You probably did not notice if your right eye twitched this morning. And you might not have attached any meaning to it, if you did notice. However, Gary Wolf, a contributing editor for Wired Magazine, sees such subtle observations as a pathway to self-illumination.
“It turns out involuntary movement of the muscles in your face is associated with moods and emotions,” he says. “Awareness of your facial muscles gives you an access point to your moods and emotions you wouldn’t otherwise have.”
Wolf is co-founder of Quantified Self, an organization dedicated to people who observe and record their own facial movements—and many other things—to gain a better understanding of themselves and improve their lives. The project began around 2007, at a time when life logging, personal genomics, location tracking, and biometrics were adding a computational dimension to ordinary existence.
“A technical person can take readily available tools and get an incredible range of information about themselves,” he says. “It turns out that measurement of facial expression is quite easily accomplished, even with gaming platforms.” It also can be done with a mirror.
Some Quantified Self members track their diets or cognitive performance over time using simple math tests. Others record their blood glucose levels, not—as you might expect—because they are diabetics but to find other correlations about their health that the glucose readings can reveal. Still others have logs of everything they have done in their lives in five-minute increments.
Wolf finds that self-measurement is a progressive activity. People start because they have a specific goal, like losing weight or sleeping better. “Beginning to use these new tools of self-reflection creates more questions,” he says. “People begin to be interested in the type of self-awareness they get from watching their numbers as much as the instrumental goal they have when they started.”
Take one Quantified Self project, where a young man named Ben started tracking how much time he spent doing his roommate’s dishes. He originally estimated an hour a day, but learned it was actually 20 minutes. What began with a desire to make sure the housework was equitably distributed led Ben to measure many other elements of his life.
“Ben uses data to find out details about himself, such as how he sleeps,” Wolf states. “The type of questions he’s asking and the conviction that these questions are answerable are a preview of the coming age of self-quantification.”
In many ways, that age is already here. The expanding field of home-health monitoring is one testament to the interest and benefits of self-quantification. As reported in Bloomberg Businessweek in 2009, Jennifer Shapiro, scientific director of La Jolla, Calif.-based Santech Inc., a company founded by researchers and thought leaders in mobile health and behavioral intervention, performed a study that found children who sent text messages detailing aspects of their exercise and food intake were more likely to stay in a weight-loss program.
“Self-monitoring is one of the most important ingredients of the weight-control recipe,” Shapiro said in the article. “The problem is that people do not stick to self-monitoring and thus lose track of what they are doing and do not experience weight loss.”
However, even this example points out some of the challenges of trying to quantify one’s life. For example, at what point does monitoring one’s food intake have the potential to move from useful information gathering to a compulsion that can contribute to an eating disorder? There are even more practical matters, like whether the information gathering should be automated.
“Information collected completely in the background never becomes part of our awareness,” Wolf says. “It turns out that something as simple as writing down information, instead of letting the collection be automated, can provide a powerful form of awareness that can provide deeper meaning.”
The questions should not be off-putting, because analytics should be viewed as a journey that provides greater insights along the way. Another of Wolf’s points, which extends to corporate business intelligence efforts, is that analytics can be applied to many areas that initially might seem too vague to measure—like facial muscles.
“We get into a long-term relationship with ourselves mediated by numbers,” he says. “We think of self-knowledge and self-awareness being mediated primarily by words—the inner voice we have—the voice of conscience and consciousness is made of words. There might be some numbers in there, too.”
And in truth, this is merely the flipside of the growing desire to turn unstructured data—such as Word documents and web conversations—into data that can be analyzed and used in decision-making. Wolf’s point is that the data providing illumination comes in many forms, and we should not be dissuaded from seeking insight simply because it can be difficult to determine how to use it.
The drive to metrics also has raised privacy issues, but Wolf has a different concern than most other people. He notes that the value of a person’s private data increases when it is joined with other people’s private data.
But he worries that the collective value in aggregated data is being privatized and used for a limited number of things, such as properly targeted ads on webpages, adjusting insurance risk, and evaluating whether to give someone a mortgage. Wolf feels that people will not be comfortable sharing their personal information until they see a direct personal benefit from doing so—and that means the information must be put to a greater use than the current “relatively impoverished world of analytic questions,” he says.
Intriguing stuff. The interest in self-quantification, along with the enlarging arsenal of personal analytics tools, truly is a reflection that we are entering an age of metrics. Soon, the only roadblock to measurement possibilities may be our imagination.
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