When we think of tracking progress or recording activity we tend to think in terms of broad scale metrics like corporate profits, high school graduation rates, or the health of an overall population — tracking the progress of an individual isn’t as common. How healthy is one individual? How much money is one person spending on a daily basis? These are questions that self-tracking could help answer, and ultimately, provide individuals with useful information about their own behavior and habits.
The Quantified Self (QS) movement is giving a whole new meaning to the phrase “Know Thyself”. The QS website, which serves a hub for connecting self-trackers across the globe, was established by Wired co-founder Kevin Kelly and contributing editor, Gary Wolf. As of today, there are more than 13,000 members of Quantified Self Meetups taking place worldwide — from Palo Alto to Buenos Aires.
If you are just starting out with self-tracking, or are curious to see if it will be useful for you, you’re probably wondering what type of tools are available and how you’re meant to organize/visualize all this personal data. The map above (see interactive version here) was created by Rachelle DiGregorio, a self-proclaimed quantified self enthusiast. Rachelle says she wanted to make something for beginners and curious individuals to learn about what tools are out there:
I wanted to make something…that showed the entire landscape of self-tracking tools while also being accessible and useful for new trackers. The subway map model works well with the multi-genre nature of most tracking tools. It’s very common for one type of tracking to intersect with another, especially in the realms of fitness or location tracking. For example, Foodspotting is as much about location as it is about food.
If self-tracking tools become mainstream, and everybody begins quantifying their work, spending habits, health and social life, what could all of this data reveal? This is part of the larger task my generation faces: extracting meaning from all of the information we digest each day. Even Kevin Kelly, co-creator of the QS movement, says he doesn’t want to be drowning in numbers, he just wants to know what action he should take. MIT’s entrepreneurship blog reports on an interview with Kevin:
When Kevin puts the weather on TV he doesn’t really want to know the temperature or the pollen prediction. And he doesn’t even want the meteorologist to tell him if it’s going to rain. Kevin just wants to know if he should carry an umbrella that day. He doesn’t value the data as much as he does the analysis.
Critics of this self-monitoring movement raise important points about the actual, practical applications of self-collected data. Rob Dyke of HandiHealth argues:
The self-monitoring movement is just another manifestation of our profound self-absorption. When you measure something, presumably you have to react to it. Is the hope that this constant self-monitoring will change our behavior? My guess is that it will simply generate revenue and speaking opportunities for its aficionados and compost, but have little impact on public health.
Further, Jaspal Sandhu, a lecturer at UC Berkeley School of Public Health says that such tools might be useful for conducting studies, such as research studies with select groups of patients, like diabetics, but not so useful for consumer adoption because we don’t always know where this data will end up. “Not all companies are created equal”, he says. “Some may help us move forward on health goals we want to achieve, but there is always a risk when sharing so much data.”
Moreover, at some point when this data is combined, it will begin to reveal patterns and insights about aggregates of individuals. For example, a mobile app called Asthmapolis helps users track their individual triggers and symptoms through a sensor that is attached to an asthma inhaler. When a patient uses the inhaler at a specific time and location, the data is captured to reveal trends in trigger locations. If every asthma patient used this self-tracking system, entire cities could be mapped with information about pollution and air quality.
With aggregate data, we might learn more about the internal dynamics of a workplace, a neighborhood, or even a family, but we aren’t quite sure what to do with these insights, especially outside the realm of health. Without a clear vision of what type of value this data can provide, we can’t expect everyone to opt-in to self tracking so easily. There are already problems that arise from tracking individuals’ behavior on the internet, so how will consumers be convinced that tracking their every step is useful? Rachelle suggests the two may be related:
People’s comfort with self-tracking may increase their comfort with being tracked by Google, Facebook, etc. As people feel the real benefits of more data in their own lives, they may be more willing to give up a certain amount of privacy to see those benefits in web services.
These struggles over data ownership and privacy will only continue to grow as more more and innovators enter into this newly developing self-tracking market. New market research projects that the mobile device sensor market will be valued at $1.2 billion by the end of 2012 and reach $2.8 billion in 2017 ! QS evangelists also predict the emergence of a “Data Commons” – a repository of individuals’ activity data from various streams. With such a Data Commons, users could choose to send their data into the repository to join the data streams of others, essentially opting in to be a data donor. As far fetched as this might all sound, the truth remains that data is the new currency. It’s time we start thinking deeply about the social and political implications of a quantified society.
- 5 personal data tracking innovations to watch (thenextweb.com)
- Tracking your body with technology (cnn.com)
- QS 2012 Roundup (quantifiedself.com)