Debates in Digital Culture 2019/The Quantified Self
The Quantified SelfEdit
As Deborah Lupton notes, "Monitoring, measuring and recording elements of one’s body and life as a form of self-improvement or self-reﬂection are practices that have been discussed since ancient times. The introduction of digital technologies that facilitate these practices has led to renewed interest in what self-tracking can offer and to an expansion of the domains and purposes to which these practices are applied." Put simply, the Quantified Self refers to collecting personal data for the purposes of analysing behaviour, health and wellbeing. In contemporary society, individuals are now able to achieve this employing wearable technology, which connect to smart devices which analyse and package the data. Uses, however, now extend beyond the individual, as the medical professions and various industries adopt both technology and practice for their own aims.
This chapter of the WikiBook, 'Debates in Digital Culture 2019', looks at the history of the Quantitative Self movement; the technology employed; the applications for the data; and explores some criticisms and concerns surrounding the movement.
History and DevelopmentEdit
Self-tracking can be traced back as far as the 16th century, to Sanctorius of Padua, who documented his eating habits, weight and bowel movements to study his metabolism. Many cite Sanctorius of Padua as the founding father of the quantitative approach to medicine. Following Sanctorius of Padua, Benjamin Franklin tracked his daily routines which informed the development of his '13 virtues'. In 1865, Francis Galton employed the statistical framework developed by Adolphe Quetelet in an attempt to identify significant characteristics of historical figures that he considered to be 'men of genius'.  In turn, this gave rise to the development of Phrenology and Eugenics, both of which have been largely discredited in the modern era.
As self-tracking technologies became more usable and widespread, communities focused on 'quantified self’ followed after as direct successors of the self-tracking communities that formed to discuss and make use of that technology. While communities interested in self-tracking had the potential to form around almost every new individual item of hardware or software, the community that shared its name with the concept, Quantified Self, would become firmly planted as the “centre of the quantified self movement”. In forming this organisation, its creators aimed to invite a wide-reaching set of interests in the existing range of self-tracking technologies into the same space, all in the spirit of self-analysis; Gary Wolf, a founding member of the movement, claimed early in the organisation’s lifespan that Quantified Self was founded as a natural consequence of the speed at which self-tracking technology had begun to develop. Wolf described the direct causal relationship between the community’s founding and rapidly developing technology very simply: “with new tracking systems popping up almost daily, we decided to create a website to track them.”
As Quantified Self grew, however, its philosophy would develop alongside its practical purpose as a centralised community for self-trackers, taking its slogan, “self-knowledge through numbers”, to new extremes. Acting as more than a single-purpose website for ‘tracking trackers’, Quantified Self would become, for example, an advocate for ‘N-of-1’ (single patient) experiments, encouraging self-experimentation as an important part of the self-tracking process. Quantified Self also developed the view that self-tracking is modern technology’s key to finally “knowing thyself”, as well as realising one’s “best self”— aspirations found throughout human history.
However, Quantified Self’s enthusiastic views on the potential of this technology marks its members out as an especially dedicated minority when compared to the less devoted majority of self-trackers. For example, a recent (2017) study found that although Quantified Self recommended constant reflection on collected data in order to attain a more comprehensive level of self-knowledge, ordinary users of self-tracking software were still using it only to help achieve short-term goals, such as weight loss. This separation between Quantified Self’s approach to self-trackers and that of casual users suggests that it has now diverged from acting as a simple ‘website to track trackers’ and into a lifestyle. As the ease of self-tracking is increased by the development of wearable technology, Quantified Self's lifestyle becomes even easier for ordinary people to adopt.
Over the years, technology has increasingly expanded its margins and borders, leading to the achievement of different goals and the birth of various innovations. In recent years, in particular, there has been the introduction of a large innovative device, namely those of the so-called “wearable technologies “.This research concerns some investigations carried out in the United States regarding wearable devices for fitness that have the potential to address some of the public health problems, but at the same time, they raise some privacy issues. The collected data can be combined with personal information from other sources, leading, consequently to the data breach. .
