It’s difficult to predict the future without first taking a look at the past. We’re going to take that a step further by examining a vision of the future from the past, courtesy of former cabinet minister and lawyer F. E. Smith, who was a friend of Winston Churchill’s. Shortly before he died in 1930, he wrote a book called The World in 2030 AD, in which he shared some predictions of what the world would look like in 100 years’ time.
THE TRUE BENEFITS of artificial intelligence, machine learning, natural language processing, robotics, and data will be seen when we move away from our current fee-for-service model of healthcare and towards preventative medicine. The idea is simple: instead of waiting for people to get sick and then trying to treat their symptoms, we can head illnesses off at the pass and stop them from becoming a problem in the first place. It might cost a little more up front, but it could save the healthcare industry a huge amount of money in the long run.
THE PRECISION MEDICINE INITIATIVE defines precision medicine as “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.”
One of the biggest opportunities for artificial intelligence is its potential to power precision medicine systems and to pioneer a future in which every patient is treated as a true individual. We’re already on our way thanks to private companies like 23AndMe and huge scientific efforts like the Human Genome Project.
AI IS ALL ABOUT MODERNIZATION, taking existing ways of working and rethinking them through the smart application of technology. A great example of this is the way that AI is being used to rethink patient communication, ultimately providing more support and improving outcomes.
We’ve reached a pivotal point in time at which we already have the possibility to create an “Internet of People” through everything from smartwatches and other wearables to electronic implants. But this comes with an interesting quandary when it comes to who’ll have ownership and access to the data that we create. In an article for the Wall Street Journal, professor of law and computer science Dr. Andrea Matwyshyn argues, “Using the human body as a technology platform raises a host of challenging legal and policy questions that regulators and judges may not be prepared to answer.”
The goal of AI should be to take human ingenuity and to attach a rocket to it, blending technology with ethics, accountability and inclusive design to empower as many people as possible. AI should benefit society, not dehumanize it. That’s why it can help to think with a “humans-first” approach. If it’s not adding value to humans, you have to ask yourself why the AI exists in the first place.
I have a vision of the future which I’d like to share with you. You’ve probably heard of black boxes before because they’re used in planes and other vehicles to monitor everything that happens while they’re in use. When a plane crashes, investigators look for the black box so that they can identify what happened. Similar technologies power telematics devices, which can be installed in cars and used to gain insights into how they’re being driven. Some car insurers now base their customers’ premiums on the data that they receive from the telematics device.
No one ever wants to come forward and talk about the issues we have with the current healthcare system — and how the future of healthcare will help to correct them. There’s a reason for that. Going on record to talk about it can put your job at risk, which is why many of the leading lights in the fight for the future are self-employed or working on the side of the technology giants. It’s a classic case of the elephant in the room, combined with the fear-based mentality of big businesses. They’re afraid of change.
It’s no coincidence that in both my book and in this article, I’ve started talking about data by using a quote from Sherlock Holmes. The world’s most famous consulting detective used the data he gathered in each of his investigations to arrive at a conclusion, and he was doing this as far back as 1887. We all create huge amounts of data on a daily basis, and yet none of this makes it into our health records. Today’s healthcare system, then, is much more Dr. Watson than Sherlock Holmes — and it’s a Dr. Watson who’s trying to theorize before he has data.
In my book The Future of Healthcare: Humans and Machines Partnering for Better Outcomes, I spent a lot of time talking about how AI, machine learning and other technologies can revolutionize the field of healthcare. I also talked about it in my last article on Medium.