Dealing with numbers. Looking beyond the self-monitoring for a new technology of the self

24 Dec
Veronica Moretti

Introduction

We have always been quantified. What has changed today is the modality by which we collect our personal information. Nowadays, sensor and wearable devices allow people to collect data easily and immediately (Neff & Nafus, 2016). What is self-tracking? We can define it as “the practice of gathering data about oneself on a regular basis and then recording and analysing the data to produce statistics and other data (such as images) relating to regular habits, behaviours and feelings” (Lupton, 2014: 1). Several causes led individuals to start to monitor themselves; to improve their health, to increase their physical or mental performances or find new stimuli (Choe et al., 2014).

Through data-collection people get more awareness about their condition. Moreover, graphs and charts confer more objectivity to the self-tracking activity. This communication form through numbers is one of the main characteristics of modern societies. Individuals are perceived as entrepreneurs who, according to the standards proposed by new liberal societies, have to realize a complete transformation of him/herself in order to achieve happiness, pureness, wisdom, perfection and immortality (Foucault, 1992: 13). Nevertheless, it is not correct to think upon a numeric hegemony on the humans activity because “like words, numbers also can be evaluated in terms other than their accuracy as representations […] Numbers that defy conventions or expectations can be infelicitous as well as wrong” (Espeland & Stevens, 2008: 403). In this perspective, objectivity is a question of legitimacy, a view of understanding things in a certain way.

When people record, analyse and reflect on data about themselves they work as a laboratory. Indeed, self-tracking promotes – or attempt to – a mutation in our life. The self is made by a negotiation of a lot of things. The interaction with data, with technology and with other people is really intense. Measure can cause people to think, and consequently to act, differently. Additionally, as shown by Ms Farzana Dudhwala during her intervention “The ‘Sobjective’ Self: A Paradoxical Multiplicity”, if self-tracking fosters our performances, how can we be the same person? How can constancy be achieved?

In this section I analyse the main dimensions in which self-tracking is experienced by people and how these activities are presenting two new aspects of the modern-quantified human being: fluidity and multiplicity. With the first element we consider an intensification of subjectivity through mechanical objectivity and, at the same time, an experience of union, play, space and intensification of senses. With the second aspect we look at self-tracking as something that forces people to organise their lives in a market manner because improving aspects of our life it is necessary to establish a self-optimization of our productivity.

 

Fig. 1 (left): An app a day keeps the doctor away.
Courtesy of Hilda Bastian

 

Below I report three areas in which self-tracking activity stimulates a debate as to the reasons behind them and describe some of the interventions in the session.

Self-monitoring at work. With regard to practices of self-monitoring in the workplace, technologies promote a way to encourage both employers and employees to be more aware of their performances. On one hand office workers can use a self-monitoring device to critique their workplace culture. As was shown by Miss Amie Weedon during her intervention “Self-monitoring as work: office workers use of a self-monitoring device to critique their workplace culture”, through apposite devices (such as Lumo, a belt that vibrates every time we slouch to remind us to sit tall and stand straight), employees can report negative conditions of their body. The other side of the coin concerns productivity-monitoring. Using apps (such as RescueTime or Worktime) employers can track the progress of the users (employees) to achieve agreed goals (Lupton, 2016). In this perspective, gamification is an important dimension for new approaches of self-monitoring in the work place. Through the use of game elements in non-game context, it is possible “to increase influence and encourage engagement and activity” (Luminea, 2013 p. 13). Corporate companies foster these game strategies for improving wellbeing (and productivity) among workers.

Self-monitoring and wellness. Through new forms of training our wellness can improve automatically. The body can be programmed and, using our data, governed. Several tools have been created to achieve this maximisation of our capabilities. The self-tracking activity, applied to wellness, consists of a digital and scrupulous registration of some physical parameters: this data-gathering consists of the digital and meticulous recording of physical parameters, such as number of burned calories per day, heartbeat, level of anxiety and stress, quality of sleep, blood pressure and also body mass index (Maturo, 2015).

Nowadays, these tools are more precise and something we can combine. A lot of wearable devices are using apps, as shown by Dr Martin Berg during his presentation “Smart jewellery: measuring the unknown”, such as Oura, wellness (ring+ app) to improve the measurement. Big brands are producing objects which are able to measure physical parameters even if they maintain pleasant features. Some examples are Swarovski necklaces, having crystal-encrusted fitness and sleep trackers, or the Polo Tech Shirt, created by Ralph Loren embedded with a body metric sensor (Lupton, 2016).

 

Fig. 2 (right): Quantifying the human body
Courtesy of Paul Abramson.

