There was a discussion going on in the IndieWeb Slack about quantified self. An interesting post called “the unquantified self” was mentioned. I skimmed over it and I just thought that I haven’t written an update on my quantified self projects in a while. I’m not feeling the best after the latest round of restrictions were announced in the UK. I hope this post will pull me out of my feelings a little bit and anchor me back to what I love doing with my time.
I have had an on-and-off relationship with quantified self for about two years. I started because I saw a few people create cool analyses of their personal data online. It was cool to see someone apply data analytics to their lives. I learn best when I am working on projects that mean something to me. Practical applications of code excite me; theoretical ones, not so much. This is not ideal because it relies on my having ideas. Nonetheless, that is how my mind seems to work.
I saw quantified self as a way to learn more about myself. More than that, I saw it as a way to refine my data analytics skills. I would not be learning about data analytics from a course. I tried that earlier this year and gave up. I would learn through my own data.
Setting Up Quantified Self
I used Exist.io to track my quantified self data. The tool has become popular for aggregating personal data and I didn’t want to reinvent the wheel. Unlike so many other of my interests, I wanted to start small and work my way into quantified self. I didn’t want to take on a massive project and burn myself out of this new interest before I’d had the chance to get to analyzing my data.
Exist.io worked for my purposes. I liked how all of my data was in one dashboard. I did not use features like correlations often. I enjoyed looking at my overall insights to see how I was doing. Because all of the data that I collected was passive, I’d never really taken any time to reflect on its use. I don’t usually check my Fitbit app. Exist brought my Fitbit statistics into one place alongside all my other metrics so I started to pay attention to them.
I set up quantified self with Fitbit, my iPhone, Dark Sky weather, and about seven or eight other services that Exist supports. The platform was generating correlations. I was definitely submitting enough data so that I could get some use from the platform. Though, I did not feel like I had a reason to keep checking Exist. I bookmarked Exist and I didn’t check it for a while.
The Downsides of Quantified Self
Every time I see people talk about quantified self, I get excited. I like seeing projects that people are working on. Maybe the problem is that I haven’t had a specific project in mind. Maybe, if I did track one data point and focus on that metric, I’d get more use out of quantified self. I presently believe that there are other issues that led me to give up on quantified self.
The first issue is the manual data collection involved with quantified self. While the metrics that apps like Fitbit and GitHub report are useful, they are not that interesting to me. Many of the data points I wanted to collect, like my caffeine consumption, involved manual data entry. This was burdensome. I have maintained an Airtable document with all the coffees I have had this year. I tried and failed to do a daily tracker to track my meat consumption and other metrics that I thought were important to me. Passive data is fine, but the real benefits accrue with manual data collection.
Quantified self did raise some privacy issues. I was not sure about how I felt giving away so much data to other companies. Fitbit is owned by Google. I assume there is some level of independence of data ownership between Google and Fitbit. However, Fitbit’s data practices will always have the potential to be influenced by Google. That is somewhat worrying.
The bigger issue was that I am not sure how comfortable I feel sharing my quantified self data. I started collecting quantified self data to refine my data analysis skills. I wanted to showcase what I had learned with the world. There was a voice that told me not to share information like my steps because it is really personal data. It’s not something that I need to share with the world.
I know that a lot of people are comfortable sharing their quantified self data. I’m still young and I do not have a high degree of conviction in the amount of privacy that I need to surrender to share my personal metrics in the public. I could track my data for my own use. As I said earlier, I struggled to keep up with manual data collection. There really was no incentive for me to keep going and to build tools to support my tracking.
Quantified self did not teach me much about myself. I did not change my financial habits after analyzing my finances. I did not set new exercise goals after looking at my historical Fitbit data. I generated a few nice graphs and learned a bit about data analysis. I’m happy I experiemented with quantified self. I may come back to it at some point. For a moment while writing this article, and you may be able to tell this, I actually started to doubt whether I gave up on quantified self too early. I do not have a firm position either way.
Quantified self data pushed me to adopt behaviors that were unnatural. Tracking various aspects of my life, while interesting, was tedious at the best of times. If I have a bad day, the last thing I want to do is track metrics about myself. I am already battling the mental burden of everything that is going on in the world. Quantified self seems somewhat of a step too far. That’s not to say that quantified self cannot be useful. I am sure there are many people out there actively learning from the data they collect.
For me, right now, quantified self does not make sense. It’s still cool to see quantified self projects in the wild. Lillian Karabaic and Aaron Parecki’s projects have been particularly inspiring. The Quantified Self website is a hotbed of resources on interesting projects. I wonder if I’ll ever revisit quantified self.