Modern societies are hardly to imagine without the omnipresence of technological media. Individuals are constantly surrounded by communication technologies and their behavior is influenced by such (Nieland 2016: 105). The use of cellphones or other mini computers has become so convenient, resulting these technological devices to remain as our constant companion (Lupton 2016: 9).
Through the meta-trend of big data, it has become possible for our devices to constantly keep track over every step we take, every interest we might pursue and every obstacle we try to overcome (Selke 2014: 13). Data accumulation on its own, however, remains worthless. What adds value to the datasets is their analyzation, eventually giving useful and deep insights into the behavioral patterns of the user (Kitchin 2014: 1). Personal details of friendships or interests in music, food, preferred gym places and workout routines – even when it comes to more intimate preferences, like which partner to choose – your devices know it all.
Data tracking consists out of two dimensions, a passive form of self-tracking and an active form of self-tracking. Through passive tracking, for example, great amounts of transactional data are collected additionally if the user is connected to GPS. Further data is collected through cookies which are downloaded automatically if the user is logging her-/ himself into a network. The active form of self-tracking, however, is highly connected to the use of self-tracking tools. Meaning the user is gathering large amounts of data about oneself and might even share them with a community.
The tracking device and its recommendations are believed to be the most reliable source of modern times, supported by the belief that throughout the individual will know more about her-/himself without being reliant on an expert’s knowledge.
The belief in data being more reliable and trustworthy is crucial and implies a whole new behavioral trend within modern society (Lupton 2016: 9). This trend is called the quantified
self-movement, which refers to self-tracking practices in general (ibid.). Throughout, various further terms have been used to describe the same phenomenon: “[…] lifelogging, personal informatics, personal analytics […]” (Lupton 2016: 9).
The movements motto: “Self-knowledge through numbers” (Missomelius 2016: 256), summarizes the self-tracking community’s belief, that the devices of self-tracking are actually more honest than any friend, mentor or consultant ever could be, most precisely (Reigeluth 2015: 32). Through the promise of being able optimize oneself constantly while keeping track over one’s data, concerned to health, fitness or any other related personal issues, the movement is tempting and revolutionizing the relationship of technological devices and their owner (Nieland 2016: 105).
In its core, what makes the idea of the digitized self-tracking so successful is the promise of empowerment. However, to be empowered in the sense of data tracking, the tracking tools intention lies within transforming the user into an object that is calculable, administrable and easy to categorize (Reichert 2015: 66). The individual shifts in this context from a mysterious being towards an administrable object (Reichert 2015: 66).
These observations however, are appreciated by two very opposing agents. On the one hand by the user her-/ himself, who is gaining thereby more self-knowledge. On the other hand, these analyzations are highly valued by companies, which increasingly try to exploit personal data (Selke 2014: 21).
However, as clarified before, through the use of self-tracking apps and devices the user is steered and modified. While the user’s behavior mistakenly seems to be steered out of free will and self-intention, it actually is done so by third parties. Within the process of fitness-tracking for example the power balance is shifted from lying within the user towards the device and the entities lying behind it. The more data the fitness-tracker generates, the more power the device gains to reach the user’s consciousness and with it steer its behavior. The ability to steer and manipulate the user via marketing strategies even exceeds over time through reaching the subconscious of the user. Such digital monitoring possibilities are a dream for entities gaining large profits out of the collected data. This concept however, is further applicable to numerous further activities of self-tracking and data collection in general – all forms of data tracking, including active and passive forms of data tracking.
The user is therefore evidently not solely tracking the data for her or his own sake. The tracker is doing this for the very profit of third agencies. These are furthermore not only the tracking companies but also several other companies related to the core of the tracking as for example when looking at fitness tracking, we would talk about fitness related companies. They can eventually use the data to generate better marketing strategies, as also mentioned in the section above. Such adjusted marketing strategies furthermore sell the user exactly what they think they need – opening up another sphere of controlling the user (Dwyer 2016: 9). It seems to be an endless circle, wherein the actual intentions of the user get lost and manipulated.
However, let’s presume the user actually becomes fitter and becomes self-optimized in a way she or he intended. Along the way the user will have contributed to the profit of companies she or he might not even be aware of. And instead of getting a salary for the work the user has contributed to the profits of the third players, she or he is more easily to be exploited in return. This activity by the user is already nowadays recognized as “Datenarbeit” (translated: Data-work) (Heilmann 2015:43).
