Digital risk society

An excerpt from a chapter I wrote for The Routledge Handbook of Risk Studies (2016). This is the introduction to the chapter. The pre-print of the full chapter is available open access here.

As social life and social institutions have become experienced and managed via novel forms of digital technologies, and as both public and personal spaces as well as human bodies have become increasingly monitored by digital surveillance devices and sensors, a new field of risk inquiry has opened up in response to what might be termed ‘digital risk society’.  The intersections between risk and digital technologies operate in several ways. First, the phenomena and individuals that are identified as ‘risks’ or ‘risky’ are increasingly configured and reproduced via digital media, devices and software. These technologies act not only as mediators of risk but frequently are new sources of risk themselves. Second, various uses of digital technologies are often presented as posing risks to users. In a third major dimension, members of some social groups are positioned in the literature on the ‘digital divide’ as at particular risk of disadvantage in relation to communication, education, information or better employment opportunities because they lack access to or interest or skills in using online technologies.

These three dimensions of digital risk society require new sources of theorising risk that are able to understand and elucidate the ways in which digitisation and risk intersect to create risk representations, mentalities and practices. This chapter addresses each one of these major dimensions in turn. Before doing so, however, it is important to introduce some of the perspectives that may be productively employed to theorise digital risk society. This involves moving away from approaches that traditionally have dominated risk sociology and embracing the ideas of writers in such fields as digital sociology, internet studies, new media and communication and surveillance studies.

Death and dying online

I am currently completing my new book, entitled Digital Health: Critical Perspectives (to be published by Routledge early next year). One of the chapters focuses on the ways in which human bodies are portrayed in digital media. I wanted to write some paragraphs about digital representations of dying and dead bodies, but not much previous research that I can find has addressed this issue. There is a growing body of literature on how the dead are memorialised on social media, but very little about actual images of the dying and dead online. This is interesting in itself, given that death is such a taboo and often avoided subject.

Here is some material I have found and included in the chapter.

It is now possible for audiences to find images of death and dying at all phases of human life. The Visible Human Project developed by the US National Library of Medicine is one example of how dead human flesh has been rendered into a digital format and placed on the internet for all to view. The Visual Human Project used computer technologies to represent in fine detail the anatomical structure of male and female cadavers. Each body was cross-sectioned transversely from head to toe and images of the sections of their bodies using magnetic resonance imaging, computed tomography and anatomical images were uploaded to a computer website and can also be viewed at the National Museum of Health and Medicine in Washington DC.

Social media platforms host images of dead bodies and first-person accounts of dying. One example that created controversy in the news media was the Instagram account of an American pathologist. She posted hundreds of images of autopsied corpses on her account, claiming it to be a form of public education. Another website, Unidentified Dead Bodies, has been established in India as a public service to assist with the identification of corpses. It features images of the bodies and details about where they were found, asking viewers to contact police or the coroner in charge of the case with any information they may have about the dead people portrayed on the site. A Chicago medical examiner’s office has undertaken a similar exercise, posting photographs of unidentified bodies that have come in for examination on its website. Several other examples of this type of publication of images of corpses can be found online. Indeed, simply typing in ‘unidentified dead bodies’ into a search engine gives ready access to many of these images.

Some people who have confronted a fatal illness have blogged about their experiences, presenting a written portrayal of their last days, sometimes accompanied by images of their failing bodies. There are numerous videos posted on YouTube showing the end of  life stages of mortally ill people, death and after-death scenes posted by friends or family members of the dead. Many memorial blogs and YouTube videos feature parents mourning pregnancy loss and stillborn infants, often featuring images of the dead foetuses or infants (I discuss this in my book The Social Worlds of the Unborn).

These are the kind of accounts and images of the dying and dead human body that until the advent of the internet would have received little or no exposure. While bereaved people in the Victorian era often had photographs taken of dead relatives, especially babies and children (sometimes with the living relatives posing alongside them), these images were kept to the private domain. Some may find these images distasteful, ghoulish or confronting. Yet advocates see their publication as a positive move towards better knowledge of death and dying.

