Quantified Self and the Politics of Self-Tracking

Quantified Self and the Politics of Self-Tracking

The Quantified Self (QS) has been the topic of much discussion recently in tandem with the development of consumer tracking applications and services. QS is a global network of individuals who voluntarily track various aspects of their bodies and lives, most often with digital and wearable technologies. If an aspect of the self can be counted, it's probably been tracked by a member of the QS community. The motivation is self knowledge and the means is numerical data.

QS technologies include smartphone lifelogging apps, health and fitness trackers like Fitbit and Apple Healthkit, EEG devices, home biomarker testing kits and quite often, spreadsheets, among other things. Typical QS projects track steps, nutrition, mood and sleep. However, a rare project will surface now and then that interrogates such things like how often a self tracker's values were exercised on a daily basis, the extent of a person's material consumption, or even conversations and things heard over a decade, in the form of a searchable database!

In this HASTAC forum, we explore a community at the intersection of posthuman and transhumanist futures, as well as contemporary debates around digital health, surveillance and self governance. Through the forum, we hope to tackle some of the tough questions and challenges facing the quantified self community, including the politics of self-surveillance, the notions of data, identity, and agency inherent in QS practices, and its efforts towards subverting institutionalized knowledge production and reforming institutionalized medicine.

Forum Hosts:

  • Meena Natarajan, PhD Candidate, UC Berkeley School of Information
  • Neal Swisher, Ph.D. Candidate, Virginia Commonwealth University
  • J.J. Sylvia, Ph.D. Student, North Carolina State University
  • Jason Tham, Ph.D. Student, University of Minnesota

Confirmed Guests:

  • Gary Wolf, Co-founder of QS, founding editor of Wired Magazine
  • Dawn Nafus, Anthropologist, Intel
  • Ernesto Ramirez, Program Director, QS Labs
  • Deborah Lupton, Professor at University of Canberra, Arts & Design Department
  • Natasha Dow Schüll, Associate Professor at MIT's Program in Science, Technology, and Society

Initial Questions:

  • What kind of “self” is practiced through personal data collection? Is the “self” a good way to discuss what QS is all about, and if so, what does QS aim to learn about the self? Does QS engage with the expansive humanities literature about selfhood and subjectivity? For Foucault and countless other scholars, forms of subjectivity are partly created by scientific investigations which produce categories of people, which are thereafter naturalized (and subjectively experienced) as “real.” Does QS manage to escape this critique because it deals with individuals, not populations? Or can we say that QS claims to investigate what it in fact produces (namely the “self” as a collection of data points?)
  • The QS privileges what is typically relegated in the data and computational cultures from which it emerges - the anecdote. It foregrounds the significance of the sample size of one. It contests traditional public health research because it believes that no one is an average. Yet, it most frequently tells the story of an individual through the language of quantification. What do numbers stand for in the QS? How do they help construct the self as data? What work do they do and to what ends?
  • Many QS meetups begin with the claim that it is the antithesis to big data. However, it attracts big data enthusiasts in large numbers. Big data researchers, often part of the emergent profession of data science, are interested in the possibilities of voluntary, in situ data collection and self surveillance of thousands of self trackers. What are the mechanisms through which QS subverts and big data co-opts? How are the goals of QS self trackers of achieving more personalized medical care dependent on collaborating with medical data science? What kind of precedence exists in medical history for similar dynamics and what could we learn from that history of negotiating both individual authority over one’s body, while also being able to see the self, the body, in relation to others?
  • Although many early QS tracking technologies were built by self trackers themselves, most QS tracking technologies today are designed by for-profit corporations and startups that the community refers to as “quantrepreneurs.” Raw data produced by their sensors and applications are stored on corporate servers, raising privacy concerns about who truly owns the data and how it might be used in the future. How do self trackers conceive of privacy? What kind of challenges do they face in their activism for greater access and control of their data? What kinds of precedence and norms do they set for individuals who do not and cannot self track?

