Technology

Can statistical analysis about our habits and moods provide tools for better living? The Quantified Self movement is counting on it. By Gillian Terzis.

Apps that guide living as a quantified self

Nick Winter uses “self-quantification” apps, and wears a Narrative Clip, a clip-on camera automatically taking photographs as he goes about his day.
Credit: SEAN FENNESSY

The past couple of decades have heralded the unstoppable rise of the quants – quantitative analysts. Financial journalist Michael Lewis’s bestseller Moneyball charted how sabermetrics – the empirical analysis of baseball games – led to the unlikely triumph of cash-strapped Oakland Athletics over much wealthier baseball teams in 2002. It was similarly notable that a statistician, rather than a pundit, was able to predict the outcome of the 2012 US presidential election.

The mathematical elegance and predictive powers of algorithms have long proved irresistible to the business world. But what can they teach us about ourselves? A growing range of “self-quantification” apps seeks to crunch the numbers of our health and activities and turn them into data that can guide us through life.

A few years ago, 26-year-old tech firm employee Nick Winter sent a sample of his saliva to 23andMe, the largest DNA ancestry service in the world. Up until December last year, the Californian company, named after the number of chromosomes in a normal human cell, sold reports to consumers for $US99 that outlined a person’s genetic disposition to more than 240 illnesses and diseases. A warning from the US Food and Drug Administration to stop marketing its health-related tests stopped the service. Customers can still receive raw genetic data, but 23andMe no longer offers an interpretation of the results, which are yet to receive approval from a recognised medical body.

Winter has a family history of clinical depression, and 23andMe’s analysis confirmed his higher genetic disposition to the illness. “Basically, I wanted to keep on top of it,” he says. To do so he uses an app called Moodscope, which asks users 20 questions about their emotions, derived from a mood test called the Positive And Negative Affect Schedule. A percentage figure is then calculated, which indicates one’s place on the happiness spectrum.

There are countless apps such as Moodscope, which imbue emotional experiences with a kind of empirical weight. The app’s three-point rating scale is not without its flaws, Winter admits, “but it’s the best system I’ve found”. Still, he plans to refine the metrics of his moods further. The webcam on his computer has been programmed to take snapshots of him browsing the internet at 15-second intervals. Winter hopes to run these photos through a smile recognition program, which would help him better understand the effects of his computer usage on his emotions.

One of the hallmarks of self-quantification is the embrace of digital technologies, but the practice has analogue origins. Benjamin Franklin finetuned his moral compass by recording each time he transgressed one of 13 personal virtues, which included cleanliness, frugality, temperance, silence and industry. Roman Stoic philosopher Seneca the Younger kept detailed notes on his dreams and food intake. Similarly, Winter has kept a diary since he was 17, but it wasn’t until he started using a smartphone five years later that he was able to monitor a wide range of activities and behaviour with greater accuracy. Few activities escape his meticulous logging: vast amounts of data have been accumulated from his sex life, web browsing habits, productivity, social life, sleep patterns, nutrition, cognitive ability and moods. “If you have all the information, you can make more informed decisions about your life,” says Winter. “But if you’re not aware of a problem, you can’t solve it.”

This numerical pathway to self-possession is the guiding philosophy of the Quantified Self movement, founded in 2007 by Kevin Kelly, self-anointed Senior Maverick at Wired magazine, and his Wired colleague Gary Wolf. While it has strong roots in Silicon Valley, the phenomenon has gathered global momentum, comprising data junkies, developers, people with chronic health conditions. Adherents to the quantified self ideology are undergirded by a simple and somewhat mawkish credo: “Self-knowledge through numbers.”

Phil Goebel, physiotherapist, avid rock climber and founder of the Melbourne chapter of the QS movement, envisages a role for self-tracking in medical care. His interest in the movement was spawned by a desire to find solutions to the myriad challenges of the healthcare system. Last December, he started building sensors for gait aids, to track elderly people’s walking quality over time with the aim of minimising and preventing injuries. He believes such an approach would drastically change how physicians understand and manage mobility among elderly people. A self-tracking aid would be rich in data, and could give “an incredible insight into how people are walking at home, in the mornings, and so on”, compared with the limited observations one might have at a regular clinic visit. “A physio can keep an eye on a patient without even being there,” he says.

But QS-related healthcare is still in its infancy. “Much of the medical community remains sceptical about the quality of the data, and how it might fit with the clinical workflow,” Goebel says. In its present state, quantified self technology presents medical professionals with a trade-off. They can generate high volumes of data, but the significant potential for user error can result in lower-fidelity information.

Bernd Ploderer, lecturer in computing and information systems at the University of Melbourne, has witnessed the positive effects of the self-quantification approach on individual health outcomes. Ploderer is currently working on an app with Quit Victoria that encourages people to quit smoking by providing them with online distractions (games, BuzzFeed articles) and support from others in the same boat. “People often keep their attempts to quit to themselves, because they don’t want the additional stress,” he says. “But you want some kind of support, and the app gives that to users while granting them relative anonymity.” Although he has mixed feelings about what the movement might mean for personalised medicine, the intrinsic value lies in “how people can be empowered by the stories told by their data”.

Elements of the movement have already become quite mainstream. The Pew Research Centre Internet and American Life Project showed that 70 per cent of adults in the US have tracked their personal data at some point in their lives, although a smaller proportion actively use smartphone apps or wearable devices like the Fitbit, the Misfit Shine or the Jawbone. Such technology unveils the seemingly boundless potential for human improvement: maximising personal efficiency becomes a utopian possibility. A dispatch from a quantified self blog often includes a liberal sprinkling of words like “optimise”, “control”, and “rationalise” as descriptors of one’s self-discovery. The parallels with the business world don’t end there: one of the world’s most prominent QS advocates, American graphic designer Nicholas Felton, releases an annual report of his life each year.

But for some users, there’s a more oppressive side to the data-driven life. Dieting apps have been criticised by health professionals for fetishising self-control over spontaneity. It’s also common for sporadic self-trackers to find their personal data provides really banal insights. Numbers can only provide a reflection of a reality that can be measured. The most intriguing facets of life perhaps lie beyond estimable bounds.

For developers, combating users’ number fatigue presents a significant challenge. Belle Cooper, one half of Melbourne start-up Hello Code, used to monitor her step count with an app called Moves, but found little motivation in its monotonous data stream. It led her to co-create Exist, an app currently in development that aims to centralise data analyses and highlight correlations between variables. Offering a colourful visualisation of data patterns – rather than an endless stream of metrics – may be a more enticing value proposition for users and potential venture capitalist backers. Identifying patterns is “where the magic happens”, she says. “For instance, my mood is higher when I listen to less music and when I tweet less.”

Correlation does not imply causation, but it’s hard to deny the power of suggestion on our behaviour. Subtle, well-intentioned suggestions are an integral part of Exist’s consumer pitch. Its website reads: “The information you already have can help you make changes to improve your lifestyle (if you want – or you can just look, and nod thoughtfully).”

Yet, could reducing one’s activities to a series of inputs and outputs make the pursuit of self-knowledge endlessly circuitous? The more you learn, the less you know: each new app brings with it a new metric to strive for. Technology’s rapid rate of change makes me think of our own built-in obsolescence and diminishing horizons. Eventually, the machine stops.

This article was first published in the print edition of The Saturday Paper on Apr 5, 2014 as "Life by numbers". Subscribe here.

Gillian Terzis
is a San Francisco-based writer.

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