Call for abstracts for themed issue on body weight and digital media

I am editing a themed issue for Fat Studies: An Interdisciplinary Journal of Body Weight and Society on the topic of body weight and digital media. Fat Studies is the first academic journal that critically examines theory, research, practices, and programs related to body weight and appearance.

If you are interested in contributing to this themed issue, please send me an article title and an abstract of 200-250 words outlining what you would propose to cover by 29 February 2016. Final submissions should be no longer than 7,000 words, including the abstract, all notes and references. Please email to deborah.lupton@canberra.edu.au

In keeping with the journal’s emphasis on ‘body weight and society’, the themed issue will include contributions that address the following and related topics from a critical sociocultural perspective:

  • representations of body weight and size in the digital news media (and also how readers may comment on news reports online)
  • apps and wearable devices for weight control, physical fitness and energy expenditure
  • selfies and body size
  • the discussion and portrayal of such issues as weight loss, body size, fat activism, thinspo, fitspo, pro-ana, pro-mia and fat pornography and erotica in blogs, social media platforms and other websites
  • big data and body weight

If your abstract is accepted, the following deadlines apply:

  • Full papers by 31 May 2016
  • Revised final versions by 30 August 2016

 

My new book: The Quantified Self

My new book The Quantified Self: A Sociology of Self-Tracking Cultures is due out with Polity Press this April. The publishers are offering a 20% discount for six months (from 18 January 2016 to 31 July 2016) if it is ordered via their website. Please use the code PY703 when you order to receive the discount.

Here is a PDF of the Introduction: Lupton 2016 Introduction to The Quantified Self.

Table of Contents

Acknowledgements

Introduction

1          ‘Know Thyself’: Self-tracking Practices and Technologies

2          ‘New Hybrid Beings’: Theoretical Perspectives

3          ‘An Optimal Human Being’: the Body and Self in Self-Tracking Cultures

4          ‘You are Your Data’: Personal Data Meanings, Practices and Materialisations

5          ‘Data’s Capacity for Betrayal’: Personal Data Politics

Conclusion

References

Index

 

POLITY-Lupton-Quantified Self Visuals-AUG24-3 (1)

 

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.

Critical social research on self-tracking: a reading list

Self-tracking has recently become a new area of fascination for critical social researchers. A body of literature has now been established of research that has sought to investigate the social, cultural and political dimensions of self-tracking, nearly all of which has come out in the last few years. This literature complements an established literature in human-computer interaction research (HCI), first into lifelogging and then into self-tracking (or personal informatics/analytics, as HCI researchers often call it).

I am currently working on an article that is a comprehensive review of both literatures, in the attempt to outline what each can contribute to understanding self-tracking as an ethos and a practice, and its wider sociocultural implications. Here is a reading list of the work from critical social researchers that I am aware of. I will publish a similar list of interesting HCI research in a forthcoming post.

Albrechtslund, A, and P Lauritsen, (2013) Spaces of everyday surveillance: Unfolding an analytical concept of participation, Geoforum, 49: 310-16.

Allen, AL, (2008) Dredging up the past: Lifelogging, memory, and surveillance, The University of Chicago Law Review, 75 (1): 47-74.

Barta, K, and G Neff, (2015) Technologies for sharing: lessons from Quantified Self about the political economy of platforms, Information, Communication & Society, online first.

Bode, M, and DB Kristensen,  (2016) The digital doppelgänger within. In Assembling Consumption: Researching actors, networks and markets, edited by R. Canniford and D. Badje. London: Routledge, pp.

Bossewitch, J, and A Sinnreich, (2013) The end of forgetting: Strategic agency beyond the panopticon, New Media & Society, 15 (2): 224-42.

Copelton, D, (2010) Output that counts: pedometers, sociability and the contested terrain of older adult fitness walking, Sociology of Health & Illness, 32 (2): 304-18.

Crawford, K, J Lingel, and T Karppi, (2015) Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wrist wearable device, European Journal of Cultural Studies, 18 (4-5): 479-96.

Daly, A, (2015) The law and ethics of ‘self quantified’ health information: an Australian perspective, International Data Privacy Law, online first.

