Since 2011, more than $870 million have been invested in more than 65 healthcare artificial intelligence (AI) startups. These startups concentrate on various areas, from nursing to drug discoveries, where AI’s potential can be put to best use. This is where the world’s heading towards and the future of healthcare lies.
The roots of AI may have been from some science fiction storytellers, but now, the reality is that AI plays a major role in our everyday life. Beginning with the IBM Watson supercomputer defeating the longtime Jeopardy champion, Ken Jennings, the world started taking notice about what artificial intelligence can do.
With Google and IBM making tremendous progress with their AI initiatives and the other tech giants (Like Apple, Dell, Facebook) trying to catch up, it makes us wonder what will happen when one day we have robots running around doing our everyday chores.
But, the main question should be what will happen when AI does fully breach our day to day lives: Will we embrace this reality and let robots take us over? And do we really need or is it desirable to have self-driving cars and artificial intelligence? Should computers acquire enough data and knowledge to replace our existing doctors?
Maybe we do or maybe we don’t, but let’s stop before we get ahead of ourselves.
AI should not be perceived as “artificial intelligence” but rather as “augmented intelligence.” It has the potential to process data and make cognitive decisions, which an average human can take many months to process. AI has truly opened numerous opportunities in the field of healthcare, which was humanly impossible just a few years ago.
Getting into the facts, the main advantage AI has over a normal human being is the ability to process a gazillion data points within seconds.
So let’s imagine a patient walks in with a flu – even to diagnose and treat this common illness with the right medication can take a while. There are some cases where the patients don’t even react to the medication. These are common scenarios, as each body reacts differently to different medicines leading to an increased treatment time. Whereas, if the diagnosis is powered with an AI backed system to help, doctor’s will be armed with all the right data and can diagnose and prescribe the right medication within minutes.
How’s that for a game changer?
Yes, AI is the perfect medical assistant to healthcare professionals.Through an iPad based electronic medical record, even the patient genome studies could be integrated into their electronic medical reports. Armed with this data, AI has enough information to make a better analysis and provide accurate treatment plans based on the patient’s medical history, genetic conditions and other medications they are taking for other illnesses.
It isn’t that doctors aren’t skilled, intelligent or capable enough—it is that the demands being placed on them are too great.
Time and documentation demands mean that something has to give. As many physicians have pointed out over the years of the HITECH Act’s implementation, the thing that normally “gives” is facetime with patients: actual, hands-on delivery of care and attention. Instead, they are driven to input data for documentation, follow prompts on EHR interfaces, ensure their record-keeping practices will facilitate correct coding for billing, as well as tip-toeing around HIPAA and the explosion of security and privacy vulnerabilities opened up by the shift to digital.
The reality of modern medicine—and especially the rate at which it evolves, grows, and becomes outdated—means that doctors need what most every other industry has already integrated: more brains. Not simply in the form of EHRs for record-sharing, or voice-to-text applications as a substitute for transcriptionists, but as memory-supplements, or second brains.
As a species, humans are also evolving away from memory as a critical element of intelligence, because we now have devices—“smart” devices—always on, always on us, and always connected to the ultimate resources of facts and data.
Our smart devices—phones, tablets, etc.—are gateways to the whole of human knowledge: indexes of information, directories of images, libraries question and answer exchanges. In effect, we are increasingly able and willing to offload “thinking” onto these devices.
Supplement or Supplant?
Depending on the context and application, this trend is both helpful and potentially harmful. For those prone to critical thinking and equipped with analytical skills, offloading some elements of memory to these devices is a question of efficiency. Even better, the more they practice using it, the more effective they become at integrating devices into their cognitive tasks. In others (those less prone to think critically), it is a shortcut that reduces cognitive function altogether: rather than a cognitive extension, the devices act as substitutes for thinking. Similarly, increasing over-reliance on the internet and search engines further diminishes already deficient analytical skills.
The standard roadmap for a medical education entails a lot of memorization—of anatomy, of diseases, of incredible volumes of data to facilitate better clinical performance. It isn’t memorization simply for the sake of recitation, though; it is the foundation for critical thinking in a clinical context. As such, medical professionals ought to be leading candidates for integrating smart devices not as crutches, but as amplifiers of cognition.
So far, that has been far from the dominant trend.
Enter the Machine
Integrating computers as tools is one thing, and even that has proven an uphill battle for physicians: the time and learning curve involved in integrating EHRs alone has proven to be a recurring complaint across the stages of Meaningful Use and implementation.
Patient engagement—another of the myriad buzzwords proliferating the healthcare industry lately—is another challenge. Some patients are bigger critics of the new, digitally-driven workflows than the most Luddite physicians. On the other hand, some patients are at the bleeding edge of digital integration, and find both care providers and the technology itself moving too slowly.