 

Twitter and health

Surprisingly little research by sociologists or media studies researchers has investigated how Twitter is used to discuss health and medical issues. Yet there are many interesting issues and topics to explore.

The Healthcare Hashtag Project operated by Symplur, a healthcare social media analytics company, provides a publicly available online resource that demonstrates the diversity of health and medical topics that are discussed on Twitter. When I checked the website in early May 2016, the Project had identified close to 13,000 healthcare topics, over 10,000 hashtags related to healthcare and almost 4,000 contributors to these discussions on Twitter. The diseases that were receiving attention on Twitter on that day included breast cancer, migraine, brain tumours, lymphoma, heart disease, diabetes, lung cancer, attention deficit disorder and leukaemia (these were the top ten trending diseases in order).

The site also shows the ‘influencers’ in the Twitter discussions it documents as well as the latest tweets related to the hashtags it collects. This information demonstrates the sheer diversity of actors who engage in discussions about medical conditions and healthcare on Twitter. The top ten (by mentions) ‘influencers’ for the hashtag #BCSM (denoting ‘breast cancer social media’) were a clinical professor in surgery, four individual breast cancer survivors, a medical school and a research institute, two patient coalitions (one for men with breast cancer and one for young women with breast cancer) and the Journal of the American Medical Association.

The story is quite different if the hashtag #digitalhealth is examined. Another market research company has analysed over 200,000 tweets and almost 30,000 engaged users to identify the top influencers and brands in Twitter discussions using #digitalhealth. The company looked at tweets using this hashtag over a period of four months spanning January to April 2016 and produced a list of the top 100 influencers (based on PageRank analytics that takes into account the number and quality of textual references).

The first four influencers listed (who gained much higher influence scores than any of the 96 others on the list), included Hungarian doctor, genomic scientist, digital health consultant and self-described ‘medical futurist’ Bertalan Mesko, followed by American John Nosta, another digital health consultant who runs his own think tank and is a member of the Google Health Advisory Board. A British health technologist, Alex Butler is next and fourth is American Paul Sonnier, another digital health consultant. These influencers are followed by more representatives of private digital health consulting or technology companies, some tech journalists and a representative from massive American pharmaceutical chain Walgreens. Academics are not well represented in the top 20: only three appear, beginning from number 13 on the list. Practising doctors and individual patients, or organisations for doctors or patients, are scarce.

The most common topics discussed by the top influencers were data (by a long way, accounting for a quarter of the tweets), the Internet of Things and wearable tech. The topics of apps, cancer, artificial intelligence, cybersecurity and telemedicine were the next-most discussed (however, they all received less than 10 per cent of discussion across the tweets).

It is evident from this report that digital health discussions on Twitter (at least those that use #digitalhealth to signify their content) are dominated by commercial and entrepreneurial interests rather than by the experiences of doctors or patients. With the exception of Susannah Fox from the US Department of Health and Human Services, spokespeople from government agencies appear to have little influence in these discussions. This is borne out by the list of top-most influential brands, which are again dominated by commercial enterprises (although the NHS England is included towards the bottom of the top 25).

These data raise some interesting questions for a digital health sociologist. How do voices other than commercial enterprises get heard on Twitter? What makes some conditions or diseases more talked about on Twitter than others? For example, why is breast cancer so prominent — is it because there are far more patient advocates and organisations for patients devoting attention to discussing this , or is it because it is a common form of cancer, or are other factors involved? Why do some practising doctors and medical specialists decide to get involved in Twitter discussions on a particular condition or a digital health technology? How do all the different actors engage with each other –- who pays attention to whom? What kinds of networks are formed between actors from the different groups who are advocates or healthcare providers or developers?