Dodge, M, and R Kitchin, (2007) ‘Outlines of a world coming into existence’: pervasive computing and the ethics of forgetting, Environment and Planning B: Planning & Design, 34 (3): 431-45.

Drew, DL, and JM Gore, (2014) Measuring up? The discursive construction of student subjectivities in the Global Children’s Challenge™, Sport, Education and Society, online first.

Fiore-Gartland, B, and G Neff, (2015) Communication, mediation, and the expectations of data: data valences across health and wellness communities, International Journal of Communication, 9: 1466-84.

Fox, NJ, (2015) Personal health technologies, micropolitics and resistance: a new materialist analysis, Health:, online first.

Gardner, P, and B Jenkins, (2015) Bodily intra-actions with biometric devices, Body & Society, online first.

Gerlitz, C, and C Lury, (2014) Social media and self-evaluating assemblages: on numbers, orderings and values, Distinktion: Scandinavian Journal of Social Theory, 15 (2): 174-88.

Gilmore, JN, (2015) Everywear: The quantified self and wearable fitness technologies, New Media & Society, online first.

Jethani, S, (2015) Mediating the body: Technology, politics and epistemologies of self, Communication, Politics & Culture, 47 (3): 34-43.

Klauser, FR, and A Albrechtslund, (2014) From self-tracking to smart urban infrastructures: towards an interdisciplinary research agenda on Big Data, Surveillance & Society, 12 (2): 273-86.

Lomborg, S, and K Frandsen, (2015) Self-tracking as communication, Information, Communication & Society: 1-13.

Lupton, D, (2012) M-health and health promotion: the digital cyborg and surveillance society, Social Theory & Health, 10 (3): 229-44.

Lupton, D, (2013a) The digitally engaged patient: self-monitoring and self-care in the digital health era, Social Theory & Health, 11 (3): 256-70.

Lupton, D, (2013b) Quantifying the body: monitoring and measuring health in the age of mHealth technologies, Critical Public Health, 23 (4): 393-403.

Lupton, D, (2013c) Understanding the human machine, IEEE Technology & Society Magazine, 32 (4): 25-30.

Lupton, D, (2014a) The commodification of patient opinion: the digital patient experience economy in the age of big data, Sociology of Health & Illness, 36 (6): 856-69.

Lupton, D, (2014b) Self-tracking cultures: towards a sociology of personal informatics. In Proceedings of the 26th Australian Computer-Human Interaction Conference (OzCHI ’14). Sydney: ACM Press.

Lupton, D. (2014c) Self-tracking modes: reflexive self-monitoring and data practices. Social Science Research Networkhttp://ssrn.com/abstract=2483549  (accessed 27 August 2014).

Lupton, D. (2014d) You are your data: self-tracking practices and concepts of data. Social Science Research Networkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2534211  (accessed 12 December 2015).

Lupton, D, (2015a) Data assemblages, sentient schools and digitised health and physical education (response to Gard), Sport, Education and Society, 20 (1): 122-32.

Lupton, D. (2015b) Lively data, social fitness and biovalue: the intersections of health self-tracking and social media. Social Science Research Networkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2666324  (accessed 13 November 2015).

Lupton, D. (2015c) Personal data practices in the age of lively data. Social Science Research Networkhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2636709  (accessed 15 August 2015).

Lupton, D, (2015d) Quantified sex: a critical analysis of sexual and reproductive self-tracking using apps, Culture, Health & Sexuality, 17 (4): 440-53.

Lupton, D, (2016a) The diverse domains of quantified selves: self-tracking modes and dataveillance, Economy and Society, in press.

Lupton, D, (2016b) The Quantified Self: A Sociology of Self-Tracking Cultures. Cambridge: Polity Press.

Lynch, R, and S Cohn, (2015) In the loop: Practices of self-monitoring from accounts by trial participants, Health:, online first.

Millington, B, (2015) ‘Quantify the Invisible’: notes toward a future of posture, Critical Public Health, online first.

Moore, P, and A Robinson, (2015) The quantified self: What counts in the neoliberal workplace, New Media & Society, online first.

Nafus, D, (2013) The data economy of biosensors. In Sensor Technologies:  Healthcare, Wellness and Environmental Applications, edited by M. McGrath and C. N. Scanaill: Springer.