16 comments

These are all really great points. Deborah, I wonder if the easy assimilation into big data analysis is also because, as Juana suggested, we haven't quite interrogated notions of data at play. Self trackers often produce just smaller versions of traditional forms of quantitative data, without necessarily creating or supporting other forms of evidence or challenging notions of data we've inherited, making it easy to co-opt what is produced. However, I also see an intent and desire to donate personal data to analysis on a larger scale, among many self trackers, especially in health tracking, as a sort of contribution to the greater good. The fact that it is collected outside of a lab setting and so much more consistently, makes it data that healthcare has not seen before. The promise is technologically mediated self care or more personalized care delivered by institutions/services, whose failure to do so currently is what led many individuals to self track health metrics in the first place. However, self tracking communities are not very diverse in terms of class, race or gender. Tracking devices are expensive. The security required to contest traditional power dynamics in a doctor's office is not available to everyone. As has been suggested, whose context, whose biology, whose social position, will be reinforced as the norm once again? And who gets left out of personalized care in the future as well?

In other forms of passive tracking where every identifiable data becomes personal as Neal and JJ point out, analytics goes into using all available data to construct a tracking experience that controls what appears like serendipitous encounters, a sort of delightful surprise that lets you know how you are cared for and understood by the technology. For example, a personalized recommendation for a restaurant through geofencing, an encounter with a friend who happens to be nearby, a suggestion that you should get more sleep. Sometimes, this fails but the rhetoric of good intention remains. 

Many times, there are real gains that people derive, especially in health. I am interested in this give and take and what the hastac community thinks about the allure of sharing personal information, the promises and the enhanced experiences. 

 

 

 

 

136

Hi hastac,

I have been doing fieldwork in the QS for two years now. My favorite part is hearing the kinds of things people track and what they learn. Even if you don't identify as a self tracker, you probably track a few things about yourself, maybe even with a device or an app. Self tracking as a practice is nothing new, we all do it in some form or the other, but what is interesting about the QS, is how a global community has been built around the idea of self knowledge through tracking and numbers. A key part of this community building is the QS show and tell. They are public presentations where people share their tracking story while answering three questions. What did you do? How did you do it? What did you learn?

Does anyone have a tracking project or an idea for one they would like to share/workshop? Or anything else you would like to add/ ask about the QS?

:)

 

 

 

115

Hi Meena!

 

First of all, thanks for putting this forum together. Even if there are only a few “Quantified-Selfers” among us— self-tracking, personal analytics (whatever you want to call it) affects us all.

 

Whether we like it or not, our devices are tracking us. If you have an iPhone, the “Health” app tracks your daily step count by default.

 

I started tracking my location data last year with an iPhone app called “Open Paths.” Its free, and the location data (based on wifi triangulation) is stored safely and only you have access to it. I was able to place this data on a map with Google’s Fusion Tables.

 

What I saw in the map was an incredibly accurate picture of my life. And I thought it was fascinating that, even without giving Open Paths any personal information about myself, anyone looking at this map could have a pretty decent guess as to: where I live (i.e. where I returned to every night), and where I work (i.e. where I traveled to every week day).

 

Here’s a question: how do we define “personal information?” If my data-trail (searches, location, activity, behavioral patterns) is unique to me and could be used to identify me, is there any data today that we can truly say is NOT personal?

117

Neal -- 

I'm really interested in this idea of what personal information means for both individuals and society. I've been trying to approach it from different directions like privacy (the recent focus of the White House), power (Mark Andrejevic), and also intimacy (Nicole DeWandre). I think you're correct in your hunch that all data really is personal now, so for me, that opens up the question of how we want to share it and with whom. Does privacy, power, intimacy, or even something else entirely make the most sense for understanding this shift? 

110

My apologies, Juana, I was unfamiliar with the format! I will do my best to find another way to respond to the questions.

97

Meena this is a really fascinating topic, and I appreciate how you are framing these questions in terms of questions of relationsality, the body, and how we understand data.  And more to the point how do we conceive of a self through and against these technologies of capture.

Neal and J.J.'s comments seem to get at the core of so much that is compelling about this as a field of inquiry, precisely because of the ways we are all implicated, The idea that somehow we could opt out if we wanted to part of the fiction operating--if we could just figure out those pesky privacy settings we would be fine!