Pregnancy apps and gender stereotypes

Pregnant women and those experiencing the early years of motherhood have used online forums for many years to share experiences and seek information. Now there are hundreds of apps that have been designed for similar purposes. As part of an integrated research program looking at apps and other digital media for pregnancy and parenting, I have been researching these apps using several approaches. In a survey of 410 Australian women who were pregnant or who had given birth in the past three years, I found that almost three-quarters had used at least one pregnancy app, while half of the women who already had children reported using a parenting app (see here for an open access report on this survey and here for a journal article about it).

With Gareth Thomas from Cardiff University, I have also conducted a critical analysis of the content of pregnancy apps themselves. This involved analysing all pregnancy-related apps offered in the two major app stores, the Apple App Store and Google Play. We examined the app descriptions, looking for how the developers marketed their apps and what they offered. See here and here for articles that have been published from this analysis. Update: we have now published an article focusing on apps for expectant fathers here.

This study found that the apps designed for pregnant women represent pregnancy as a state in which women must maintain a high degree of vigilance over their own bodies and that of their foetuses. Many apps promoted this level of self-monitoring, often seeking to render the practices aesthetically-pleasing by using beautiful images of foetuses or allowing women to take ‘belfies’ (belly selfies) and share these on social media.

Among the most surprising of our findings were the large numbers of pregnancy-related games designed for entertainment. These include pregnancy pranks such as fake foetal ultrasounds to fool people into thinking someone is pregnant. We also found many games for little girls that are on the market. The encourage girls to give pregnant women ‘make-overs’ so that they will ‘feel more confident’ and look beautiful, ready for the birth. Some even let players perform a caesarean section on the characters, who remain glamorous and serene even on the operating table. The types of messages about pregnancy and childbirth that are promoted to their young female users are troubling.

Other apps are directed at men who are becoming fathers, although there were far fewer of these apps compared with those for pregnant women. We noticed from our analysis of these apps that even though quite a few of them are marketed as being written ‘by men, for men’, they typically portray the father as a bumbling fool, who requires simplistic or jokey information to keep him interested in the impending birth of his child. Men are advised not to stare at attractive women and to constantly reassure their partners that they find them attractive. Foetuses are compared to beer bottles so that men can learn about foetal development in supposedly unthreatening ways.

Our overall finding, therefore, is the highly stereotypical gendered representations of pregnant women and expectant fathers in these apps. Women are encouraged to use apps to achieve the ideal of the self-monitoring ‘good mother’, closely tracking their bodies because they have their foetus’s best interests at heart in every action they take. They are expected to celebrate their pregnancy and changing bodies – there is little room for ambivalence. Their male partners, on the other hand, are assumed to be uninterested and to require nudging to act in a supportive role to their partners.  And little girls are encouraged to accept and perpetuate the ‘yummy mummy’ stereotype in playing the pregnancy games that are marketed to them, and to view caesarean sections as a quick and easy way to give birth.

Living Digital Data research program

People’s encounters and entanglements with the personal digital data that they generate is a new and compelling area of research interest in this age of the ascendancy of digital data. Members of the public are now called upon to engage with a variety of forms of information about themselves and to confront the complexities of how these details are used by others. Personal digital data assemblages are configured as human bodies, digital devices, code, data, time and space come together.

 

Personal digital data assemblages smartart

Personal digital data assemblages

 

Over the past few years I have been researching the social aspects of personal digital data: how people understand and conceptualise these data, how they use their data, what people know about where their personal data go and how their data are used by second and third parties.I have analysed the metaphors that are used to describe digital data, the politics of digital data, the types of data that are collected by apps and self-tracking devices, how people use these software and devices and how personal digital data are materialised, or rendered into visualisations or three-dimensional objects. I have sought to theorise the ontology of personal digital data, drawing particularly sociomaterialism, feminist technoscience, cultural geography and sensory studies. (See My Recent Publications for further details.)

I am bringing these research questions together under a program that I have named ‘Living Digital Data’. This title builds on my conceptualisation of digital data as ‘lively’ in a number of ways.

