Datafied Life: Techno-Anthropology as a Site for Exploration and Experimentation

Abstract

Techno-Anthropology recognizes the intertwining of technology with aims, needs, practices, and skills; ‘the techno’ and ‘the anthro’ are not only interconnected, but historically co-constituted. In this paper developments in ‘personal analytics’ are examined with the aim of proposing epistemological and methodological directions for techno-anthropological exploration. Personal analytics refers to the field of interactions that surrounds tracking various bodily and mental functions, including the analysis, visualization, and distribution of the data, thereby encompassing people’s involvements with measuring devices and data movements. By discussing findings from a self-tracking study that focused on heart-rate variability measurement, the article opens for scrutiny ways in which personal data can translate people’s selves into a format that is engaging and actionable. This, in turn, enables researchers to witness and critically assess a terrain where bodily and mental capacities, and life itself, are not taken as given, but become part of the processes of everyday sense-making and contestation.

Full text

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Forthcoming in Techne: Research in Philosophy & Technology
Datafied Life: Techno-Anthropology as a Site for Exploration and
Experimentation
Minna Ruckenstein
1
and Mika Pantzar
Abstract: Techno-Anthropology recognizes the intertwining of technology with aims, needs, practices, and
skills; ‘the techno’ and ‘the anthro’ are not only interconnected, but historically co-constituted. In this paper
developments in ‘personal analytics’ are examined with the aim of proposing epistemological and
methodological directions for techno-anthropological exploration. Personal analytics refers to the field of
interactions that surrounds tracking various bodily and mental functions, including the analysis, visualization,
and distribution of the data, thereby encompassing people’s involvements with measuring devices and data
movements. By discussing findings from a self-tracking study that focused on heart-rate variability
measurement, the article opens for scrutiny ways in which personal data can translate people’s selves into a
format that is engaging and actionable. This, in turn, enables researchers to witness and critically assess a
terrain where bodily and mental capacities, and life itself, are not taken as given, but become part of the
processes of everyday sense-making and contestation.
Key words: Techno-Anthropology, knowing capitalism, datafied life, personal analytics, Quantified Self
Techno-Anthropology – a disciplinary hybrid combining methodologies, findings, and attitudes from
anthropology, studies of science and technology, engineering, pedagogy, and ethics – has been
introduced as a scholarly endeavor that attempts to bring together research in various academic fields
to examine technology in relation to contemporary worldviews and practices. Because of its
numerous disciplinary roots, Techno-Anthropology is defined in multiple ways; rather than a unified
disciplinary field it is an approach that offers complementary reflections on complex phenomena. It
can explore and advance the uses and philosophical foundations of technology, or focus on the social
underpinnings of technology encounters. A further suggested role for a techno-anthropologist is that
1
Minna Ruckenstein, Consumer Society Research Centre, Department of Political and Economic
Studies, P.O.Box 24, 00014 University of Helsinki, tel. +358-50-5215828,
minna.ruckenstein@helsinki.fi

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of translator or mediator between technoscientific projects and the public, and between technology
developers and users (Børsen and Botin 2013a, 2013b; Elgaard Jensen 2013, 11-12).
The purpose of this paper is to outline some ways in which the emerging Techno-Anthropology
approach becomes a site for exploration and experimentation, where the alignments of ‘the techno’
and ‘the anthro’ may be highlighted and negotiated. In particular, we
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add to the work of Techno-
Anthropology that is concerned with emergent technologies, such as biotechnologies, and food and
health technologies (Birkholm 2013). In terms of anthropology, we promote research that detects in
everyday goals and practices larger organizing themes and principles in people’s lives and society –
in this case through demonstrating how people are entangled with technology through economic,
practical, and emotional connections. A rich body of anthropological research focuses on the
reproduction of everyday techno-relations (e.g. Edwards, Harvey, and Wade 2010; Ingold 2000, 289-
419). Marilyn Strathern (1992, 136), for instance, has written about the enablements and resources
offered by technology, observing how its assimilation causes society itself, as we know it, to
transform. In terms of emerging technology, this is an observation that lies at the heart of Techno-
Anthropology, highlighting the need to empirically engage with the dynamic ways in which people
and technologies co-construct their everyday conditions and possible futures, and the ways in which
people make technologies and are made by them. Additional conceptual guidance for; and
clarification of, this engagement can be derived from a philosophy of technology that critically attends
to how technologies are defined by, rooted in, and harnessed to cultural, political, and economic aims,
offering proposals for reconfiguring technology’s diverse possibilities (e.g. Feenberg 1991; Stiegler
1998.)
In order to share empirical guidelines with current and future practitioners in Techno-
Anthropology, this paper discusses empirical research on ‘personal analytics.’ Personal analytics
refers to a field of interactions connected with tracking and measuring various kinds of bodily and
mental functions including everyday movements, physical activity, and body weight, along with
technological devices promoting self-tracking that include scales, pedometers, sleep trackers, and
heart-rate variability measuring devices.
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In addition to tracking and measuring, personal analytics
comprises the analysis, visualization, and distribution of the data, thereby encompassing people’s
involvements with both measuring devices and data movements (Nafus and Sherman 2014;
Ruckenstein 2014). These developments tie in with the notion of the Quantified Self (QS), which
promotes the idea that self-monitoring tools, as they continue to enter daily use, offer an effective
means for people to understand their own lives as sets of numerical phenomena that can be examined

