Details

Autor(en) / Beteiligte

• Schüll, Natasha D

Titel

The Data-Based Self: Self-Quantification and the Data-Driven (Good) Life

Ist Teil von

• Social research, 2019-12, Vol.86 (4), p.909-930

Ort / Verlag

New York: Johns Hopkins University Press

Erscheinungsjahr

2019

Quelle

EBSCOhost Business Source Ultimate

Beschreibungen/Notizen

• the capacity to amass, store, and analyze data drawn from the physiological, behavioral, and “geolocational” experience of individuals is growing at an exponential rate and spreading to an ever-wider range of social domains.1 In the “datafication” (van Dijck 2014) of everyday life, big data enthusiasts see a new and important opportunity: to transform areas of life typically known through their qualitative aspects into quantitative variables that can be measured and mined for hidden correlations and patterns. Such data, they argue, promises to yield objective insights into and answers for individual and social problems, increase our rational and predictive power, and provide new forms of self-determination. Yet many scholars are skeptical of these promises, highlighting the ways in which digital quantification technologies “permeate and exert power on all manner of forms of life” (Iliadis and Russo 2016, 2). Those who base their criticisms in Michel Foucault’s work on modern forms of power tend to approach datafication from one of two angles: some draw on Foucault’s early conception of disciplinary power (1977), focusing on the insidious surveillance capacities of datatracking technologies (Ruckenstein and Schüll 2017); others draw on his later conception of biopolitics (2010), focusing on the way that population metrics are mobilized to regulate society—and, in particular, how quantification serves a neoliberal governmental rationality that accelerates the withdrawal of the welfare state from citizens’ lives (Ruckenstein and Schüll 2017). Scholars working in a political-economic vein emphasize the “asymmetric relations between those who collect, store, and mine large quantities of data and those whom data collection targets” (Andrejevic 2014, 1673), as well as the ways quantification and algorithmic analysis alienate us from our own practical reasoning, intuition, and understanding of ourselves (Smith and Vonthethoff 2017). Selves are “sliced and diced into decontextualized parts, and bought and sold” (Neff and Nafus 2016, 62). Many invoke Deleuze’s (1992) idea of a control society and the dividual—a subject divided into ever more granular bits so that it may be sorted into and tracked through multiple data sets with the aim of algorithmically steering its behavior (Ruckenstein and Schüll 2017). Running through these varied criticisms is the claim that datafication decomposes the person: as this special issue suggests, we are becoming persons without qualities. Particular deployments of algorithms, artificial intelligence, and other technologies of quantification work against human agency and self-image, such that we are treated—and treat ourselves—as “uniform, averaged, smoothed out” (Davis and Scherz, this issue, 4). This essay does not run counter to this criticism so much as obliquely, seeking to explore a space between the poles of boosterism and readymade critique, entertaining the idea that data tracking and quantification might serve as aids to self-understanding and new forms of living. A conceptual entry point is found in the distinction that Foucault drew between technologies of power, “which determine the conduct of individuals and submit them to certain ends or domination, an objectivizing of the subject,” and “technologies of the self,” through which individuals perform “operations on their own bodies and souls, thoughts, conduct, and way of being, so as to transform themselves in order to attain a certain state of happiness, purity, wisdom, perfection, or immortality” (1988, 18). The case of contemporary self-tracking, in which individuals monitor and make meaning of their own everyday “data exhaust” via sensor-laden devices, smartphone apps, data-visualization software, and analytical algorithms, provides an ethnographic entry point. The popular Fitbit wristband, which tracks daily steps, is just the best known of an ever-expanding array of devices and apps for monitoring productivity, mood states, and mundane aspects of life such as sitting, chewing, and even breathing (Schüll 2016b). While self-tracking could certainly be characterized as self-surveillance, it lacks the punitive dimension of disciplinary technology. And, while it is true that device companies are invested in extracting value from consumers’ tracked data, it is also true that individuals are invested in deriving a different sort of value from their own tracked and quantified self-data. Individuals collect and reflect upon their data intentionally, gathering information about themselves so as to learn new things and experiment with self-transformation. In this sense, data-tracking technologies provide a new inflection point for older technologies of the self. The point, at least for some dedicated self-trackers, is to “arrive at realizations about who you are and how you might change,” according to Eric Boyd, the user and designer of tracking devices referenced in this essay’s epigraph.22 With self-tracking, “You set up this kind of external person or version of yourself, an avatar or companion—or something.” Echoing Foucault’s (1997) characterization of ethics as “establishing a relationship of oneself with oneself,” he continues, “You’re ultimately setting up a framework by which you can establish a relationship with yourself.” Exploring how self-tracking might serve as a technology of the self—as a means and a medium for self-understanding and creative transformation—allows for a richer understanding of datafication and its human dynamics. Grasping its ethical dimensions also opens up a more effective critique of its dangers and discontents. To explore these dimensions, my ethnographic window is the international community known as the Quantified Self.