Artificial intelligence is coming to healthcare. In fact, in areas such as radiology and cancer detection, it’s already here in places, and is poised to become ever more prevalent in the industry. There’s strong consensus that AI won’t replace doctors. Arguing that it can goes not just against the complexity of what doctors actually do, but such a stance fails to realize the need for a human touch. You will want a human to hold your hand when discussing your cancer diagnosis. Empathy is critical in such life-changing moments. Physicians, nurses and other members of the medical staff have plenty of cumbersome monotonous and repetitive tasks to complete every single day. The level of human connection you’ll have with your doctor will directly influence how well you feel, how likely you are to stick with a treatment plan, and how you and your family will remember the trauma for decades to come. At present, you would not trust a robot or a smart algorithm with a life-altering decision or even with a decision whether or not to take painkillers, for that matter.
Artificial intelligence and machine learning algorithms tend to rely on large quantities of data to be effective, and that data needs human hands to collect it and human eyes to analyze it. And since AI in healthcare is currently utilized mainly to aggregate and organize data — looking for trends and patterns and making recommendations — a human component is very much needed. Doctors banter with patients, gather a few symptoms, hunt around the body for clues, and send the patient off with a prescription. This sometimes (accidentally, maybe) leads to the correct treatment, but doctors are acting on only a fraction of the available information.
But agreeing that the human doctor will always be there doesn’t reflect the massive changes and risks to their jobs. Doctors essentially do three things: diagnosis (what’s wrong with me?), treatment (what’s the plan?) and prognosis (how long before it gets better?). All three core tasks are being gradually performed by AI systems that employ machine learning, deep learning, natural language processing and time series forecasting.
AI could help us diagnose and treat disease. It can collate and serve up broad swaths of data in a clear and concise way, cutting down on the imprecise judgments that doctors make because of the pressures and complexity of our practices. There’s no doubt that for certain doctors, whose work is highly focused on diagnosis (radiologists or pathologists, for example), that breakthrough may prove an existential threat. A decade ago, for example, researchers showed that AI was as good as radiologists at detecting breast cancer.
The U.S. radiologists will make the claim that AI systems cannot possibly replace them, the majority of people in the world don’t have, and will never have, access to a radiologist. The next century of progress in medicine may be driven by AI, deployed to give your local primary care doctor, as well as the world’s top specialists, superpowers to diagnose and treat any disease. But first-world specialists are also not exempt from change. Although data, measurements and quantitative analytics are a crucial part of a doctor’s work – and it is going to be even more critical in the future– setting up a diagnosis and treating a patient are not linear processes. It requires creativity and problem-solving skills that algorithms and robots will never have.