 

 

Lively data smartart

Lively Data

 

 

The first element of the vitality of digital data relates to the ways in which they are generated and what happens thereafter. The personal digital information that is constantly generated contributes to data assemblages that are heterogeneous and dynamic, their character changing as more data points are added and others removed. Digital data may be described as having their own social lives as they circulate in the digital data economy and are purposed and repurposed. Second, digital data constitute forms of knowledge about human (and nonhuman) life itself and hence possess another type of vitality. Third, personal digital data have impacts on people’s lives, shaping the decisions and actions that people make and those that other people make about them.  The profiles constructed from these data can influence decisions about the opportunities people have to travel, access employment, credit or insurance, the people that they meet on online dating sites, the knowledges that they hold about themselves and their bodies and those of intimate others. Finally, personal digital data are forms of livelihoods, contributing to the commodification and capitalisation of information. Indeed, they may be described as a form of biocapital, which possesses many forms of value beyond the personal: for research, commercial, security, managerial and governmental agencies.

This approach recognises the entanglements of personal digital data assemblages with human action. Not only are personal digital data assemblages partly comprised of information about human action, but their materialisations are also the products of human action, and these materialisations can influence future human action.

Rather than refer to data literacy or data management skills, I take up the term ‘data sense’ to encapsulate a broader meaning of ‘data sense’ that includes human senses (sight, sound, touch, smell and taste) and how these are part of people’s responses to data and also acknowledges the role played by digital sensors in the act of ‘sense-making’; or coming to terms with digital data.

 

Data sense smartart

Data Sense

 

My 2015 publications

Here are my publications that came out in 2015.

Book

  • Lupton, D. (2015) Digital Sociology. London: Routledge.

Book chapters

  • Lupton, D. (2015) Digital sociology. In Germov, J. and Poole, M. (eds), Public Sociology: An Introduction to Australian Society, 3rd St Leonards: Allen & Unwin.
  • Lupton, D. (2015) Donna Haraway: the digital cyborg assemblage and the new digital health technologies. In Collyer, F. (ed), The Palgrave Handbook of Social Theory in Health, Illness and Medicine. Houndmills: Palgrave Macmillan.

Peer-reviewed journal articles

Report

  • Lupton, D. and Pedersen, S. (2015) ‘What is Happening with Your Body and Your Baby’: Australian Women’s Use of Pregnancy and Parenting Apps. Available here.

Edited book ‘Beyond Techno-Utopia: Critical Approaches to Digital Health Technologies’ now out

Last year I guest-edited a special issue of the open-access sociology journal Societies that focused on critical perspectives on digital health technologies. The collection includes my editorial and another article I contributed (on the topic of apps as sociocultural artefacts), as well as eight other articles from scholars based in the UK, Australia, Finland, the USA and Sweden. Individual contributions may be accessed on the journal’s website here, and now the whole collection is available as an open access book PDF (or can be purchased as a hard copy), both available here.

The following outline of the special issue/book’s contents, an edited excerpt taken from my editorial, provides an overview of its contents.

The articles in this special issue build on a well-established literature in sociology, science and technology studies and media and cultural studies that has addressed the use of digital technologies in health and medicine… Several of these topics are taken up in the articles published in this special issue. All the authors use social and cultural theory to provide insights into the tacit assumptions, cultural meanings and experiences of digital health technologies. The articles cover a range of digital health technologies: devices used for the self-tracking of body metrics (Ruckenstein; Till; Rich and Miah; Lupton); social media platforms for discussing patients’ experiences of chronic disease (Sosnowy) and experiences of pregnancy and early motherhood (Johnson); health and medical apps (Till; Johnson; Christie and Verran; Lupton); telehealthcare systems (Hendy, Chrysanthaki and Barlow); and a digital public health surveillance system (Cakici and Sanches). While some articles focus on globalised digital media (Cakici and Sanches; Rich and Miah; Till; Lupton), others engage more specifically with a range of sociocultural groups, contexts and locations. These include Aboriginal people living in a remote region of Australia (Christie and Verran) and Australian mothers in urban Sydney (Johnson) as well as research participants in Helsinki, Finland (Ruckenstein), the United States (Sosnowy) and England (Hendy, Chrysanthaki and Barlow).