Nafus, D, (2014) Stuck data, dead data, and disloyal data: the stops and starts in making numbers into social practices, Distinktion: Scandinavian Journal of Social Theory, 15 (2): 208-22.

Nafus, D, and J Sherman, (2014) This one does not go up to 11: the Quantified Self movement as an alternative big data practice, International Journal of Communication, 8: 1785-94.

Neff, G, and D Nafus, (2016) Self-Tracking. Cambridge, MA: The MIT Press.

Niva, M, (2015) Online weight-loss services and a calculative practice of slimming, Health:, online first.

Pantzar, M, and M Ruckenstein, (2015) The heart of everyday analytics: emotional, material and practical extensions in self-tracking market, Consumption Markets & Culture, 18 (1): 92-109.

Reigeluth, TB, (2014) Why data is not enough: digital traces as control of self and self-control, Surveillance & Society, 12 (2): 243-54.

Rettberg, JW, (2014) Seeing Ourselves Through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves. Basingstoke: Palgrave Macmillan.

Ruckenstein, M, (2014) Visualized and interacted life: personal analytics and engagements with data doubles, Societies, 4 (1): 68-84.

Ruckenstein, M,  (2015) Uncovering everyday rhythms and patterns: food tracking and new forms of visibility and temporality in health care. In Techno-Anthropology in Health Informatics, edited by L. Botin, C. Nohr and P. Bertelsen. Amsterdam: IOS Press, pp. 28-40.

Ruckenstein, M, and M Pantzar, (2015a) Beyond the Quantified Self: thematic exploration of a dataistic paradigm, New Media & Society, online first.

Ruckenstein, M, and M Pantzar, (2015b) Datafied life: techno-anthropology as a site for exploration and experimentation, Techne, 19 (2): 191-210.

Sellen, AJ, and S Whittaker, (2010) Beyond total capture: a constructive critique of lifelogging, Communications of the ACM, 53 (5): 70-77.

Smith, WR, (2015) Communication, sportsmanship, and negotiating ethical conduct on the digital playing field, Communication & Sport, earlyview online.

Stragier, J, T Evens, and P Mechant, (2015) Broadcast yourself: an exploratory study of sharing physical activity on social networking sites, Media International Australia, 155 (1): 120-29.

Thomas, GM, and D Lupton, (2015) Threats and thrills: pregnancy apps, risk and consumption, Health, Risk & Society, online first.

Till, C, (2014) Exercise as labour: Quantified Self and the transformation of exercise into labour, Societies, 4 (3): 446-62.

Van Den Eede, Y,  (2015) Tracing the tracker: a postphenomenological inquiry into self-tracking technologies. In Postphenomenological Investigations: Essays on Human–Technology Relations, edited by R. Rosenberger and P.-P. Verbeek. Lanham, Maryland: Lexington Books, pp. 143-58.

Whitson, J, (2013) Gaming the quantified self, Surveillance & Society, 11 (1/2): 163-76.

Wilkinson, J, C Roberts, and M Mort, (2015) Ovulation monitoring and reproductive heterosex: living the conceptive imperative?, Culture, Health & Sexuality, 17 (4): 454-69.

Williamson, B, (2015) Algorithmic skin: health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education, Sport, Education and Society, 20 (1): 133-51.

Yang, Y, (2014) Saving the Quantified Self: How we come to know ourselves now, Boom: A Journal of California, 4 (4): 80-87.

 

 

 

 

Digital sociology and human-computer interaction research

I have been thinking for some time about some of the shared interests of digital sociology and human-computer interaction (HCI) research. In December 2014 I gave a paper at the major annual Australian HCI conference (known as ‘OzCHI’), offering a sociological perspective on self-tracking cultures. And I recently submitted a brief position paper for a workshop on everyday surveillance, to be held as part of the preeminent conference on HCI internationally (referred to as ‘CHI’), to be held in May 2016. Here is what I have to say in this position paper.

Everyday Surveillance: What Digital Sociology Can Offer

In this position paper I outline how perspectives from digital sociology can contribute to researching and theorising everyday surveillance. I contend that sociologists and human-computer interaction (HCI) researchers have tended to conduct their research in relatively separate spheres that would benefit from collaboration and greater use of the literatures in each discipline.

