When it comes to health and wellness, most people have a similar goal: we want to live a healthier, longer, and happier life. Thanks to antibiotics, vaccines, medical imaging, and other technological breakthroughs, we’ve already made major strides. So it’s perhaps no surprise that all eyes are now on the transformative innovation of this century: AI.
The promise of AI to solve our health and wellness woes almost seems inevitable. From DeepMind’s algorithms that match or outwit radiologists in breast cancer or eye disease diagnosis to Fitbits, Apple Watches, or smart pregnancy waistbands that track your health stats, the answer seems clear: more high-quality data will empower us to take control of our own health and happiness. Read more, do more, test more, quantify more.
It’s a popular narrative. But at Singularity University’s Global Summit in San Francisco last week, physician and entrepreneur Daniel Kraft, Dr. David Karow from Human Longevity, Inc., and happiness hacker Penny Locaso from BKindred painted a more nuanced picture. Data is power, yes. But what fundamentally matters is what you measure and how you respond.
And perhaps more importantly, it’s also about when to say no. To take control of our mental health, it pays to periodically ignore the information overload in our lives, instead focusing on a less data-driven, less busy but much happier life. In the big data era, more isn’t always the answer. Sometimes what truly matters for health and happiness is doing less.
Large-scale data gathering and analysis has enormous potential in healthcare. Our current system relies on intermittent and episodic data: you go to the doctor once in a while for regular checkups or when you feel sick. If you’re lucky, you can stop a life-threatening disease while it’s still early. Unfortunately, most of the time, people don’t.
This “sick care system” is ripe for disruption. The future of AI in medicine is to leverage personalized, comprehensive data and tell patients 10 years before disease onset of their risk factors and—more importantly—how to prevent it. The tools are already here to get us to over 100 years old, healthy and vibrant, and die of something we love rather than disease, said Karow.
Data and AI are already tackling two major advances in healthcare: prevention rather than treatment, and precision medicine in place of a population average. For example, Google and the NIH have both kicked off large-scale projects that measure baseline physiological factors from thousands of people of different ages, races, genders, and socio-economic backgrounds. The goal is to slowly build a database that paints a comprehensive picture of what a healthy person looks like for a given demographic.
Considering the shocking lack of diversity in clinical trials—including those of cancer drugs—the data will paint a more comprehensive picture of human health, one that includes you. These baselines can then be used to develop more personalized treatments, based on a particular patient.
At the same time, wearables are rapidly expanding into a full suite of trackers. Tracking steps and sleep is old school: there are now gadgets that monitor blood pressure, brain waves, heart rhythms, or even the health status of a fetus. Many of us have peeked into our genetic heritage and disease risk factors using 23andme; as DNA sequencing gets increasingly more affordable, consumers will be able to get a readout of their entire genome, rather than chosen snippets. Then there’s uBiome, which tracks the status of your gut microbiome. Add in medical imaging, biomarker testing, and diet and exercise data, it’s now possible to connect all those dots into a full, evolving movie of your health.
The end goal is to build a digital twin of every patient. Using simulations, we’ll be able to optimize diagnostics, prevention, and treatments that tailor to a particular patient. “We have the tools to generate that data—now we need to transform knowledge into clinical applications,” said Kraft.
Yet so far, AI hasn’t really moved the needle on healthcare. The reason, said Karow, is because AI hasn’t really been “measuring what matters.” Not all medical data is equal; rather than relying on superficial wearables, it pays to go deep.
Four years ago Karow kicked off a trial that recruited nearly 1,200 presumed healthy individuals and gave them a comprehensive medical checkup—everything from whole-genome and microbiome sequencing to biochemical measurements and advanced imaging. To the team’s surprise, they found early tumors, brain aneurysms, and advanced heart blood vessel disease in these supposedly healthy people. 14 percent had significant, life-altering clinical findings that could be nipped in the bud.
“Data empowers you to take charge of your health. It builds the story of you,” said Karow.
Yet there’s also a darker side to data. Anyone who’s felt constantly pummeled by information, let social media control their life, or desperately sought out new experiences to satisfy an increasingly shorter attention span understands: data may make us healthier, but that doesn’t always mean happier.
“We’re affluent, yet desperately wanting more. Connected, yet starved for human interaction,” said Penny Locaso. As we get increasingly busier, we focus less on what that truly matters, instead succumbing to a data deluge that makes us busy and stressed out. “Our focus on doing is compromising our state of being,” said Locaso.
She’s not alone. Plenty of studies have linked higher social media use to depression, anxiety, feelings of loneliness and isolation, and FOMO. Yet we’re so starved for data that people would rather receive an electrical shock than be left alone with their thoughts, deprived of any content.
Scientists have long known that spending time offline with your own thoughts is linked to creativity. Mental breaks away from the internet and other data sources—meditation, showering, or nature walks—replenish attention, solidify memories, and boost overall happiness. Ironically, even those who built the very platforms designed to capture our attention go on digital detoxes at New Age retreat centers such as Esalen or the desert culture bonanza Burning Man.
The overabundance of data is causing a constant state of distraction, and we’re unconsciously adapting into a state of loneliness and discontent, said Locaso. The solution isn’t further speeding up and looking for the next data hit; it’s to slow down.
With practice, being alone in your head won’t feel like torture. Rather, it’ll be a state of being that leads to creativity, one that will allow you to shape the world and make yourself happier in the process, said Locaso.
The trick, of course, is to reconcile and balance the promise of data in healthcare with its negative impact on mental health. Picture, for example, a physician struggling to keep up with thousands of new studies every month while tracking and analyzing health data from hundreds of patients and individually communicating with them.
There isn’t yet a complete solution to tackle her stress and happiness, but AI could help. By sorting through the data deluge, AI could potentially transform stressful raw data streams—academic papers, medical histories, exam results, or Twitter and RSS feeds—into more digestible visualizations. In turn, it harnesses the power of data for good while feeding our need for content in a compressed form that frees up more of our time.
The question is, what will you decide to do with that time?
Originally published at the SignularityHub.