Two years ago, sales giant Target joined Fitbit to convince its US workers to engage in healthy behavior. Those who signed up for the program received free and discounted Fitbit activity trackers. The purpose of these US companies is to adopt wellness programs and offer various incentives to encourage participation. Mobile app development with wearable fitness devices helps American lose weight, improve fitness and reduce stress. The digital company Endeavour Partners claims that wearable devices belong to a category of mass-market products. The market for these wearable health devices is set to develop due to the continued use of smartphones and the dependence on digital media for health information and services. Between 2013 and 2015, the use of wearable health apps doubled. In 2016, 39.5 million adults used a wearable device at least once a month, also facilitated by the fact that these devices are becoming less expensive.
The birth of this “new health economy“ is overcoming the boundaries between health institutions and the digital commercial market. The last few years have led to an expansion of specific sectors that offer different Big Data services to marketing experts. For example, data management platforms, through an analysis of data relating to individuals from different online and offline sources, allow to provide marketers with detailed control of their entire audience.
The advertising industry is working to use wearable devices and other digital devices as the main tools for data-based marketing of a more complete medical and health ecosystem. According to a recent survey carried out for a marketing company, the main advantage of wearable devices is to provide a more detailed set of information.
The focus of this section will be specifically on the Fitbit. The Fitbit is a watch with a unique technology that track elements of your lifestyle such as your sleep patterns, the number of heart beats per minute, when you have been exercising and even if you have simply walked up a flight of stairs. It does so much more, too. It appears that having this information about yourself on your wrist and phone at all time can make users motivated to be more active.
A study a Haynes done of himself in 2015 revealed a lot about self-motivation through wearable technology, specifically the Fitbit. By keeping a close eye on his heart rate and activity levels every day and tweaking his work out regime to suit, he had gone from a self-proclaimed ‘couch potato to marathon runner’. Without this technology available, it can be argued that Haynes and many other Fitbit users would be would not be motivated to put in the same effort to improve their health and fitness as perhaps they would be ignorant to the possibility that they were unfit in the first place.
A study done in the United States of America shows a similar result. When 50 unfit postmenopausal women were given a Fitbit or a standard pedometer as a health intervention in the hope that they would enjoy it and start their journeys to good health, it worked. The results of the study shown that the women using the Fitbit showed a significant change in their fitness whereas the standard pedometer women did not. This is a very useful insight into the impact that not just any old wearable technology, but the Fitbit specifically, has on people of all ages.
The reason as to why the Fitbit stands out against the others may be due to the mobile phone app that comes with it. The Fitbit itself gives a brief summary of the information it tracks throughout the day, but the app is a whole world of insight. When you meet a target, 10000 daily steps for example, everything goes green and it throws you a mini party for a few seconds. Could this be why it is so successful and why people want to keep using it?
A large part of the quantified self is not just the devices but the applications on smart devices which help the user to input and track the data the devices records. As the popularity of the applications has spread over the last decade there is now a Quantified Self Application for almost any part of someone’s life: fitness, health, sleep, diet, sexual behavior, moods and dreams etc.
Most manufacturers of Quantified Self Devices have now expanded into having their own apps. For example, if you buy a FitBit to record your steps, heart rate and sleep you can only track that data on the FitBit app. This allows for many other apps to form a relationship with these companies to allow for a more in-depth analysis of the data. For example, if you want to record your food and drink intake you would need to use a different app that is associated with FitBit.
Gary Wolf describes the application of Quantified Self data as 'the macroscope', a concept borrowed from Piers Anthony's 1969 novel of the same name, which referred to "a machine to view anything anywhere".. For Wolf, the concept translates to the ability of an indivdual to analyse their life as a " collection of countless moments, behaviors, and locations. Within the “n=1” of the individual is an “n=∞” of times, actions, and places."