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and acted upon (Lupton 2014a). In line with this notion, we initiated a participatory self-monitoring
study that focused on heart-rate variability measurement and offered volunteers the opportunity of
joining a ‘self-tracking experiment.’
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In the following, we discuss the strengths and limitations of our
research in terms of its Techno-Anthropological context, describing how the data-driven market and
attempts to commodify research are linked to and have shaped our project, and investigating some
predispositions in our research design that affected the inquiry. Throughout the process, we detail
research findings that document the expansion of personal analytics and the diversity of practices and
politics that are connected to it; furthermore, emotional and practical aspects of self-monitoring are
discussed in an effort to identify questions relevant for Techno-Anthropological explorations.
Since our self-tracking experiment had an individualistic bias, we explored self-monitoring as an
intensely personal journey, one that focuses on health and self-realization, and is harnessed to various
social causes. Yet we also problematized the individualistic framing of our research design by
establishing links between personal analytics and capitalist developments. In doing so, we highlight
the seductive and indirect mechanisms of capitalist control that are fueled by the emancipatory and
creative potentials of technologies catering to people’s self-realization and social aims (Thrift 2005).
Here we follow an expanding literature that explores a recognizable trend in capitalism that feeds off
people’s self-expression, everyday practices, social aspirations, and problem solving skills in value
creation processes (Arvidsson 2005, 2009). Nigel Thrift (2005) has characterized this trend as
‘knowing capitalism’ that has “the effect of making knowledge into a direct agent of the technical-
artistic transformation of life: knowledge and life become inextricable” (Thrift 2006, 281). We
suggest that a focus on knowing capitalism within a Techno-Anthropological context allows the
exploration of how technologies, in this case self-tracking devices, act as interfaces and
communication devices that energize researchers and research subjects, construct knowledge, and
change perception. Therefore, this kind of approach can aid in efforts to explore how emerging
technologies work with the anthro-techno interface. Since personal analytics offers opportunities to
create and expand ‘the personal’ and ‘the everyday,’ it also functions as a means of boosting
difference and inserting that difference into the cycles of production and reproduction (Thrift 2006).
In other words, knowing capitalism is part of, and accelerates, research efforts to learn, through
empirical and participatory research, about the ways in which digital devices and the data that they
generate are both material to people’s lives and a part of knowing and valuing those lives.
The following discussion presents empirical material, organized around Techno-Anthropological
themes, that explores how technology engagements push us to rethink selves and the everyday when

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knowing itself is an integral part of accelerating the reproduction of capitalism. The material suggests
that aspects of life, such as ‘mind’ and ‘body,’ and ‘social’ and ‘physiological,’ are challenged and
transformed with the merging of technological offerings, existing competences, and social and
economic aims.
Engagements with tracking devices
Along with a profound interest in technology and innovation, techno-anthropologists need to be
conscious of the ways in which their projects are aligned with, and support, the interests and advances
of the technology market. One way to disengage from the most obvious aims of commodification is
to make Techno-Anthropology a value project that openly pursues and promotes socially responsible
modes of association between people and technology. Andrew Feenberg (1991), for instance, has
paved the way for exploring the use of technologies in a more human and democratic manner by
systematically working against their inbuilt reductionism. According to the promoters of Techno-
Anthropology, their mission is to build on the philosophy of technology that emphasizes responsible
engagements within hybrid techno-anthropological intentionalities locally and globally in order to
educate a new generation of socially and politically involved engineers who have internalized “an
ethics of presence” with a goal of creating technological solutions that foster empathy, cultural
understanding, and social responsibility (Børsen and Botin 2013a, 2013b). We add to this aim by
suggesting that an explicit goal for Techno-Anthropology should be to explore and to experiment
with the multiplicities of ‘the techno’ and ‘the anthro’ (Rabinow 2009). In order to become a truly
responsible value project, Techno-Anthropology needs to adopt a reflexive stance on how it aims to
produce value in people’s lives. One way to promote such a stance is by not relying on pre-existing
theological or philosophical principles, but by aiming at ‘qualified estimates’ that ask who benefits
from, and can build on, techno-anthropological endeavors (Birkholm 2013, 100).
The multi-disciplinary and trans-disciplinary goals of Techno-Anthropology align it with
contemporary commodification of research and higher education wherein disciplinary and
educational hybrids are sought. Educators and policy makers have lost faith in clearly bounded
disciplines, such as ‘engineering’ and ‘anthropology,’ and believe that multi-disciplinary knowledge
production better serves the economic and social revitalization of society. Consequently, academics
are encouraged to find ways to cross-pollinate their ideas and rethink their disciplinary comfort zones
in order to accelerate the circulation and commercialization of research and knowledge (Børsen and
Botin 2013a, 2013b). Our empirical research on personal analytics was a case in point: it was closely
linked to these aims in that it was funded by the SalWe Research Program for Mind and Body that