To clarify that the data work is intentionally used by third agencies and is intentionally applied, a perspective of a salesmen follows.
Tim O’Reillys has spoken at a conference called “Web 2.0-conference”. He states: “Customers are building your business for you […] set inclusive defaults for aggregating user data and building value as a side-effect of ordinary use of the application.” (Heilmann 2015: 40). What he means by that is exactly what was mentioned above. The user ads value through tracking for the companies themselves and furthermore this contribution is calculated within the business models of such firms. The guidance towards self-disciplining the user is intended for the seller’s own profit. Crucially, however, is that this form of labor is not perceived as such by the user (Heilmann 2015: 41). And it is this degree of unconsciousness lying within the user, which is highly critical.
Michael Foucault has described a term called “Governmentality” adding value to this discussion. The term in a broader sense wants to examine governance as the exercise of “[…] conduct of conducts […]” (Walters 2012: 11). The intention within governmentality hence lies within the understanding and shaping of the ‘conduct or the conduct of others’ (Walters 2012: 11). Accordingly, the tracker is governing her or himself through tracking with the very specific aim of self-optimization. This act is comparable to the description of Foucault’s ‘conducting the self’.
Foucault further states that the most effective acts of governing “[…] generally seek to incentivize rather than punish, and to guide rather than to coerce […]” (Valverde 2017: 81). In this way the user is emphasized to govern her-/ himself towards the managed aim of the community: which in the quantified self-movement is self-optimization. On the surface self- tracking is perceived as freedom of choice and thereby the user seems to follow her-/ his own desires and aims. This is decisive for effective governmentality as in turn, however, the user is not necessarily acting out of free will (Foucault, 1978: 144). Merely she or he acts out and is motivated through the steering mechanisms generated through the tracking-device. This structure of governing the self is in our modern times extendedly common also in further areas of life.
As if the individual itself is disciplined and through this self-discipline acts as the conductor intentions it, the relations of power are through the eyes of the individual lying within them. The conductor in this case, could be represented through multiple other subjects. Such as for example the companies which are selling the devices, or the companies buying such data and using them for their own marketing strategies. Already scientific studies show that institutions in fact have the power to affect how a consumer feels and acts, without the consumer knowing it. This fact not only highlights the significance of this argument, furthermore it underlines the usefulness of Foucault’s term of governmentality (Reichenstein, 2018).
Technology is in this sense not making our life’s more efficient, it is reshaping our behavior. Conveniently, this process has led to the emergence of a self-surveillance culture, which in the end can be recognized as a commercial surveillance of every aspect of the user’s life.
As this process goes on however, let us imagine what would happen if instead of corporation’s governments would exploit the data. The reaction of society would probably be much more critical. However, in fact, corporations are throughout slowly on the path to gain total control over a significant part of their customer’s life. Therefore, in modern times totalitarianism is slowly gained by other parties than the government, and also in a much more intransparent manner.
Characteristics of totalitarianism such as force, terror, and forbidden freedom of speech, are not to be recognized within the context of self-tracking. However, further characteristics of a totalitarian state such as subordination of the individual within a group, surveillance and detailed knowledge and eventually control of behavior of the individual are already more suitable descriptions of what is happening nowadays within our controlled society (Jaschke, 2008). What has changed is only the perception of the one being controlled – just in the sense of governmentality’s optimal practice. The individual seems to be having control, when in fact he has not. Moreover, when comparing the scope of power corporations have nowadays over their user, to old totalitarian regimes, such as the Nazis or the Soviet Union, our modern way of surveillance has outraced these old regimes methods by far.
Here one must still differentiate that officially totalitarianism is a political rule, which decrees over unlimited power over society which is totally subjected towards the regime. Furthermore, that total power and control is achieved through tyranny, force and violence (Jaschke, 2008). However, in a more modern approach of totalitarianism, tyranny, force and violence might not be necessary anymore, as the quantified-self controls itself already and is keen to share. In times of Stalin, a movement like the quantified-self, would have gained a lot of political sympathy.
To sum up, the act of self-tracking becomes falsely to be recognized as resulting out of freedom of choice. As the entities collecting this data have nothing in common with the wish to empower the user solely for the users own sake. The user is a valuable consumer and as long such entities are able to steer the behavior of the consumers to maximize their own profits, they will do so.
Ironically, the original intentions of the self-trackers to gain more self-determination through self-knowledge, eventually lead to a limitation of the individual and a loss of control towards the devices, institutions and international corporations (Duttweiler & Passoth 2016: 24).