The recording of physical data allows the user to track a variety of metrics relating to their health and well-being. Weight, digestion and calorie intake analysis allows the user to modify their diet and track how their body reacts to different foods. Sleep analysis allows the user to identify poor habits and health risks such as sleep apnoea. Posture and gait tracking gives the user insight into their movement and body-shape, allowing for adjustments to avoid future health complications.
Many users are also able to record data based on their sexual experiences and use this to look at how their body and physiology changes throughout these experiences. Analyzing this data allows the user to see which part of their health is struggling from the strenuous exercise and how this could be improved. This also raises a lot of ethical and privacy issues as to what data people should be recording.
It is not just physical elements that can be informed by data collection. Psychological health can also be tracked and improved, with some claiming that this is an updated framework that is identified as the 'Qualified Self'. Mood tracking can inform Cognitive Behavioural analysis to evidence factors that influence the users state of mind. Breathing coaches within wearables and mindfulness apps can intervene in anxiety attacks, supporting the user in overcoming otherwise uncontrollable mental states.
All of these metrics, wearables and applications can be cross-referenced to provide a holistic overview and assist in linking factors that affect health and wellbeing.
The ability to use self-tracking to support health and wellbeing has informed the approach of medical professionals as well as individuals. A key development in delivering care for patients with Alzheimer's disease is the ability to track the whereabouts of patients categorised as 'wanderers'. Wearable technology allows caregivers to supply patients with tracking devices that are not contingent upon the user's ability to carry or use the monitoring device. Wearables can also be employed by health professionals to support care and rehabilitation for patients suffering from epilepsy, strokes and myocardial ischemia. 
More in-depth analysis can also allow medical professionals to develop health plans for individuals. Genomic data such as Single Nucleotide Polymorphisms (abnormal sequences in the genome), transcriptome (RNA expression data) and microbiome data all provide deep insights into the individual's potential health risks and inherited genetic markers. This, in turn, allows doctors to prescribe not just medicine, but also advise on whether regular screening is required.
Industry has been quick to adopt wearable technology and self-tracking as a facet of data analytics. Applications include automation of timesheet processes, dispensing with the need for an employee to 'clock in'. Supervisors can also track the online behaviour of employees such as browsing habits and project participation.Access to restricted areas in the workplace can be controlled by fingerprint/iris scans. More controversial uses include proposals for sub-dermal implants, keystroke logging  and wristbands that employ haptic feedback to influence and control employee behaviour.
Animal tracking has also emerged as a key component of both the scientific research community and farming industry. Scottish company, Ice Robotics, have developed wearable technology which is employed by both, allowing researchers to automate practices previously conducted in person and dairy farmers to improve the health and wellbeing of their herds.
The ‘Quantified-Self’ movement can be seen as a way to optimise one’s health and well-being. However, continuously tracking what you eat, how many steps you have taken, how much you sleep, etc. can have negative consequences on your mental health. In the article, 'The Hidden Anxieties of the Quantified Self Movement' by Candice Lanius she began to 'quantify herself' by using various technologies and applications to account for her daily life activities. From basic daily routines such as grocery shopping (using Grocery IQ) to physical activity (Fitbit) and what she eats in a day (MyFitnessPal). She discusses her experience and makes obvious that this can be the experience for many who decide to track and monitor aspects of their life. Lanius notes how, “after the novelty wore off, however, I found self-tracking and self-monitoring created restrictions on my life” . Lanius looks deeper into the personal effects that self-quantification has on individuals, physically, mentally and emotionally and how it can cause limits on your life.
A lot of her time was spent using her devices and apps to input data and some of this period was even spent trying to optimise her time using an application which is meant to help you be more productive, "The effort input into tracking 'work sprints' and overall productivity cost me precious minutes of break time" . This is ironic as this application's purpose is to enhance your time, however consumers end up spending some of that precious time inputting data. However, Lanius felt that "wasted time was not the only or most insidious effect self-tracking applications had on me". Through monitoring herself, she found how she would get ‘anxiety’ when the data she received was condemned as ‘poor’. She then started to notice changes in her lifestyle such as not enjoying her meals because of the restrictions on the intake of calories and taking a longer and uncomfortable route so her GPS could get a signal to properly work. This highlights how self-tracking and monitoring can have an impact on your body and behaviour and this isn't always in a positive way. Also, people are growing ever more scared of the unknown nowadays as so much information is available very easily and the quantified self-movement is adding to this as people can tend to be less spontaneous in their actions as this may not be ‘quantifiable’ and therefore they do not want to part take in it as they cannot bear to feel the guilt of not accounting for it.