Thus far there has been little interaction between sociologists and HCI studies. Yet there is much potential for the approaches of each area of study to draw insights for each other’s work. Sociologists can learn from innovative methods presented in HCI. For their part, HCI researchers could benefit from the sociocultural theory developed in sociology to provide greater depth to their investigations. While they engage in approaches to researching user experience that offer interesting new methods for sociologists, their work tends to draw on psychological models of behaviour that fail to incorporate the broader social, cultural and political dimensions of everyday beliefs and practices and are often paternalistic in their approach.

Digital sociology is a subdiscipline of sociology that is beginning to blossom. This work draws on a long interest on the part of sociologists in the social, cultural and political elements of the internet, cyberspace and personal computer use. In line with the traditional interests of sociologists, those scholars who have directed attention at digital technologies have emphasised the social determinants of technology use: structuring factors such as gender, age, social class, geographical location, race and ethnicity. As such, their perspective tends to be critical, interested in identifying the power relations and tacit assumptions that underpin social relationships and institutions.Sociologists have adopted a range of social theories, including Marxist-influenced structuralist conflict theory, feminist and poststructuralist Foucauldian theory as well as Latourian actor-network theory, to generate insights into people’s use of digital technologies and the social impact of these technologies.

More specifically, in relation to everyday surveillance, HCI researchers have yet to fully engage in the ground-breaking work of sociologists who have explored the social elements of digital surveillance technologies and the ways in which these technologies are used across a range of domains and for a multitude of purposes.

Several sociologists have sought to investigate how people within specific social groups engage in voluntary and participatory surveillance, typically using ethnographic, focus group or interview-based research to do so. Some survey-based research has sought to identify people’s attitudes to the ways in which their personal data are used by third parties and the accompanying data security and privacy issues, as well as the influence on attitudes of membership of social groups.

An important sociological literature has developed that takes a critical approach to covert or disciplinary surveillance and the spread of such monitoring into many nooks and crannies of everyday life, often without people’s knowledge or consent. Analysis of the social implications of algorithmic sorting on people’s life chances and opportunities (sometimes referred to as ‘algorithmic authority’) has also begun to develop. This literature is part of critical data studies, a developing multidisciplinary field of research incorporating not only sociology but also anthropology, cultural studies, internet studies, media and cultural studies and cultural geography.

As a digital sociologist who has researched digital data practices and data materialisations, particularly in relation to self-tracking cultures, big data politics and understandings, digitised academia, and parenting cultures, I am interested in learning more about user-experience methods in relation to surveillance technologies as they are employed in HCI, but also contributing my sociological perspective to broadening HCI’s hitherto often individualistic, instrumental and uncritical approach. I argue that bringing greater awareness and more in-depth analysis of the social into HCI research on surveillance to a greater extent would enrich the field.


Public understanding of personal digital data

One of the research projects I am conducting, with Mike Michael from the University of Sydney, is investigating the public understanding of digital data. We are experimenting with using novel methods (for sociologists at least!) in our project, which combines focus group discussions with cultural probes.

In the discussion groups, we wanted to go beyond the usual approach of simply asking questions of people. We wanted to invite people to think and work together playfully and creatively. We therefore decided to employ cultural probes to stimulate thought, discussion and debate, involving asking people to work together as a group or in pairs to generate material artefacts. Cultural probes are objects or tasks that are designed to be playful and provocative so as to encourage people to think in new ways about technologies. They are particularly valued for their ability to address intimate or controversial issues, to act as ‘irritants’ to engage people’s responses.

We asked people in our focus groups (held in Sydney) to engage in three collaborative tasks that we devised for them.

  1. The Daily Big Data Task. This task asked participants to work together as a group to draw a timeline on a huge piece of paper of a typical person’s day and adding the ways in which data (digital or otherwise) may be collected on that person.
  2. The Digital Profile Card Game. This task involved small groups to use cards with socio-demographic details on them to construct a profile of an individual, speculate about their characteristics and discuss how this information could be used.
  3. The Personal Data Machine. In this activity, participants were asked to work in pairs to design two data-gathering devices: one that they would find useful to use to collect any kind of data about themselves, and one for collecting data on another person. They were asked to write notes or make drawings describing their devices.

