The concept of the ‘quantified self’ has become the focus of global interest. Less acknowledged is the emergence of a range of technological devices and apps designed specifically for children to track, monitor and analyze data about their health, bodies and well-being. What are the issues raised by these technologies of the quantified self for kids?
Emergence of the ‘Quantified Self’
In the last five years, there has been a sharp growth in the popularity of health data collection devices and apps for use in everyday life. The idea of a ‘quantified self’ first emerged through the launch of the Quantified Self web community in 2008 (founded by two former Wired editors). Focused on the ideal of ‘self-knowledge through numbers,’ self-quantifiers use statistical data from self-tracking devices and apps to understand their personal health, and on that basis, to modify and optimize their health behaviors. According to cofounder Gary Wolf, the ‘data-driven life’ represented by the quantified self movement came about through the convergence of four developments: the miniaturization and automation of electronic sensors; the ubiquity of mobile computing devices and smart phones; the normalization of sharing through social media; and the emergence of a ‘global superintelligence’ enabled by cloud connectivity.
The ‘quantified self’ has since become a tag applied to those individuals and communities that use health tracking devices and apps for various practices of ‘lifelogging,’ ‘lifestreaming,’ ‘personal experimentation,’ and ‘digital autobiography.’ Everyday digital health tracking devices include a variety of sensors, accelerometers, pedometers, GPS devices, and wi-fi or Bluetooth enabled clothing and household items. Some researchers describe an emerging ‘sensor mania’ with personal health tracking technologies part of a vast interconnected ‘Internet of Things.’
Twinned with these devices, a huge range of apps to support user-led health data collection is available via the web. Apps are available to track food and drink intake, mood and emotion, physical activity and workouts of all kinds, sleep, inactivity, and more. These apps allow users to interpret and visualize the health data collected through tracking technologies, and to use these data to inform and optimize their health behavior choices. Some health tracking apps also feature built-in ‘personal analytics,’ capacities that permit users to generate fine-grained data about their own health, dietary and physical activities. Jawbone Up, for example, features an ‘insights engine’ that uses analytics techniques driven by specific algorithms to reveal hidden connections between different data such as diet and sleep. Likewise, TicTrac allows users to ‘sync’ all their tracking activities using its ‘Discovery Engine,’ while the Reporter App combines self-tracking with survey questions and automated prompts, aiming to make automated measurement and manual survey input into a simple process for users to build self-understanding through ‘self-ethnography’ or ‘self-science.’
Beyond its technical elements, a distinctive cultural discourse has sprung up around these health-tracking apps. The emphasis is placed on setting personal goals and challenges, ‘life projects,’ personal discovery, receiving motivational prompts and nudges, being rewarded for meeting or beating goals, and on using insights gained from data to make healthy lifestyle choices. Some social science researchers are beginning to suggest that self-quantification is an emerging mixture of social science methods, digital tracking, social networking, and the ‘start-up’ discourse associated with Silicon Valley entrepreneurship.
Quantified Child
There now is some evidence of self-tracking and quantification taking off with children. Within the Quantified Self community itself, there are some emerging indications of ‘quantified child’ activities mobilizing self-tracking technologies and techniques, usually under parental guidance and often motivated by a concern to better understand and manage a child’s illness. A number of commercial child-tracking devices and applications have been launched to allow parents to generate knowledge about their child’s health. These include sensor-enabled ‘smart diapers’ to enable urine analysis and identify health patterns and ‘smart baby clothing’ activated with ‘sleep algorithms,’ temperature and respiratory sensors to continually monitor infant health.
Another emerging area is health-tracking apps for children, designed to encourage healthy lifestyles, aid dietary planning, and encourage physical activity. A range of apps, websites and multimedia games exist, the market represented well by the Apps for Healthy Kids competition, which awards prizes to the best health apps for children.
A popular feature of health-related apps for children is the concept of caring for virtual creatures by fulfilling their dietary and fitness needs. For example, Fitter Critters requires players to ‘care for’ and ‘nurture’ their creature by providing optimal nutrition, and to engage in physical exercise, which can be translated into the improved health of their creature. Creature-based apps such as Fitter Critters are a key focus for the ‘gamification’ of digital health among children. Gamification refers to the use of elements of gameplay to make real life more like a game and a form of pleasure. Many mainstream self-tracking devices and apps feature gamified elements, such as competing with others on specific physical activity challenges or racing to complete goals. Jennifer Whitson refers to gamification strategies in self-tracking as ‘pleasurable surveillance’ — a kind of self-monitoring and self-policing done voluntarily and for fun.