Understandings and experiences of selfhood and embodiment as they are generated and experienced via digital health devices are central preoccupations in the articles by Ruckenstein, Rich and Miah, Till, Lupton, Sosnowy and Johnson. Ruckenstein’s study of self-trackers found that they often conceptualised their bodies and their physical activities in different ways when these were being monitored and rendered into digital data. The data that were generated by these devices proved to be motivational and to give value to some activities (like housework) that otherwise lacked value or new meaning to functions such as sleep (which when digitised and quantified became viewed as a competence). Ruckenstein found that the digital data tended to be invested with greater validity than were other indicators of bodily wellbeing or activity, such as the individual’s physical sensations.

All of the above authors comment on the ways in which digital health devices such as wearable self-tracking devices, social media platforms, apps and patient support websites work as disciplinary tools. They invite users to conform to the ideals of healthism (privileging good health above other priorities) and the responsible self-management and self-monitoring of one’s health and body, including avoiding exposure to risk. Rich and Miah use the concept of “public pedagogy” to describe the socio-political dimensions of digital health technologies as they are employed to educate people about their bodies and promote self-management. As Johnson notes, for women who are pregnant or have the care of young children, this sphere of responsibility is extended to the bodies of others: the foetus or child. And as Till’s article emphasises, when employees are “encouraged” to engage in self-tracking, the ethos of responsibility extends from personal objectives to those of employers.

Ruckenstein, Till and Sosnowy also highlight the digital labour involved for people who engage with social media or self-tracking apps as part of their personal health or fitness practices. Sosnowy’s interviews with women with multiple sclerosis who blog about their condition emphasise the work involved in such engagement as an “active patient”. Till’s analysis of digital exercise self-tracking points to the appropriations of people’s labour by other actors for commercial reasons.

The article by Hendy, Chrysanthaki and Barlow moves in a somewhat different direction. Using ethnographic cases studies, they look at the managerial issues involved with implementing telehealthcare in English social and health care organisations. Their focus, therefore, is not on the recipients or targets of digital health technologies but rather those who are attempting to institute programs as part of their work as managers. These authors’ contribution highlights the messiness of introducing new systems and practices into large organisations, and the resistances that may emerge on the part of both workers and the targets of telehealthcare programs. Cakici and Sanches’ article also takes an organisational perspective in addressing a European Commission co-funded project directed at syndromic surveillance, or the use of secondary sources to detect outbreaks and patterns in diseases and medical conditions. Digital data are increasingly being use as part of syndromic surveillance: Google Flu Trends is one such example. Cakici and Sanches’ analysis highlights the role played by human decision-making and the affordances of digital technologies in structuring what kinds of data are retrieved for syndromic surveillance and how they are interpreted.

While there are as yet few detailed ethnographic accounts of how people are implementing, adopting or resisting contemporary digital health technologies, there are even fewer that investigate the use of these technologies by members of cultural groups outside the global North. The article by Christie and Verran takes a much-needed diversion from perspectives on white, privileged groups to Aboriginal people living in a remote part of Australia. As they argue, the concepts on health, illness and the body that are held by this cultural group differ radically from the tacit assumptions that are invested in mainstream health and medical apps. Any app that is developed to assist in health literacy that is targeted at this group must incorporate culturally-appropriate modes of communication: positioning people within their cultural and kinship networks of sociality, for example, rather than representing them as atomised actors.

The articles collected here in this special issue have gone some way in offering a critical response to digital health technologies, but they represent only a beginning. Many more compelling topics remain to be investigated. These include research into the ways in which lay people and healthcare professionals are using (or resisting the use) of social media, apps and self-monitoring devices for medicine and health-related purposes; the implications for medical power and the doctor-patient relationship; how citizen science and citizen sensing are operating in the public health domain; the development of new digital health technologies; the implications of big data and data harvesting in medicine and healthcare; the spreading out of health-related self-tracking practices into many social domains; the unintended consequences and ethical aspects of digital technology use and their implications for social justice; and data security and privacy issues.