After each task the group came together to talk about the artefacts they had created or handled and what their implications were.

Earlier this year, we published a short piece in Discover Society that outlined some of our initial findings. A new article in the journal Public Understanding of Science, entitled ‘Toward a manifesto for the public understanding of big data’ has just been published. We are currently working on another article that presents our empirical work in greater detail.

In the ‘manifesto’ article, we pointed out that there are many intersections between research on the public understanding of digital data with the literatures on the public understanding of science and public engagement with science and technology. These are bodies of work that have been devoted to making sense of the intersections between how citizens engage with scientific knowledge, including not only consuming but producing this knowledge. Indeed, it may be contended that members of the public have been ‘prosumers’ of scientific knowledge long before the emergence of digital data (that is, both acting to consume and produce scientific information), particularly when they are engaging in citizen activism or citizen science initiatives.

There are many examples of citizens participating in activities that either contribute to or challenge accepted scientific beliefs. This critical approach has led to the development of a public engagement with science and technology model, in which ‘the public’ and ‘scientific expertise’ are not contrasted with each other. Rather, it is acknowledged that each draws their definitions from the other, contributing to hybrid assemblages of knowledges. The public are both the subjects and objects of scientific research and data, just as they are of digital data.

Our research project findings suggest that we may be seeing a transformation in attitudes in response to the controversies and scandals in relation to the use of people’s personal data that have received a high level of public attention over the past two and a half years, potentially reshaping concepts of privacy. What emerged from our focus groups is a somewhat diffuse but quite extensive understanding on the part of the participants of the ways in which data may be gathered about them and the uses to which these data may be put.

It was evident that although many participants were aware of these issues, they were rather uncertain about the specific details of how their personal data became part of big data sets and for what this information was used. While the term ‘scary’ was employed by several people when describing the extent of data collection in which they are implicated and the knowledge that other people may have about them from their online interactions and transactions, they struggled to articulate more specifically what the implications of such collection were.

On the other hand, when the participants were designing their ‘Personal Data Machines’, it was evident from their creations that they appreciated and enjoyed the opportunity not only to collect detailed information about themselves, but also on other people: partners, children and other family members and co-workers. Some imagined devices included those that monitored other people’s dreams or snooped on partners’ phone call metadata to check if they were unfaithful. Other people described a lie-detecting device, one that could track commercial competitors’ activities, another that revealed the salary of their workmates (so that the user could know if they were being fairly remunerated) and a dating device that could scan a prospective partner’s hand or face and reveal their financial assets and criminal record details.

In some cases, it seems, too much information is never enough. The seductions of data can be very appealing, not just for commercial enterprises or national security agencies.

 

Towards a new mode of self-tracking

In a conference paper and my forthcoming book The Quantified Self: A Sociology of Self-Tracking Cultures, I identify five modes of self-tracking. What I call ‘private self-tracking’ is undertaken for voluntary and personal reasons that are self-initiated. ‘Pushed self-tracking’ involves encouragement for people to monitor themselves from other agencies, while the mode of ‘communal self-tracking’ relies on people sharing their personal information with others. ‘Imposed self-tracking’ involves moving from encouragement to requiring people to collect or engage with data about themselves, so that they may have little choice in doing so. The ‘exploited self-tracking’ mode represents the ways in which personal data may be used by other actors and agencies for their own purposes, either overtly or covertly.

Since writing the initial conference paper, developing these ideas in my book and also for a journal article based on the paper, I have added some thoughts about the possibilities for forms of self-tracking that go beyond these modes. As I argue, self-tracking conforms to a conservative political agenda that represents citizens as automated/autonomous subjects, ideally engaging in self-responsibilised practices of monitoring and life optimisation and emitting valuable ‘data exhausts’ for repurposing by other actors and agencies.

As yet, there has been little discussion of the ways in which self-tracking may be used for resistant or strategic political interventions – as means to challenge accepted norms and assumptions about selves and bodies rather than conforming to these norms and assumptions. Few commentators have drawn attention to how self-tracking highlights certain forms of information about specific kinds of individuals or social groups while it neglects or ignores others, and how idealised citizen subjects are configured via dominant self-tracking cultures while those who fail to meet these ideals are stigmatised or disciplined.

