Robotic surgical systems are used in thousands of hospitals around the world. A decade ago, it was bulky machines that were built to support routine operations. Today they are able to perform end-to-end operations without human assistance.
Recent advances in deep learning have made difficult tasks like surgery, electronics assembly, and piloting a fighter jet relatively easy. It can take a decade to train a person in all of the medical skills required to perform brain surgery. And these costs are the same for each subsequent human surgeon. Approximately the same investment is required for every human surgeon.
But AI is different. The initial investment in developing a robotic surgery device is large, but changes once you’ve built a working model. Instead of 8-12 years to create a human specialist, factories can be built to mass-produce AI surgeons. Over time, the cost of maintaining and operating a surgical machine – a machine that can operate 24 hours a day, 365 days a week without a paycheck – would likely become trivial compared to maintaining a human surgical staff.
That is not to say that there is no place for human surgeons in the future. We always need human experts who are able to inform the next generation of machines. And there are some techniques that go beyond the capabilities of modern AI and robotics. But surgery, like any other precision-based endeavor, is within the realm of modern AI.
Surgery is a specialized skill, and a large part of robots excel at automating tasks that require more precision than creativity. And that’s exactly why robotic surgeons are the order of the day, but we are probably decades away from being a fully functional, AI-powered nurse.
And that’s exactly why the AI didn’t have much of an impact during the pandemic. When COVID-19 first hit, there was a lot of optimism that big tech would save the day with AI. The idea was that companies like Google and Microsoft would develop incredible contact tracking mechanisms that would allow us to customize medical responses at an extremely detailed level. As we jointly suspected, this would lead to a shortened pandemic.
We were wrong, but only because the AI actually had nothing to do. Where it could help to aid the rapid development of a vaccine, it did. But the vast majority of our problems in hospitals had to do with things that a modern robot cannot fix.
What we needed during the last patient summit was more human nurses and PPE for them. Robots cannot look around and learn like humans, they have to be trained to do exactly what they are going to do. And that’s just not possible in huge emergency situations where, for example, the floor plan of a hospital changes to accommodate an increase in the number of patients and where huge amounts of new equipment are introduced.
Researchers at John Hopkins University recently conducted a study to find out what we need to do so that robots can help healthcare professionals with future pandemics. According to them, modern robots are not up to the task:
A big issue was deployability and how quickly an inexperienced user can customize a robot. For example, our intensive care ventilation robot was designed for a type of ventilator that pushes buttons. However, some ventilators have buttons, so we need to be able to add a modality so that the robot can manipulate buttons as well. Suppose you want a robot that can service multiple ventilators. Then you would need an arm-mounted mobile robot, and that robot could do many other useful tasks on the hospital floor as well.
That’s all well and good when things go perfectly. But what happens when the button pops off or someone introduces a new type of toggle or touchscreen machine? Humans have no problem adapting to these situations, but a robot would need entirely new accessories and a training update to compensate for this.
In order for developers to create a “nurse robot,” they need to anticipate everything a nurse experiences on a daily basis. Good luck with it.
AI and machines can be customized to perform specific maintenance-related tasks, such as: B. the support with the admission or the recording and monitoring of the vital functions of patients. However, there is no machine in the world that can perform the daily routine functions of a typical hospital staff nurse.
Nurses spend most of their time responding to real-time situations. At one shift, a nurse interacts with patients, setting up and dismantling equipment, handling precision instruments, carrying heavy objects through human-filled rooms, solving puzzles, taking meticulous notes, and acting as a liaison between medical staff and the general public.
We have the answer to most of these problems individually, but putting them together into a mobile unit is the problem.
This Boston Dynamics robot, doing backflips for example, could certainly navigate a hospital, carry things, and avoid injury or damage. However, there is no way to know where a doctor accidentally left the table they need to update their logs, how to calm a frightened patient, or what to do if an immobile patient misses the bedpan.
Published on March 30, 2021 – 17:58 UTC