Changing representations of self-tracking

I recently completed a chapter for a book on lifelogging that discussed the concepts and uses of data as they are expressed in representations of self-tracking (see here for the full paper, available open access). In part of the chapter I looked at the ways in which people writing about the quantified self and other interpretations of self-tracking represent data and data practices, including in articles published in Wired magazine and other media outlets and blogs.

From the beginning of discussions of the quantified self, the representation of data in quantified self-tracking discourses (as least as it was expressed by its progenitors) included several factors. These include the following: quantified data are powerful entities; it is important not only to collect quantified data on oneself, but to analyse these data for the patterns and insights they reveal; data (and particularly quantified or quantifiable data) are an avenue to self-knowledge; the emergence of new digital and mobile devices for gathering information about oneself have facilitated self-tracking and the generation of quantified personal data; quantifiable data are more neutral, reliable, intellectual and objective than qualitative data, which are intuitive, emotional and subjective; self-tracked data can provide greater insights than the information that a person receives from their senses, revealing previously hidden patterns or correlations; self-tracked data can be motivational phenomena, inspiring action, by entering into a feedback loop; everything can be rendered as data; and data about individuals are emblematic of their true selves.

In more recent times, however, it is evident that a further set of concepts about self-tracked data have emerged since the original euphoria of the early accounts of quantified self-tracking. They include: the meaning of self-tracked data can be difficult to interpret; personal data can be disempowering as well as empowering; the conditions in which data are gathered can influence their validity; the contexts in which data are generated are vital to understanding their meaning; individuals’ personal data are not necessarily secure or private; quantified personal data can be reductive; and personal data can be used to discriminate against individuals.

We as yet know very little about how people are conceptualising and engaging with digital data about themselves. Given the recent scandals about how people’s personal data may be hacked or used or manipulated without their knowledge (the Snowden revelations about security agencies’ use of metadata, the Facebook emotional manipulation experiment, the celebrity nude photo and Sony Pictures hackings, for example), as well as growing coverage of the potentially negative implications of self-tracking as described above, these are pressing issues.

Edit (12 December 2015): More on this topic can be found in my book The Quantified Self: A Sociology of Self-Tracking Cultures.

 

The five modes of self-tracking

Recently I have been working on a conference paper that seeks to outline the five different modes of self-tracking that I have identified as currently in existence. (Update – the full paper can now be downloaded here).

I argue that there is evidence that the personal data that are derived from individuals engaging in reflexive self-monitoring are now beginning to be used by agencies and organisations beyond the personal and privatised realm. Self-tracking rationales and sites are proliferating as part of a ‘function creep’ of the technology and ethos of self-tracking. The detail offered by these data on individuals and the growing commodification and commercial value of digital data have led government, managerial and commercial enterprises to explore ways of appropriating self-tracking for their own purposes. In some contexts people are encouraged, ‘nudged’, obliged or coerced into using digital devices to produce personal data which are then used by others.

The paper examines these issues, outlining five modes of self-tracking that have emerged: private, pushed, communal, imposed and exploited. There are intersections and recursive relationships between each of these self-tracking modes. However there are also observable differences related to the extent to which the self-tracking is taken up voluntarily and the purposes to which the data thus created are put.

Here are definitions of the typology of self-tracking that I have developed:

