Metrication of the Self

A soon-to-emerge recurring theme…

Also referred to as “datafication” by the authors of Big Data: A Revolution that Will Transform how we Live Work and Think, metrication can be defined as beginning to see all aspects of our lives as valuable data points and metrics against which to gauge our worth, success, and productivity, a relatively recent trend. Spurred on by technological advances, new tools of monitoring others such as plug-ins and cookies also allow us to track ourselves.

Using metrics to evaluate people is not a new concept–from birth we’re monitored against percentile growth charts by pediatricians and our anxious parents; once we’re of schooling age we are monitored and tracked by the government and school districts using grades and standardized testing–reducing our school performance to “valuable” numbers and the odd, coded comment like “works hard in class”. After graduation and/or college, it could be over, but the working world possesses its own set of metrics. At my own job we track all sorts of data related to customer satisfaction, in addition to how quickly and efficiently we serve our users. This is consistently relayed back to us as workers, with the implicit intent of improving those numbers. The higher the better.

However, the advent of the Internet, and the cookies and plug-in data that it carries with it, has allowed and enabled this metrication to flood into our personal lives. In this way it is a personalization of metrics, _however_the metrics are not personalized in a manner of control. Like the previously discussed metrics, cookies and plug-ins collect all manner of data without your knowledge and in oft-difficult to monitor ways. They are personal metrics because they monitor your personal behavior.

Some of it is voluntary tracking and metrication, like that engaged in by Nike + users, or Last.FM users (to be discussed in a future post). Some of it is more implicitly gathered, in the terms of service of various sites that users typically engage with, like Facebook and Gmail. And even more of it is gathered and inaccessible to the user providing it, like electronics systems in cars that spit out near-indecipherable codes, as well as pacemaker and insulin pump data, locked down by the manufacturers in most cases.

One interesting plug-in to examine is called TimeStats, which tracks your website history and monitors how long you spend on various sites. It purportedly exists as a productivity-enhancing plug-in, but to have it installed on a personal computer, as I do, serves more as a method of monitoring ones own casual web activity.

For instance, this chart reflects my overall internet usage from May 16, 2012, when I installed the plug-in, to today, April 20, 2013.

Internet usage from May 2012-April 2013

In April I had 2 conferences and graduated from college, so I was too busy to be online much. However, in June through most of August, I was unemployed, so my internet usage skyrocketed.

If you dig further into the patterns, some fun trends emerge:

Time spent on idealist.org

Time spent on craigslist.org

I spent my summer unemployed, so I looked for jobs. One of the sites I used was www.idealist.org. However, once I got employed, I moved out to Michigan two weeks later and stayed with friends. The first three weeks of my time here, I was living with friends and I finally was able to move into a new apartment (that I yes, found on craigslist). But that was a short term situation and soon I needed to find another place–hence the smaller blips later on. Last month, I bought a couch, so I perused the site again.

Seemingly inconsequential data, when narrativized, gains some meaning. And perhaps that is one thing to be gained by collecting and tracking data on our actions on the internet–we create personal records of our experiences in unexpected ways.

Which should be valued more? The quantified and metricated self, or the narrativized and existent being? As big data (or micro data, as depicted here) are treated as eminently valuable, we risk becoming anonymized data points to be manipulated by corporations.