Monitoring and tracking many aspects of your life also leads many people to be uncomfortable with who they are and feel that they need to change themselves to be ‘perfect', “These outside forces guide citizens to become ideal subjects, and these forces are slowly internalized so that individuals want to become the best version of themselves as approved by the state” . The ‘Quantified Self’ movement can be destructive to someone’s self-image and create an idea that you have to fit to certain standards. However, Lanius also criticises some of the user’s personal gain through these applications as ‘a form of narcissism’ as it is used as a way of showing off your growth, meaning that they are only working hard to prove to others what they have accomplished rather than working hard for the benefit of their personal gain.
The data that is put into these self-improving applications can later be sold ‘on the dark web’, as stated by Mathew Aldridge in his article ‘Evolving perception of personal data in 2019’. Aldridge states that “companies held in high esteem and who are regularly trusted with sensitive personal data are successful targets of cyberattacks”. This means that consumer data is too easily sold from one company to the next without the customer’s knowledge and they might even sell the data for a profit gain.
In 2018 ‘MyFitnessPal’, an application used for calculating daily nutrient and calorie intake, was part of the 620 million accounts that were sold on the dark web . “While it doesn’t sound like hackers will be able to check on what MyFitnessPal users ate for breakfast, the leaked credentials could be a problem for people who reuse passwords across multiple websites. This means a buyer may easily be able to access a lot of personal information about a user, especially if they are able to get a hold of their email. This conveys how there are some negatives to the ‘quantified self’ movement.
- Lupton, D. (2016). The quantified self: A Sociology of Self-Tracking Cultures (1st ed.). Cambridge: Polity Press.
- Eknoyan, G. (1999). Santorio Sanctorius (1561–1636)–founding father of metabolic balance studies. American journal of nephrology, 19(2), 226-233.
- Forde, S. (1992). Benjamin Franklin's Autobiography and the education of America. American Political Science Review, 86(2), 357-368.
- Grue, L., & Heiberg, A. (2006). Notes on the History of Normality–Reflections on the Work of Quetelet and Galton. Scandinavian Journal of Disability Research, 8(4), 232-246.
- Rafter, N. (2005). The murderous Dutch fiddler: Criminology, history and the problem of phrenology. Theoretical Criminology, 9(1), 65-96.
- Swan, M. (2013). The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery. Big Data, 1(2), 85–99.
- Wolf, G. (2009). Know Thyself: Tracking Every Facet of Life, from Sleep to Mood to Pain, 24/7/365. Retrieved from https://www.wired.com/2009/06/lbnp-knowthyself/
- Lupton, D. (2016). 'An Optimal Human Being'. In "The quantified self" (pp. 49-65). Malden, MA: Polity.
- Didžiokaitė, G., Saukko, P., & Greiffenhagen, C. (2017). The mundane experience of everyday calorie trackers: Beyond the metaphor of Quantified Self. New Media & Society, 20(4), pp.1470-1487.