Paul--it seems you are new to HASTAC, this is a forum for intellectual engagement and inquiry, and parts of your comment just seem gossip-y and frankly pretty offensive. I suggest that you limit your comments to the topic.  Meena already gave us such a rich set of questions--I hope we can focus our online discussion on these.

Following up on Meena's questions about how this constructs a data point of one, and how it contructs the very idea of subjectivity, I am curious about the ways these QS instruments leave uninterrogated the very metrics they use, as if we have all agreed on what constitutes a reasonable measurement of data. How does the knowledge that is being produced already adhere to what we understand as measurable, quantifiable, and useful?

122

For me, one of the most interesting issues about contemporary practices of quantifying the self (or what I call 'reflexive self-monitoring') is the ways that 'small' data now almost inevitably become 'big' data when people's personal information is contributed to cloud computing archives. Once this happens, people lose control of their data as they enter the digital data knowledge economy and are circulated and repurposed by others. There are major political implications here for how personal data may come to influence life chances and opportunities that people are offered, for example in getting access to insurance, credit and employment.

96

For me, one of the most interesting issues about contemporary practices of quantifying the self (or what I call 'reflexive self-monitoring') is the ways that 'small' data now almost inevitably become 'big' data when people's personal information is contributed to cloud computing archives. Once this happens, people lose control of their data as they enter the digital data knowledge economy and are circulated and repurposed by others. There are major political implications here for how personal data may come to influence life chances and opportunities that people are offered, for example in getting access to insurance, credit and employment.

116

So I realize this is a bit of an aside, but also speaks to what Deborah is addressing--I was wondering what folks thought about the idea of police wearing body cameras. It is being thought of as a way to document and perhaps prevent police abuse, or at least record interactions between the state and individuals who encounter law enforcement.  But it also seems like this major data trove--a way of collecting huge amounts of data on individuals that in many ways are being targeted by the state because of race and poverty. So we can imagine the police filming in someone's house, their bedroom, their car, their bathroom. The data would of course include voice recordings, an archive of gestures, facial expressions, as well as what we wear, where and how we live, the colors we use in our homes, what we eat for breakfast. And of course, the cop is the one waering it--so we won't see what his face is doing, or be able to see his body posture or where his hands are--the camera will function as the eye of the state...

 

125

So I realize this is a bit of an aside, but also speaks to what Deborah is addressing--I was wondering what folks thought about the idea of police wearing body cameras. It is being thought of as a way to document and perhaps prevent police abuse, or at least record interactions between the state and individuals who encounter law enforcement.  But it also seems like this major data trove--a way of collecting huge amounts of data on individuals that in many ways are being targeted by the state because of race and poverty. So we can imagine the police filming in someone's house, their bedroom, their car, their bathroom. The data would of course include voice recordings, an archive of gestures, facial expressions, as well as what we wear, where and how we live, the colors we use in our homes, what we eat for breakfast. And of course, the cop is the one waering it--so we won't see what his face is doing, or be able to see his body posture or where his hands are--the camera will function as the eye of the state...

 

106

So I realize this is a bit of an aside, but also speaks to what Deborah is addressing--I was wondering what folks thought about the idea of police wearing body cameras. It is being thought of as a way to document and perhaps prevent police abuse, or at least record interactions between the state and individuals who encounter law enforcement.  But it also seems like this major data trove--a way of collecting huge amounts of data on individuals that in many ways are being targeted by the state because of race and poverty. So we can imagine the police filming in someone's house, their bedroom, their car, their bathroom. The data would of course include voice recordings, an archive of gestures, facial expressions, as well as what we wear, where and how we live, the colors we use in our homes, what we eat for breakfast. And of course, the cop is the one waering it--so we won't see what his face is doing, or be able to see his body posture or where his hands are--the camera will function as the eye of the state...

 

97

Juana, you might be interested in the idea of sousveillance, a term that Steve Mann introduced in the 90s (I think) while exploring the possibilities of wearable technologies for personal research and counter surveillance. His idea was that everyday people could also watch power and authority through body borne cameras. The critical privacy debate around sousveillance seems only emergent.  