  • Private self-tracking relates to self-tracking practices that are taken up voluntarily as part of the quest for self-knowledge and self-optimisation and as an often pleasurable and playful mode of selfhood. Private self-tracking, as espoused in the Quantified Self’s goal of ‘self  knowledge through numbers’, is undertaken for purely personal reasons and the data are kept private or shared only with limited and selected others. This is perhaps the most public and well-known face of self-tracking.
  • Pushed self-tracking represents a mode that departs from the private self-tracking mode in that the initial incentive for engaging in self-tracking comes from another actor or agency. Self-monitoring may be taken up voluntarily, but in response to external encouragement or advocating rather than as a personal and wholly private initiative. Examples include the move in preventive medicine, health promotion and patient self-care to encourage people to monitor their biometrics to achieve targeted health goals. The workplace has become a key site of pushed self-tracking, particularly in relation to corporate wellness programs where workers are encourage to take up self-tracking and share their data with their employer.
  • Communal self-tracking involves the voluntary sharing of a tracker’s personal data with other people. They may use social media, platforms designed for comparing and sharing personal data and sites such as the Quantified Self website to engage with and learn from other self-trackers. Some attend meetups or conferences to meet face-to-face with other self-trackers and share their data and evaluations of the value of different techniques and devices for self-tracking. This mode is also evident in citizen science, citizen sensing and community development initiatives using data collected by individuals on their local environs, such as air quality, traffic conditions and crime rate that are then aggregated with other participants for use in improving local conditions and services or political action.
  • Imposed self-tracking involves the imposition of self-tracking practices upon individuals by others primarily for these others’ benefit. These include the use of tracking devices as part of worker productivity monitoring and efficiency programs. There is a fine line between pushed self-tracking and imposed self-tracking. While some elements of self-interest may still operate, people may not always have full choice over whether or not they engage in self-tracking. In the case of self-tracking in corporate wellness programs, employees must give their consent to wearing the devices and allowing employers to view their activity data. However failure to comply may lead to higher health insurance premiums enforced by an employer, as is happening in some workplaces in the United States. At its most coercive, imposed self-tracking is used in programs involving monitoring of location and drug use for probation and parole surveillance, drug addiction programs and family law and child custody monitoring.
  • Exploited self-tracking refers to the ways in which individuals’ personal data are repurposed for the (often commercial) benefit of others. Exploited self-tracking is often marketed to consumers as a way for them to benefit personally, whether by sharing their information with others as a form of communal self-tracking or by earning points or rewards. However their data are then used by second parties for their own purposes and in some cases are sold to or used by third parties. Customer loyalty programs, in which consumers voluntarily sign up to have their individual purchasing habits logged by retailers in return for points or rewards is one example. Some retailers (for example a large pharmacy chain in the US) are beginning to use wearable devices as part of their customer rewards schemes, encouraging customers to upload their personal fitness data to their platforms. The data can then be used by the retailers for their marketing, advertising and product offers as well as onsold to third parties.

In the rest of the paper I draw upon theoretical perspectives on concepts of selfhood, citizenship, biopolitics and data practices and assemblages in discussing the wider sociocultural implications of the emergence and development of these modes of self-tracking. I argue that there are many important issues that require further exploring in relation to the appropriation of self-tracking. As humans increasingly become nodes in the Internet of Things, generating and exchanging digital data with other smart, sensor-equipped objects, self-tracking practices will most probably become unavoidable for many people, whether they are taken up voluntarily or pushed or imposed upon them. The evidence outlined in this paper suggests a gradually widening scope for the use of self-tracking that is likely to expand as a growing number of agencies and organisations realise the potential of the data that are produced from these practices.

Edit (12 December 2015): More on this topic can be found in my book The Quantified Self: A Sociology of Self-Tracking Cultures.

Beyond the quantified self: the reflexive monitoring self

This piece is partly a response to a recent blog post by Mark Carrigan about the concept of the qualified self, and partly a section of the new book that I am working on about the sociology of self-tracking cultures.

As part of my research for the book I made a Google Trends graph comparing the major terms that are used to denote the practices of voluntarily monitoring aspects of the self: self-tracking, the quantified self, life logging and personal analytics. As the resultant graph demonstrates, it was not until mid-2007 that any of these terms began to show up in Google searches. Self-tracking led the way, followed by life logging, then personal analytics. The quantified self is the newest term. It began to appear in searches in January 2010 and rose quickly in popularity, beginning to overtake self-tracking by April 2012 (although just recently self-tracking has caught up again). The quantified self, therefore, has become a well-used term, at least among people using Google Search. In another study of news coverage of the quantified self I found that the term has become increasingly used in these accounts as well.