Nascent moves towards a more political use of self-tracking are evident in some citizen sensing initiatives, when they are used to expose or challenge assumptions about geographical areas, the social determinants of ill-health, the environment and living conditions in the effort to draw attention towards social inequalities, government neglect or environmental mismanagement.

There is ample further scope for alternative approaches to self-tracking as a form of knowledge production that seek to identify, record and highlight details of socioeconomic disadvantage or social stigma rather than simply perpetuating them, or to generate knowledge of others rather than being directed at serving the solipsism of self-knowledge. Resistant self-tracking efforts may serve to make visible forms of power relations, injustice and inequalities that are currently hidden from view. It is here that a new mode of self-tracking may develop. The possibilities for a new form of data politics that takes up these more critical and challenging practices are intriguing.

Digitising female fertility and reproduction

Over the past few months, I have been working on writing about the findings of several research projects addressing the topic of digital technologies directed at female fertility and reproduction. These projects involve:

1) a critical content analysis of fertility and reproduction-related software and devices (especially apps);

2) an online survey of 410 Australian women’s use of pregnancy and parenting apps; and

3) focus groups and interviews with Australian and British women about their use of these technologies (these are still in progress).

Several outcomes have now been published drawing on these findings. They include a report (with Sarah Pedersen from Robert Gordon University, Aberdeen) outlining the findings of the online survey (this can be accessed here), an article on the gamification and ludification of pregnancy in apps (with Gareth Thomas from Cardiff University, available here) and a book chapter on the concept of the reproductive citizen and the range of digital technologies that are directed at helping women to monitor and regulate their fertility and reproduction (available here).

Some of the key findings are:

  • The survey showed that pregnancy and parenting apps were very popular among the survey respondents – three-quarters of the respondents (who were either pregnant or who had a baby in the past three years at the time of the survey) said that they had used at least one pregnancy app, while almost half had used at least one parenting app.
  • Googling information about pregnancy is very common among pregnant women, for whom too much information about pregnancy appears never to be enough (this finding emerged in the focus groups). They tend to invest their trust in the first few search findings that come up on their search engine, reasoning that because this is evidence of popularity, then these websites must be credible.
  • Despite the popularity of pregnancy and parenting apps, few women are contemplating the validity of the information presented in them, or demonstrated concern about the data security and privacy of the personal information that the apps may collect (this was evident in both the survey and the focus groups).
  • This genre of software is intensifying an already fervid atmosphere of self-surveillance, attempts at management and control and self-responsibility in which female fertility and reproduction are experienced and performed.
  • Stereotypical concepts of idealised female fertile and pregnant bodies are reproduced in apps and other software. They use highly aestheticised images and the promise of rational calculation and monitoring to seek to contain and control women’s fertility and reproduction.
  • Women in their fertile years – and particularly those contemplating pregnancy or already pregnant – are part of a highly commodified demographic. The information that they generate from their online practices possess a new form of value, biovalue, as part of the bioeconomy of personal health and medical data.

Self-tracking, social fitness and biovalue

I have just completed a chapter for the forthcoming volume The Sage Handbook of Social Media. The chapter addresses the intersections of self-tracking for health and medical purposes with social media platforms and rationales. As I argue in the chapter, the expanded array of digitised devices that are available for self-tracking and the capacity of many of these technologies to interact with social media platforms have encouraged self-trackers to share the details that they collect about themselves with others. I begin with a description of self-tracking and the sociomaterial theoretical foundations on which the chapter rests. This is followed with an overview of the technologies that are available for health and medical self-tracking and for self-trackers to share their data. The discussion section of the chapter presents an analysis of the new forms of value that personal health and medical data have attracted in the digital data economy, and the moral and political repercussions of encouraging people to participate as socially fit citizens. The chapter ends with outlining key questions for further research.

The full pre-print of the chapter is available here.

Who owns your personal health and medical data?