In my own QS fieldwork, I have seen some people use Memoto or the Narrative clip as a form of lifelogging, although I am not certain their intent is resistance, rather another way to capture aspects of their daily life towards a personal archival project. I remember QS trying to unpack notions of consent, privacy and ways to resist lifelogging in the 2013 conference. I did hear "don't lifelog me" said quite often. However, if adopted and used as a form of research into power, I am wondering how it may place the burden of proof, once again on those who are marginalized. I am curious about what Hastac thinks about the ethics at play here and how these technologies intersect with different marginalities and social positions. 

Wearable cameras for sousveillance over the years:

Pictures of technologies for sousveillance from 1998 to 2013

 

 

105

There are two issues I think are worth bearing in mind. One is that not all data is instantly interoperable with all other data. It doesn’t really go off into “the cloud” (a term of obfuscation if ever there was one), but to specific institutions who cohere it in particular ways that reflect institutional relationships. That’s why projects like Open mHealth exist—the pipes aren’t enough to get the data flowing.  The amount of work it takes to even make data commensurable is enormous. That’s a problem if what you think you are doing benefits the public in some way, and an inadvertent ‘solution’ if you think the problem is too much institutional access to data. Still, I do take Meena’s/Deborah’s/Neal’s comments to mean that meaningful control can be taken away pretty darn quick (and with market consolidation, even quicker).  Those harms that Deborah mentioned are real—we’re seeing it with “enhanced” credit scoring now.  Creating incommensurability can be a form of data obfuscation, though perhaps a weapon of the weak in some ways. The good news there is, you are on your own. The bad news is, you are on your own-- it’s harder to leverage what others have found useful to measure.   

 

The second issue, then, is what it would take to re-assert more equitable control over where data goes and what it does. Many people here will have thought deeply about personhood/the ‘self’ as something that never really had beginnings or endings except as a kind of social form. There are many traditions here to draw from—the question of self makes me recall my grad school obsession with the Russian word for “individual” or “personality” (lichnost’)—a Stalin era invention if you can believe it! It predates by some decades any recognizable notion of a ‘private sphere’, which to this day doesn’t mean what it means in English.  Because the social sciences/humanities don’t work from a naturalized, taken for granted figure of the self, we can look closely at the  self in data and the relations in which both travel. That means that we could do a pretty good job of exploring what kind of a design would we actually need for data-havers to reassert some control over where their data goes and what gets done with it. Open Paths has a pretty good model to start—users get to yay or nay any project that wants to use their data-- but there is so much more we could do here.  What would a Strathernian set of data controls look like, for example? What if we were to use Trebor Scholtz’s ideas about cooperative digital labor to think about data access? Our theoretical and conceptual bench is pretty deep here.

96

Hopefully I am not too late to the party. I have been teaching first-year writing for awhile now, and having done some research and deployment with Google Glass this year, I am wondering how we might design/develop a writing/general humanities course around personal-big data (responding to Deborah Lupton's "small" and "big" data comments) -- inviting students to think critically and rhetorically about generating, monitoring, and sharing personal information. 

Further, I am interested in the kinds of technology that we could bring into the classroom to demonstrate what personal data are quantified, how they are quantified, and what we could make of the quantified information. Are wearable devices the technology to turn to? What are the stakes involved in exposing students to such practice? The risks and rewards of quantifying the classroom?

107

In my work recently I have been thinking through how digital self-tracking practices may be used in more politically resistant ways. We already have citizen science/sensing initiatives for environmental monitoring of local areas, but what about other political uses? Can fat activists use self-tracking data to demonstrate that they are not lazy and diseased, as the dominant discourses would have it? Can exploited workers use self-tracking data to demonstrate to authorities how their employers over-work and under-pay them? Any other suggestions?

116

Last minute:

Manuscript proposals are being solicited for a special issue of IEEE Transactions on Learning Technologies (Impact Factor: 1.22) on "Wearable Technologies and the Internet of Things in Education and Training".

The deadline for the submission of proposals (500-word extended abstracts plus 8-10 key references in IEEE format) is June 15, 2015. The authors of shortlisted proposals will have until the end of September 2015 to submit their full manuscripts.

The Call for Papers is available at the following URL: http://goo.gl/R9l9yo.

102