SA Forum is an invited essay from experts on topical issues in science and technology. This column was produced in collaboration with the World Economic Forum.
Imagine you have a great-aunt, a vibrant woman in her 70s who refuses to be trapped in a rocking chair. In fact, she holds a full-time job and insists on walking there and back, a couple of miles each way. She says it keeps her young, but you can’t help worrying. No one is healthy forever.
Like many people her age, your great-aunt follows a set routine. Before her trip to work, she stops at a nearby café for a cup of tea, and as she walks she phones a friend on her mobile phone. After work, she likes to call another friend to ask about a visit. She picks up a small cake or a few cookies at a shop on the way. Afterward she buys groceries to take home for supper.
A big departure from this pattern could mean your great-aunt is having problems. If you had access to her cell phone records and GPS data, you could see that something was up. It could even help you tell how urgent the situation might be. If she’s quit socializing and is just shuttling to work and back, it might signal depression—you’d make a note to drop by and make sure she’s okay. If she stops leaving the house entirely and doesn’t answer her phone, you know the problem is urgent. If you can’t get over there immediately, you’d better call a neighbor to look in on her.
Your auntie probably can’t enable you to access her data directly, no matter how she might wish to. But soon you could have a better solution: an app on her phone that would scan her data regularly for symptoms of physical or emotional distress and text or e-mail you a warning if necessary. Using sophisticated machine-learning algorithms, the app could even distinguish between a yellow alert and a red one.
This is just a bare-bones example of “quantified self” technology. The term may be unfamiliar to most people, but the idea behind it is already starting to change lives—and to reshape society as a whole. "QS" is basically the everyday use of electronic devices to monitor, interpret and possibly adjust our own physical and mental processes. And it can work wonders.
One of my most indispensable QS devices is a wristband containing just one sensor: an accelerometer. Besides clocking my daily exercise, it goes on monitoring me through the night, sorting deep sleep from light sleep according to how much I toss and turn. With its help I’ve discovered that regardless of when I go to bed, the time between 5:30 and 6:45 A.M. is when I can count on getting some of my deepest sleep. Now I know better than to set the alarm for 6:15. Instead, I go to bed later, get up later and feel far more rested with the same amount of sack time. Once you experience something like this, you’re sold.
QS devices and apps don’t tattle to your doctor. They don’t yell at you. They just help you see what you’re doing—and maybe how to do it better. As the trend grows, our appetite for deeper insights will grow with it. People will demand to see existing data that’s always been kept from them—not only the confidential histories in their insurers’ files but also the undisclosed marketing dossiers their favorite Web sites have been assembling for years, if not decades. In the future we simply won’t stand for a company’s owning data on us and refusing to let us see it.
So far, most QS sensors remain on wristbands, phones and other wearables. But sooner or later the technology is bound to get under our skins—literally. Like it or not, modern humans are mutating into a race of cyborgs. Medical devices like hearing aids and pacemakers have become commonplace—and it’s only a slight exaggeration to say we’ve grown attached to our smartphones. As QS technology becomes smarter, tinier and more essential to our daily lives, it’s likely to become literally a part of us. Eventually we might even communicate with one another via those devices. Not everyone may like the prospect of such a networked future. But you never know when your great-aunt might need help.