 

Self-monitoring and health 

Self-tracking to monitor and improve health has already become a common practice (Neff, Nafus 206). Technological objects and artefacts become constituent elements of the clinical encounter between doctor and patient 2.0. As shown by Dr Maki Iwase in her intervention “The Glucometer: Figures don’t lie, but women figure”, due to technology, especially with the possibility to collect a lot of information in real time, people are becoming patients earlier than before. Moreover e-health policy is promoting health and care by means of technology and consumer apps. This collection of data also increased the value and the use of personal health data for prevention of early diseases and there is no clear boundary between what is self-monitoring and medical monitoring.

For this reason, technological instruments could facilitate health self-management, creating a new form of patient who is responsible for his or her care and for the collection of data used for the supervision of the disease (Bruni & Rizzi, 2013).

 

Data-meaning

Through self-monitoring, contradictory evidence in self-tracking can appear.

Living algorithmically can lead people to have a bias to accept confirmatory evidence of the collected data because subjective reporting is often different from an objective measurement.

Sometimes the mouth expresses stress but the heart does not. In addition, self-tracking activity does not guarantee that the person will avoid being prescribed insulin. For this reason it is important to consider the relationship between individuals and their data because “self-tracking data has a vitality and a social life of their own, circulating across and between a multitude of sites” (Lupton, 2016: 88). Cultural, politics, ethical and social issues are raised by the big data movement. Being a data citizen prompts new forms of data work. For this reason we can talk about data as social lives, because they have an impact on life, on the new digital-self.

Through numbers we can become more aware of our bodies’ states, with the peculiarity that nowadays “data in more people’s hands is not neutral; it can create or undermine beliefs” (Neff & Nafus, 2016:17).

Numbers, created through self-tracking activities, are elements socially built that do not offer a neutral worldview but, on the contrary, describe our reality while influencing whoever is using them (Neresini, 2015). In this way numbers are not describing reality but creating it. They also represent what Latour defined as “immutable mobiles” that help us to get a better understanding of our endeavours. Furthermore, immutable mobiles facilitate the proliferation of information through society, greatly expanding the scientific revolution as well as present culture (Latour, 1986).

Conclusion

Self-monitoring in everyday practices aims to enhance performance and productivity. Through motivation and self-discipline it is possible to reduces contradictory experiences (moving towards an optimization of our skills/capabilities) and to celebrate a new process of knowledge about ourselves. The integration between individuals and technology is becoming increasingly composite “as technical activities have become more pervasive and complex, demand has grown for more complete and multivalent evaluations of the costs and benefits of technological progress” (Jasanoff, 2003: 243).

Nevertheless it is important not to exclude some negative aspects of self-monitoring. First of all data collection, if becomes an obsession, can overload individuals. At the same time, with regards to self-tracking and health, patient lives in the balance between instruments that facilitate the task of self-management and considerable pressure due to the transfer of the responsibility of care from the doctor to the patient. In fact, it is not easy to establish if these instruments can effectively improve the quality of patients’lives or are only a short-cut to reducing the operating costs of care services.

Finally, individuals who are controlling other humans through the so-called interveillance can create some mechanisms of social exclusion. Indeed, in our digital era, whoever refuses to be under these practices of control refuses to be a part of the society itself.

References

Bruni A & Rizzi C (2013) Looking for Data in Diabete Healthcare: Patient 2.0 and the Re-engineering of Clinical Encounters. Science and Technology Studies 26(1): 29-43.

Choe EK, Lee NB, Lee B, Pratt W & Kientz JA (2014) Understanding Quantified-Selfers’ Practices in Collecting and Exploring Personal Data. ACM, 1-10.

Daston L (1992) Objectivity and the Escape from Perspective. Social Studies of Science 22 (4): 597-618.

Espeland WN & Stevens ML (2008) A sociology of quantification. European Journal of Sociology, 49(3): 401–436.

Foucault M. (1992) Tecnologie del sè. Torino: Bollati Boringhieri.

Jasanoff S (2003) Technologies of humility: citizen participation in governing science. Minerva 41: 223–244.

Latour B (1986) Visualization and Cognition: Thinking with Eyes and Hands. Knowledge and Society. Studies in the Sociology of Culture Past and Present, 6: 1–40.

Lupton D (2016) The quantified self. Cambridge: Polity Press.

Neff G & Nafus D (2016) Self-tracking. London: The Mit Press

Neresini F (2015) Quando I numeri diventano grandi: che cosa possiamo imparare dalla scienza. Rassegna Italiana di Sociologia LVI (3-4): 405-431.

Wolf G. (2010) The Data-Driven Life. The New York Times: 1-12.

Maturo A (2015) Doing Things with Numbers. The Quantified Self and the Gamification of Health. eä Journal, 7(1): 87-105

Author information

author Veronica Moretti is a Ph.D. student and teaching assistant in Sociology and Business Law Department at the University of Bologna. Her research interests focus on the intersections between technologies and human activities, with specific emphasis on the interrelationship between self-tracking, health, risk and new forms of surveillance.
 

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