- K. Montgomery; J.Chester & K.Kopp; (2018) Journal of Information Policy; Published by: Penn State University Press
- Haynes, K., 2015. The Fitbit generation: From couch potato to marathon runner. Significance, 12(6), pp.24-25. Retrieved from https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1740-9713.2015.00864.x
- Cadmus-Bertram, L.A., Marcus, B.H., Patterson, R.E., Parker, B.A. and Morey, B.L., 2015. Randomized trial of a Fitbit-based physical activity intervention for women. American journal of preventive medicine, 49(3), pp.414-418. Retrieved from https://www.sciencedirect.com/science/article/pii/S0749379715000446
- Wolf, G. (2019). Quantified Self | Antephase. Retrieved from http://antephase.com/quantifiedself
- Wolf, G. (2019). QS & The Macroscope | Antephase. Retrieved from http://antephase.com/themacroscope
- Wolf, G. (2019). Quantified Self | Antephase. Retrieved from http://antephase.com/quantifiedself
- Piwek, L., Ellis, D. A., Andrews, S., & Joinson, A. (2016). The rise of consumer health wearables: promises and barriers. PLoS Medicine, 13(2), e1001953.
- Bianchi, M. T. (2018). Sleep devices: wearables and nearables, informational and interventional, consumer and clinical. Metabolism, 84, 99-108.
- Samadder, R. (2019). Upright Go: a device that buzzes if you dare to slouch, like a slap from your mother. Retrieved from https://www.theguardian.com/lifeandstyle/2019/mar/18/wellness-or-hellness-upright-go-rhik-samadder
- Lupton, D. (2015). Quantified sex: a critical analysis of sexual and reproductive self-tracking using apps. Culture, Health & Sexuality , 440-453. Retrieved from https://http://www.canberra.edu.au/researchrepository/file/25d1310f-2c5d-4ca5-9e8e-c17f1a140cb1/1/full_text_postprint.pdf
- Prince, J. D. (2014). The quantified self: Operationalizing the quotidien. Journal of Electronic Resources in Medical Libraries, 11(2), 91-99.
- Linden, J. (2018). Qualified Self: Quantified Self’s AI-powered replacement?. Retrieved from https://medium.com/@jameslynden/the-rise-of-the-qualified-self-e2b0b27bf639
- Mahoney, E. L., & Mahoney, D. F. (2010). Acceptance of Wearable Technology by People With Alzheimer’s Disease: Issues and Accommodations. American Journal of Alzheimer’s Disease & Other Dementias®, 25(6), 527–531. https://doi.org/10.1177/1533317510376944
- Raskovic, D., Martin, T., & Jovanov, E. (2004). Medical monitoring applications for wearable computing. The computer journal, 47(4), 495-504.
- Swan, M. (2012). Health 2050: The realization of personalized medicine through crowdsourcing, the quantified self, and the participatory biocitizen. Journal of personalized medicine, 2(3), 93-118.
- Cameron, F. (2019). 6 Employee Tracking Apps That Can Benefit Small Businesses In 2018 - The Next Scoop. Retrieved from https://thenextscoop.com/employee-tracking-apps-small-businesses-2018/
- Cuthbertson, A. (2019). Plans to microchip UK workers spark privacy concerns. Retrieved from https://www.independent.co.uk/life-style/gadgets-and-tech/news/microchip-uk-workers-employees-privacy-bioteq-biohax-cbi-tuc-trade-union-a8629656.html
- Ciocchetti, C. A. (2011). The eavesdropping employer: a twenty‐first century framework for employee monitoring. American Business Law Journal, 48(2), 285-369.
- Solon, O. (2018). Amazon patents wristband that tracks warehouse workers' movements. Retrieved from https://www.theguardian.com/technology/2018/jan/31/amazon-warehouse-wristband-tracking
- IceRobotics Research Projects. (2019). Retrieved from https://www.icerobotics.com/research/
- Lanius, C. (2015). The hidden anxieties of the quantified self movement, Cyborgology, 5 May 2015.
- Aldridge, M. (2019). Evolving perception of personal data in 2019. Retrieved from https://www.techradar.com/news/evolving-perception-of-personal-data-in-2019
- Newcomb, A. (2019). http://fortune.com. Retrieved from http://fortune.com/2019/02/14/hacked-myfitnesspal-data-sale-dark-web-one-year-breach/
- Sharma, J. (2019) Top 8 Effective Advertisement Campaigns to Boost Your Business- TheNextHint. Retrieved from https://www.thenexthint.com/effective-advertisement-campaigns/