Quantifying Yourself for a Better Life

A few years ago I was guinea pig for an Intel Labs study. I attached three sensors to my body for a week: a pedometer on my belt, a heart rate monitor strapped around my chest, and a galvanic skin response detector (stress or “lie” detector) taped to one of my fingers. I also made regular notes about my mood on a smartphone app. It was a fun (albeit a bit uncomfortable) experience, but what I didn’t realize at the time is that our researchers were temporarily placing me in the early stages of a cultural movement called the “Quantified Self.” Today this movement has evolved and it’s more apparent how data collection and computing can improve personal well-being.  

A significant number of people today are collecting and analyzing information on their health, exercise, activities and moods in order to learn things about their life. According to a study by the Pew Research Center, 69% of U.S. adults keep track of at least one personal heath indicator, including 12% who tracked on behalf of a loved one. However, according to the same study only 21% of trackers use technology to do so.  

As the size of computing continues to shrink, more sophisticated wearable devices (e.g. pedometers) will facilitate this data collection as they become more personalized and connected. More analytical tools are also becoming available to allow people to make sense of the data. For instance, one might learn:

  • When and what to eat to achieve the best performance in a marathon
  • Which foods consistently lead to a depressed or irritable mood
  • What patterns at work result in the most productive bursts of activity  

This increased interest in self-tracking has developed into the Quantified Self (QS) movement which aims is to make it easier for people to track the information – or data – in their daily lives (e.g. diet, air quality, mood, blood oxygen levels, etc.) and from this information this derive personal meaning. It’s part of what we call the future “data economy,” wherein people will be able to make their own data work for them, unlocking new insights and opportunities.  

QS has begun to get media attention as well, but more often than not the participants have been wrongly painted in an unfavorable light as narcissists on the fringes of society. Intel Labs ethnographer Dawn Nafus, our resident expert on this movement, challenges this view in a recent post to the official blog of the Committee on the Anthropology of Science, Technology, and Computing (CASTAC). In the blog, Dawn and her collaborator Jamie Sherman explain the motivations and challenges faced by this community as they struggle to get the right data from off-the-shelf sensors to better understand how to do things like maintain good fitness habits or just get a good night’s sleep. They argue that what appears to be egocentric behavior or gratuitous “geeking out” is really just symptom of people trying to make the best of our society’s inclination to try to make one-size-fit-all in terms of solutions for wellness.

Traditional heath regimens are often based on broad studies that statistically average out important person-to-person variations. What people really need, ultimately, is a better relationship with that data.  This could take the form of personalized health care, i.e. recommendations that take individuality into account like genome, health history, and lifestyle.  It could also take the form of self-discovery. Data can help us to understand things about our lives that no one else might think to investigate. What gives me energy? What triggers my allergies? These are matters of personal context, and data can help us decide what daily patterns should (or should not) be changed. Far from a fringe, the QS members are at the leading edge of our future data society. They are trying to understand how to collect and make sense of data in way that works for them – and ultimately you.

Having participated in a QS-style experiment, I can vouch firsthand for the kinds of insights you can get from personal data. I learned, for instance, that the low-stress profile produced during mediation was very similar to that produced while jogging or when listening to a particular song (“Roads” by Portishead). This made me realize that I had multiple options available when I need to de-clutter my mind after a stressful day.

Intel Labs recognizes that your own data will become one of your most valuable assets. In order to foster this new data economy that allows a wider range of people to exchange benefit from such information (and control who it is shared with), Intel is conducting research to develop new innovations which support many citizen science movements, including QS. We’ll be sharing more developments in this and other aspects of our future data society over the coming months.

 

Sean Koehl

About Sean Koehl

Sean Koehl (@smkoehl) is a Vision Strategist for Intel Labs, the global research arm of Intel Corporation. He is responsible for crafting visions of how Intel R&D efforts could impact daily life in the future. He leverages insights from Intel’s technologists, social scientists, futurists, and business strategists to articulate how technology innovations and new user experiences could improve lives and society. Sean received a bachelor’s degree in Physics from Purdue University and launched his career at Intel in 1998. He has worn many hats in his career including those of an engineer, evangelist, writer, creative director, spokesperson, and strategist. He has led a variety of projects and events, authored numerous technology publications and blogs, and holds seven patents. He is based at Intel’s headquarters in Santa Clara, California.

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