But is it time to rethink or even relinquish the term ‘the quantified self’? For my book I prefer to use ‘self-tracking’ over the alternatives, as this term is broader and more inclusive of a range of practices (and I refer to ‘self-tracking cultures’ to denote the various social, cultural and political contexts in which self-tracking practices are carried out).

Self-tracking is not simply about quantified (or quantifiable) information. Many self-trackers record non-quantifiable data as part of their practice, including journaling accounts of their daily activities, emotional states and relationships, collecting audio data or visual images and producing visualisations that centre on their aesthetic or explanatory properties rather than their representation of numbers.

Some commentators seek to position the ‘qualified self’ as a practice involving reflection and interpretation of information, whether this information is in the form of numbers or not. For several writers, the qualified self involves interpretation and assessment of any form of data, a considered engagement with this information that seeks to contextualise it in relation to other forms of data. As two designers put it:

context humanizes the numbers and places them back into our lives in meaningful ways. For example, a fitness tracker can tell us that our physical activity is down from the previous month. But it cannot tell us that the inactivity is due to a sprained ankle. Given that context, those declining numbers might tell a different story: that we are recovering steadily rather than slacking off. Even in that simple scenario, it is clear that a small bit of context can frame data in a much more insightful way.

In her blog post on the qualified self Jenny Davis has similarly contended that:

This qualitative component is key in mediating between raw numbers and identity meanings. If self-quantifiers are seeking self-knowledge through numbers, then narratives and subjective interpretations are the mechanisms by which data morphs into selves. Self-quantifiers don’t just use data to learn about themselves, but rather, use data to construct the stories that they tell themselves about themselves.

This distinction between the quantified and the qualified self works to challenge the term ‘the quantified self’. The essential feature of the quantified self, at least as it is described in the motto ‘self knowledge through numbers’ (used on the official Quantified Self website) is self-knowledge, however it is produced. Indeed selfhood and identity as they are articulated via self-tracking are inextricably entangled with interpretation of information. It could be argued that the word ‘numbers’ really comes to stand for ‘information of any kind about oneself’ and ‘self-knowledge’ means not only the accumulation of facts about oneself, but paying attention to the self or self-awareness. The practice of self-tracking can therefore be regarded as a way of thinking through as well as with information, working to make connections between one kind or source of information and others and interrogating the quality or validity of the data.

When self-tracking is viewed in this way, numbers are not important. What is important for self-trackers is the range of information that can be gathered about one’s self, what specific types of information one chooses to collect and the process of making sense of this information as part of the ethical project of selfhood. Davis’s description of the qualified self makes the important point that the information that self-trackers collect on themselves is not simply about self-knowledge but also about presentations and narratives of selfhood – or what might also be glossed as performing selfhood. She refers to the ‘stories that they tell about themselves’, but self-tracking is also about the stories that people tell others, or the types of selves that are presented to others. Indeed the very act of self-tracking, or positioning oneself as a self-tracker, is already a performance of a certain type of subject: the entrepreneurial, self-optimising subject. A fine line must be negotiated, however, in seeking to perform this subject position. Too much focus on the self may be interpreted as self-obsession and narcissism, while too little signifies failure to conform to the idealised responsible citizen who is actively seeking out information as part of the project of taking control over her or his life.

At the broader level of social explanation, self-tracking is the latest practice in a long tradition of ethical self-reflection that extends back to the ancients, inflected through newer devices for tracking and contemporary understandings about ideal selfhood. Novel ways of collecting, representing and sharing data have emerged in digital society. What might be better described as ‘the reflexive monitoring self’ is an aggregation of practices that combine regular and systemised information collection, interpretation and reflection as part of working towards the goal of becoming. Underpinning these efforts are the notion of an ethical incompleteness and a set of moral obligations concerning working on the self that are central to contemporary ideas about selfhood and citizenship. I will be looking in detail at these aspects in the book and expanding on the arguments presented here.