
Robots are not likely to revolutionize the industry as quickly as other technologies, they are more likely to be accepted and introduced little by little into hospitals as complementary technologies and taking over highly repetitive and low risk jobs such as basic care, post-surgery services and basic diagnosis services.
Missed a source:
http://theorion.com/46812/opinion/medical-robots-will-never-replace-human-interaction/
https://www.wired.com/2016/05/robot-surgeon/
Hi thank you for your post. I very much agree with what Sergio commented. A doctor’s professional does not rely on pure skills entirely. These skills can be taught by programming a robot, but what cannot be programmed is the human aspect to a doctor’s profession. Knowing how to deal with patients on a personal level is important to make the patient feel as comfortable as possible, is an environment that is usually associated with negativity (hospitals etc.). And this to my opinion, will never be replaced by robots.
Hi Katarina!
I had no idea about the example you gave; it’s quite fascinating how a robot was able to do something the human previously could not. Although I do believe that computers are more capable of diagnosing a disease quicker with a lower error margin (based on analyzing numerous data sets), I don’t think that it will be able to replace a human medical profession. There is still an interactive process between patient and doctor where the doctor must first identify the symptoms of the patient, prior to giving the computer this data. I also think that the final step of prescribing should remain with a human, as to avoid making prescriptions for those who are ‘faking’ their symptoms and simply want access to certain medication.