Farzana Dudwhala is postdoctoral researcher in the Health Experience Research Group's Digital Health Team. She is currently part of the INQUIRE project team, trying to understand how online patient feedback and experiences may be used to improve the quality of NHS services.
...simply saying that one went for a run, was not thought to be as convincing as being able to ‘show’ that one went for a run, using graphs and charts illustrating metrics like average pace, heart rate and distance.
We live in a curious society. Not only because we are a strange species, but because we are inherently eager to learn more about our society and our selves. This is true of both those of us formally researching society, and also of those in society whom we are researching. People are increasingly turning to technologies to track, measure, and record themselves, for the purposes of finding out more about who they are and what they do. Quality of sleep is being monitored by wearing sleep bands, blood sugar levels are being tracked using blood-glucose monitors, activities are being recorded using pedometers and GPS watches, and emotional states are being analysed using heart-rate variability devices. To make sense of how these technologies affect the self and society, I spent four years ethnographically analysing the ‘Quantified Self’ group, a group where people come together to share stories and experiences about their practices of self-quantification.
Are these technologies just recording and measuring who we are – simply tracking our behaviour and merely representing us via the resulting numbers and visualisations? Well, this research would be pretty uninteresting if the answer was yes! As has been argued many times, by economists and quantum physicists alike, the very act of measurement changes the nature of the thing that is being measured. The same can also be said for the case of self-quantification. The use of technologies to track and measure the self changes the very nature of the self and its behaviours. These technologies are not merely representing or recording the self, but are actively complicit in producing the self as it is being measured, and consequently in changing the behaviour of the measurer. Understanding how these technologies have a bearing on the self is therefore paramount.
Think about this for a moment: a CEO of a company that I met told me that he usually went for a run to de-stress from a hard day at the office. He had recently downloaded an application on his phone to track the speed and distance of his runs. After one particularly stressful day at work, he decided to go for his usual run. He put on his trainers and grabbed his phone to track the run via this application. A few metres into the run, however, his phone ran out of battery. Rather than continue with the run, he turned around to go back home, he put his phone on charge, and watched TV instead! He told me that it would have been a ‘wasted run’ if it wasn’t tracked and recorded. What happened here? How did the need to record the activity supersede his tried-and-tested method of de-stressing?
I found that simply saying that one went for a run, was not thought to be as convincing as being able to ‘show’ that one went for a run, using graphs and charts illustrating metrics like average pace, heart rate and distance. It is apparent, therefore, that the recording of an activity and the resulting visualisations enable the self-quantifier to have a new way of being able to communicate themselves with other people. Moreover, it seems as though these data-visualisations allow the self-quantifier to see things that may otherwise have been unknowable through instincts or intuition alone. A weight-loss of 100g in a day, for example, is difficult to notice in the mirror, but much easier to ‘see’ when plotted on a daily graph showing a downward trend.
This ‘seeing’ is not only important for the person that is doing the quantifying, it is also important for those with whom this person communicates. Here, others are invited to participate in the production of the self in question by including them in the negotiations of what the visualisation may even be revealing about the self, be this the-self-that-has-lost-weight, the-self-that-has-diabetes, or the-self-that-is-stressed. The inclusion of the audience in the narrative of the self is thus one of the most important aspects of data-visualisations in practices of self-quantification.
Paradoxically, therefore, in trying to show the individuality and uniqueness of their particular self, the person engaged in practices of self-quantification ends up measuring similar metrics to others in the group, presenting these metrics using similar visualisations, and adopting very similar language to communicate these. Through practices of self-quantification, the ‘self’ becomes a communal achievement.
To be an individual here, depends on being part of a collective, and the collective is enacted during the communal achievement of seeing and producing the self through numbers and the resulting data visualisations. In this context at least, curiosity didn’t kill the cat, it created a community of quantified-selves!
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