The Greeks had the right idea but the wrong equipment.
Know thyself, they said – but all they had to work with were the dusty corners of our angst-ridden psyches.
I’m talking a walk with my iPhone, a pedometer app ticking off my baby steps toward a different kind of self-knowledge – truer, some would say, because it’s brought down to numbers.
This isn’t a belated New Year’s resolution of personal improvement (the new gym membership is supposed to cover that), but my attempt to understand the rise of the Quantified Self – a movement that evolved from geeks filling in spreadsheets with every conceivable detail of their daily lives to automated apps and gadgets even an old lap-counter like me can try to figure out.
As I proceed, step by step, I could be tracing a journey to the kind of numerical utopia promised by products like Fitbit Force, one of the wireless “wearables” being pushed at the recent Consumer Electronics Show in Las Vegas. There are also apps like Sleep Cycle, which graphs the quality of your sleep (and adjusts your wake-up alarm accordingly), MoodPanda, to help you rate your feelings through an interactive diary, and 80Bites, for those who want to track their food consumption bite by bite.
All of them share the sort of data software once exclusive to research labs, sports franchises and Fortune 500 companies, but now designed to modernize the search for an elusive better self, stripped of intellectual waffling and philosophical posturing.
“Never before have we had the ability to self-improve to such a massive extent,” says Christopher Berry, chief science officer at Authintic, a company that helps companies make use of personal social data. “There’s always a difference between what somebody tells you they are and what they actually are.”
What we are, please note, not who we are.
And there’s the rub. Can a pedometer – or a sleep app or a mood tracker – tell me what I need to live a better life, to know myself in ways that the old forms of introspection missed? And how much should I trust the “what” – all that data that I uncover? Can all these newly generated numbers, much like the selective haziness of human memory, sometimes get it wrong?
Numbers can surprise you.
Walking has become a large part of my life, in part because it’s the kind of locomotion that invariably takes time, but also because it comes with its own pleasure. I started my foot-based rambling in Europe, where the more concentrated landscape offered constant rewards at walking speed, and then realized that it was as easy and rewarding to cover large swathes of ground in my day-to-day life.
Walking is liberation – no traffic jams, subway delays, cellphone conversations on a cramped bus, just a trip home from work that is also exercise and even spiritually cleansing. Bad weather, like the recent ice storm, raises the stakes but doesn’t diminish my sense of accomplishment. Unable to sleep one power-free night, but unwilling to sit in the frozen dark at home for hours, I set myself loose and walked to the warmth and light of an office that still had functioning electricity. But I didn’t know as much about my walking as I thought.
I had always assumed I walked at about 6.4 kilometres an hour, a brisk marching pace. The pedometer told me that I covered the seven-km trip at only 5.3 km/h – a disappointment until I worked in the slippery footing of the icy sidewalks (the pedometer showed my stride shortening as I struggled to keep my balance).
Because I kept the pedometer working the whole day, I discovered that I took 13,708 steps, counting my roaming around the workplace – far more than I would have imagined.
Once you outsource yourself to an app or device, human measurement quickly becomes much more precise. There’s a natural tendency to want to do more to earn the gold stars that come with big numbers, to keep up with your apps’ demands and expectations – at some level you become more accountable, because you have a standard to meet and an external monitor to remind you of how you’re doing.
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