09/01/15 -- A moment during day 1 of the 2-day international Healthcare and Social Media Summit in Brisbane, Australia on September 1, 2015. Mayo Clinic partnered with the Australian Private Hospitals Association (APHA), a Mayo Clinic Social Media Health Network member to bring this first of it's kind summit to Queensland's Brisbane Convention & Exhibition Centre. (Photo by Jason Pratt / Mayo Clinic)

Presenting my talk at the Mayo Clinic Social Media and Healthcare Summit (Photo by Jason Pratt / Mayo Clinic)

Tomorrow I am speaking on a panel at the Mayo Clinic Healthcare and Social Media Summit on the topic of ‘Who owns your big data?’. I am the only academic among the panel members, who comprise of a former president of the Australian Medical Association, the CEO of the Consumers Health Forum, the Executive Director of a private hospital organisation and the Chief Executive of the Medical Technology Association of Australia. The Summit itself is directed at healthcare providers, seeking to demonstrate how they may use social media to publicise their organisations and promote health among their clients.

As a sociologist, my perspective on the use of social media in healthcare is inevitably directed at troubling the taken-for-granted assumptions that underpin the jargon of ‘disruption’, ‘catalysing’, ‘leveraging’ and ‘acceleration’ that tend to recur in digital health discourses and practices. When I discuss the big data phenomenon, I evoke the ‘13 Ps of big data‘ which recognise their social and cultural assumptions and uses.

When I speak at the Summit, I will note that the first issue to consider is for whom and by whom personal health and medical data are collected. Who decides whether personal digital data should be generated and collected? Who has control over these decisions? What are the power relations and differentials that are involved? This often very intimate information is generated in many different ways – via routine online transactions (e.g. Googling medical symptoms, purchasing products on websites) or more deliberately as part of people’s contributions to social media platforms (such as PatientsLikeMe or Facebook patient support pages) or as part of self-tracking or patient self-care endeavours or workplace wellness programs. The extent to which the generation of such information is voluntary, pushed, coerced or exploited, or indeed, even covert, conducted without the individual’s knowledge or consent, varies in each case. Many self-trackers collect biometric data on themselves for their private purposes. In contrast, patients who are sent home with self-care regimes may do so reluctantly. In some situations, very little choice is offered people: such as school students who are told to wearing self-tracking devices during physical education lessons or employees who work in a culture in which monitoring their health and fitness is expected of them or who may be confronted with financial penalties if they refuse.

Then we need to think about what happens to personal digital data once they are generated. Jotting down details of one’s health in a paper journal or sharing information with a doctor that is maintained in a folder in a filing cabinet in the doctor’s surgery can be kept private and secure. In this era of using digital tools to generate and archive such information, this privacy and security can no longer be guaranteed. Once any kind of personal data are collected and transmitted to the computing cloud, the person who generated the data loses control of it. These details become big data, part of the digital data economy and available to any number of second or third parties for repurposing: data mining companies, marketers, health insurance, healthcare and medical device companies, hackers, researchers, the internet empires themselves and even national security agencies, as Edward Snowden’s revelations demonstrated.

Even the large institutions that are trusted by patients for offering reliable and credible health and medical information online (such as the Mayo Clinic itself, which ranks among the top most popular health websites with 30 million unique estimated monthly visitors) may inadvertently supply personal details of those who use their websites to third parties. One recent study found that nine out of ten visits to health or medical websites result in data being leaked to third parties, including companies such as Google and Facebook, online advertisers and data brokers because the websites use third party analytic tools that automatically send information to the developers about what pages people are visiting. This information can then be used to construct risk profiles on users that may shut them out of insurance, credit or job opportunities. Data security breaches are common in healthcare organisations, and cyber criminals are very interested in stealing personal medical details from such organisations’ archives. This information is valuable as it can be sold for profit or used to create fake IDs to purchase medical equipment or drugs or fraudulent health insurance claims.

In short, the answer to the question ‘Who owns your personal health and medical data?’ is generally no longer individuals themselves.

My research and that of others who are investigating people’s responses to big data and the scandals that have erupted around data security and privacy are finding that concepts of privacy and notions of data ownership are beginning to change in response. People are becoming aware of how their personal data may be accessed, legally or illegally, by a plethora of actors and agencies and exploited for commercial profit. Major digital entrepreneurs, such as Apple CEO Tim Cook, are in turn responding to the public’s concern about the privacy and security of their personal information. Healthcare organisations and medical providers need to recognise these concerns and manage their data collection initiatives ethically, openly and responsibly.