The data collected by the user furthermore not only allow steering mechanisms to unwind. They also allow deep insights into the user’s lifestyle and their behavior in general (Lupton 2016: 42). This new form of data collection through disciplining the user, comparatively intervene deep into the user’s privacy (Lupton 2016: 84). The self-tracking tool reshapes itself into a surveillance tool (Duttweiler & Passoth 2016: 9).
Throughout, the self-tracking community eventually paves the way for total control. In which however the side effects politically remain to be examined and are highly dependent on the political system the user is living in. However, one can only imagine what happens if such amounts of data come into false hands. If such totalitarian political power would occur in the future, there would be no way truing back and demand that one’s own data will be used carefully – big data has saved everything.
Furthermore, the self-tracking tool does not grant any place for contentment. It is an illusion that the optimum self is ever to be reached. As the optimum of the self is not to be found within comparison and correlated graphs. It is solely found within and is rather classified by each individual. For commercial purposes the data gathered and evaluated might just be precise enough. To expand self-awareness of a human being to further get more self- knowledge, however, the collected data is not enough. The question lies therein to what extend the devices actually are able to track what really matters to and characterizes us as human.
The price occurring out of these means, such as growing restlessness and dissatisfaction, is then paid by the user. It should be seriously reconsidered when the pain barrier is reached – What price do we pay in relation to the actual profits made by corporations?
A modern version of totalitarianism might have already found its way into society.
Bibliography:
Duttweiler, S., & Passoth, J.-H. (2016 ). Self-Tracking als Optimierungsprojekt? In S. Duttwieler, R. Gugutzer, J.-H. Passoth , & J. Strübing, Leben nach Zahlen. Self- Tracking als Optimierungsobjekt? (pp. 9-42). Bielefeld: Transcript Verlag.
Dwyler, T. (2016). Convergent Media and Privacy. Palgrave Global Media Policy and Business.
Foucault, M. (2004). Vorlesung 4. Sitzung vom 1. Februar 1978. In M. Foucault, Sicherheit, Territorium, Bevölkerung. Geschichte der Gouvernementalität I. (pp. 134- 172). Frankfurt am Main : Suhrkamp Verlag.
Heilmann, T. A. (2015). Datenarbeit im <<Capture>>-Kapitalismus, Zur Ausweitung der Verwertungszone im Zeitalter informatischer Überwachung. Zeitschrift für Medienwissenschaft , 35-47.
Kitchin, R. (2014). The Data Revolution . London : SAGE Publications Ltd.
Jaschke, H.-G. (2008, 1 31). Bundeszentrale für politische Bildung. Retrieved from Bundeszentrale für politische Bildung: http://www.bpb.de/politik/extremismus/linksextremismus/33699/totalitarismus?p=all
Lupton, D. (2016). The Quantified Self. A Sociology of Self-Tracking . Cambridge: Polity Press.
Missomelius, P. (2016). Das digitale Selbst – Data Doubles der Selbstvermessung. In S. Selke, Lifelogging. Digitale Selbstvermessung und Lebensprotokollierung zwischen disruptiver Technologie und kulturellem Wandel (pp. 257-286). Wiesbaden : Springer SV.
Nieland, J.-U. (2016). Optimierung als neues Leitbild – Anmerkungen zur Berichterstattung über die «Quantified Self-Bewegung». In A. Beinsteiner, & T. Kohn , Körperphantasien. Technisierung – Optimierung – Transhumanismus (pp. 105-119). Innsbruck : Innsbruck university press.
Reichenstein, O. (2018, February 7). iA Net . Retrieved from iA Net: https://ia.net/topics/take-the-power-back
Reichert, R. (2015). Digitale Selbstvermessung, Verdatung und soziale Kontrolle .
Zeitschrift für Medienwissenschaft , 66-77.
Reigeluth, T. (2015). Warum <Daten> nicht genügen, Digitale Spuren als Kontrolle des Selbst und als Selbstkontrolle. Zeitschrift für Medienwissenschaft , 21-34.
Selke, S. (2014). Lifelogging, Wie die digitale Selbstvermessung unsere Gesellschaft verändert. Berlin: Ullstein Buchverlage GmbH.
Valverde, M. (2017). Michel Foucault . New York : Routledge .
Walters, W. (2012). Governmentality, Critical encounters . New York : Routledge.