Gaming elements often are combined with online social media environments in self-quantification technologies for kids. For example, Zamzee consists of a wearable physical activity meter twinned with a social media experience and personalizable avatar, as well as facilities for accessing individual activity graphs, online leaderboards, sending status updates, and earning virtual currencies.
Another hybrid health gaming/social media platform for children is Sqord, which consists of a wearable data logger, an online social media environment and a personalizable on-screen avatar called a PowerMe. Sqord is marketed as ‘one part social media, one part game platform, and one part fitness tracker.’ Users compete on a leaderboard through everyday physical challenges, and are able to win medals and ‘sqoins’ as rewards for completion of goals which can be used to purchase ‘upgrades’ and further PowerMe personalizations. The Sqord social media environment promotes peer competition as a motivational technique. Sqord also provides an administrative reporting tool for educators to access metrics on the physical activity levels and participation of each child player.
Issues in Child Self-quantification
Some social science researchers have begun to identify possible ethical, commercial and social implications associated with using health-tracking technologies with children, perhaps most obviously, surveillance and privacy issues raised by the automated collection and storage of children’s health data.
A major issue concerns the data itself. Self-quantification practices mobilize techniques of data analysis that appear to provide an ‘objectively’ real account of the human body that unmediated haptic perception cannot. Some researchers have acknowledged, however, that a quantified ‘data self’ is mediated by algorithms and physiological models that often contain normalizing biases. Metricization and algorithmic calculation of health data do not produce neutral, objective sources of knowledge, but construct a ‘data double’ — a decorporealized digital version of a person constructed out of traces of their activities and abstracted into data visualizations, composities of information, and representations. Rendered in numbers and visualizations, your ‘data double,’ then, becomes a source of interaction with a mediated version of yourself. Through self-quantification methods, children are encouraged to experience themselves through their data doppelgangers rather than through their sensory experiences.
The disembodied data double matters because it exerts real effects. It can profoundly alter how children and young people reflect on themselves and their daily lives, and shape how they act to change their bodies and their minds. There are value judgments embedded in self-tracking tools, particularly how they are programmed to reward some activities and not others. Programmed with the capacity to tweak, nudge and configure users’ behavior, self-quantification algorithms are increasingly directing people’s behavior, even though the data on which their directions are based may be partial, incomplete and inaccurate.
Technologies of the quantified self, thus, appear to augment, or even substitute for, the body’s sensory capacities and embodied knowledge. As Deborah Lupton has argued, though self-tracking bodies are represented merely as ‘nodes’ in the ‘Internet of Things,’ exchanging data with other bodies as well as with other objects and devices through networked communication and informational infrastructures:
The body in this discourse becomes positioned as a ‘smart machine’ linked with other ‘smart machines.’ Bodily sensations become phenomena that are mediated and augmented through machines, transformed into data and then communicated back to the user. This vision of the body as augmented via self-tracking devices present a digital cyborg, in which such devices not only become prosthetics of the body but extend the body into a network with other bodies and with objects.
Beyond these ‘cyborg’ concerns, there also are more subtle issues to do with the culture of self-quantification. The dominant cultural discourse around self-tracking is of goal-setting, personal life projects, and self-improvement, which tends to highlight the individual’s responsibility for the maintenance of one’s own health and body. It positions ill health, unhappiness and so on as personal failures of self-control rather than the complex outcome of social and environmental factors. As such, these personal analytics reflect normative assumptions, particularly those associated with the Silicon Valley culture of individualization, entrepreneurship, and health-conscious self-optimization, that have the power (albeit at a distance) to shape and configure how individuals manage their own lives. These issues beg the question, to what extent is it desirable to position children as ‘quantrepreneurial’ selves, incited to constantly calculate on themselves in terms of their disembodied data in order to optimize themselves as a personal project?
Banner image credit: John R. Hofmann Sr.
