Tracking our interactions :: measuring attention, socializing, and our environment.

July 11, 2011

Recently, Technology Review invited me to do a guest post on one of their blogs as part of their feature, “The Measured Life.” I chose to engage a claim I saw on Ethan Zuckerman’s blog — that at the QS Conference, it seemed that “quantified self” = “quantified health.” He asked about mood, attention, emotions — other parts of our self beyond the physical body.

This point resonated with me quite a lot — that what’s interesting about the quantified self isn’t just the democratization of established physical measures, but also the creation of new ones to help us understand parts of ourselves that we don’t know how to measure yet. After the jump is the blog post I wrote for Technology Review — looking at current examples of tracking that cover parts of the self — our attention, communication, and environment — that go beyond the physical body.



Many of the new instruments of the Quantified Self increase our personal capacity to measure our bodies. A $200 Zeo can do much of the analysis that formerly could only be done in a $2,000 a night sleep lab. The $99 Fitbit can tell you not just how much you exercised, but how many steps you took and how many calories you burned. Tools to measure our bodies are becoming cheap and commonplace.

But I think an even bigger shift could come from tools that will give us new measures and new ways of knowing ourselves beyond our bodies. Our attention will become a common thing to track: how do we handle our mental real estate amidst the “information overload” of the Internet? Our socializing will become another — how do we manage close relationships and intimacy in an era of unprecedented social connections? And our physical environment will be a third – what is the environmental health of our home, work, and city?


One of the interesting questions of the Internet era is how to preserve focus and keep attention from fragmenting. But the internet (and computers more broadly) also provide the means for tracking our attention more closely than ever before.

Most current efforts to track attention are focused on charting what you do as a way to become aware of where your attention is going. Tools like RescueTime automatically log what’s happening on your computer as a way to measure productivity, but I don’t think just knowing *what* you’re doing is enough. In my own usage of RescueTime, I’ve noticed that sometimes, three hours of email in a day is par for the course of successfully organizing an event, and sometimes it’s a telltale sign of anxious procrastination. New tools could help make this kind of distinction; perhaps by measuring how often someone switches tasks or channels — a stab at measuring attention span — or how quickly they flip through tabs in a browser.


Another major concern in the Internet era is understanding how to manage the explosion of new relationships and related communication. In her book Alone Together, MIT professor Sherry Turkle points out that we can mistake connectedness for intimacy, and Facebook friends for real ones. Similar to attention, to better understand ourselves, we need to know not just what relationships we have, but how to devise ways to understand their quality.

One way to understand these relationships is to zoom out from the day to day patterns and look at the broader patterns over the years. This occurred to me after trying out Cataphora’s Digital Mirror, a product which uses linguistic context tools to analyze your email and present you with data about how you communicate. One feature is its ability to create a piechart of which people you spent the most time with throughout your email’s history, as determined by clues for scheduling meetings in real life.

I had this done for the past five years of my email, and Digital Mirror produced a simple visualization of my relationships over that time. The names of partners, collaborators, and friends came and went. It felt like a sort of nostalgic, digital scrapbook — making it easy to remember those parts of my life, being reminded of who I used to spend time with.

Another way to understand our communication comes not from the long-term perspective, but getting better analytics and measures of our day-to-day communication. Anmol Madan, cofounder of, has shown that he could infer with 90 percent accuracy when people are sick based on smartphone data alone — cell phone use, texting, and GPS data. At first the inference sounds like magic, but when people are sick, they unsurprisingly tend to stay in one place and not talk on their phone. Insight like these show that there’s much more meaning to be made of our communication patterns. It’s possible that we’ll one day have measures as basic and essential as heart rate or blood pressure for our communication data.


Our personal environments are incredibly complex, and it’s difficult to figure out whether common suggestions for improving our physical environment– like drinking filtered water — will have a significant or even noticeable impact on health. At the same time, studies implicate the environment heavily in our physical well-being; research suggests that five of the six problems that pediatricians spend most of their time on (childhood cancers, asthma, developmental delays, obesity, and diabetes) are significantly correlated to environmental factors.

Tools for tracking environmental factors are beginning to appear, such as this visualization of air quality in a room created by the Public Laboratory in collaboration with RISD. It was made by strapping a particulate sensor and color changing LED to an autonomous Roomba, and then taking an open shutter image of the Roomba, and capturing where the light changed color. Tools like these begin to help us be aware of what we’re normally not seeing that does affect us.

In a different direction, Edison Thomaz put a sensor on his water faucet to sense the water pressure in his home. A single sensor could measure the water pressure through all the faucets, which revealed a surprising amount of information: did the residents eat at home or go out to eat that night? Were people waking up in the middle of the night to use the bathroom? This corresponds more to the use of the environment than to the health of the environment, but was striking to me in that only one data source could yield so many behavioral inferences.

Right now self-quantification has a sense of geeky overload: obsessive-compulsive technology that could keep you from living a normal life. But I think one of the exciting prospects for this trend is the tools and measures that we don’t know about yet, the development of a human dashboard. Just as we wouldn’t buy a car without a fuel gauge, it could be that new personal metrics will dawn in the next few years that will seem as commonplace as height and weight do to us now. These metrics could be things that let us understand our selves — emotional, social, psychological, as well as physical — better, helping us become more human, not less.


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