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expected that collaboration between researchers and companies would produce marketable products
and services. In terms of personal analytics, it is significant that in the current economic climate data
– whether represented as personal, open, big or small – are seen as important in generating and fueling
new markets (Nafus 2014; Nafus and Sherman 2014; Boyd and Crawford 2012).
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The data-driven
economy is an example of the drive in capitalism to know more in order to work actively with cycles
of production and reproduction to reveal unknown patterns that can reap benefits in various fields,
including health care, urban planning, and marketing (Swan 2012a, 2012b). By using self-monitoring
devices in our research, we became part of the collaborative economy wherein companies promote
research that takes advantage of their tracking devices in order to gain legitimacy and give credence
to claims of reliability for their offerings. From the perspective of Techno-Anthropology, however,
commodification is far from a simple process. While it typically aligns interests, creates new kinds
of intimacies, and encourages oneness, in practice collaboration per se does not create sufficient
conditions for commodification if the goals of collaborating partners are not intimately linked. In
order to maintain a reflexive attitude to our research engagements, we approached the field of personal
analytics with a critical attitude that is not the norm in profit-oriented contexts. Ultimately, we were
acutely aware that we needed to understand the emerging personal analytics market in its historical
context in order not simply to replicate its aims when reporting our research findings.
In an effort to create a more contextual account of personal analytics, we started to explore the
notion of ‘the quantified self’ – the archetypal figure of the QS discourse– currently being promoted
in the marketing of health recording devices, self-diagnostics, and bodily sensors. The quantified self
refers to an ideal type of person who enthusiastically engages in self-improvement and self-
optimization, the underlying assumption being that when people know more, they will act on that
knowledge (Lupton 2014a, 2014b). Significantly, self-tracking is not a novel practice, but rather a
fundamental way of being in the world (Foucault 1988). Historically people have monitored their
eating, drinking, expenditure, sexual behavior, and many other practices, so what appears to be new
is also a routinized aspect of everyday self-enhancement and introspection. This insight explains why
tracking technologies can find a place in people’s everyday lives with relative ease: many people
already engage in some form of this practice. Importantly, tracking devices measure and interpret
body-related evidence that would otherwise remain hidden and undetected; the visibility of bodies
and minds produced by personal data streams offers the promise of improving one’s health,
happiness, and performance via calculative processes and algorithms (Viseu and Suchman 2010).
Thus, the data-driven quest for a better life unveils assumptions about the nature of the human body,
particularly with regard to how the body is seen to reflect and to become intertwined with

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technological developments, something which ties in with a long-standing research tradition in this
field. At the time of the industrial revolution the human body was represented as an engine, with input
and output mechanisms in the form of pipes and pistons. In digital culture, the body is represented as
a smarter machine: an integral part of the information system (Lupton 2013b, 26-7). Wired magazine
(Goetz 2011) describes how self-tracking tools offer information to people about their minds and
bodies in the form of feedback loops, with a similar operating principle to a home thermostat which
fires the furnace to maintain temperature. What is crucial for a feedback loop is that the information
gained through self-tracking needs to be displayed to people, preferably in real time, allowing them
to relate to their previous experiences and modify their bodies and behavior accordingly. Feedback
loops entwine ‘the techno’ and ‘the anthro’ – the idea being to merge machine intelligence and
learning with people’s everyday doings.
As our research progressed, we learned that the international Quantified Self community, built
around meet-ups and conferences, also problematizes self-optimization, demonstrating ambivalence
in relation to it, and trying to reach beyond it (Nafus and Sherman 2014). This underlines the fact that
as personal analytics becomes more commonplace, questions arise concerning how, and for what
purposes and benefits, personal data could and should be used (Nafus 2014). While the theme of self-
optimization remains an important stabilizing element in personal analytics , it would be too simplistic
to treat it as an all-encompassing aim. Technologies offer guidance and agentic power to users
concerning how they should treat the body, the self, or nature, but they cannot determine such
treatment. From the perspective of Techno-Anthropology, it is the culture that is inscribed in
technology development that is significant: the enduring aims of efficiency and the reduction of
uncertainty that technologies promise and promote (Feenberg 1991). Transparency is also seen as
desirable; not-seeing and not-knowing are states to be avoided and overcome. This latter goal is,
however, never fully realized, because the alignments of the body, technology, and everyday
experience continue to carry elements of the unknown and unforeseeable (Irwin 2005; Mol 2008;
Suchman 2007; Wellner 2014).
By formulating a research agenda that aimed at detecting the merging of technological offerings,
existing skills and competences, and social desires, we carved out a space for an endeavor that
critically witnessed and mediated emerging interactions in the field of personal analytics. We did not
take the field of study for granted but, rather, documented a process of expansion and divergence
within personal analytics wherein various kinds of developments are being tested and enhanced
(Pantzar and Ruckenstein 2015). From the perspective of Techno-Anthropology, the way in which

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engagements between technology and scholarly research are to be described and brought into
existence is significant: the more contextualized the research account, the more reflexivity it offers
for understanding the processes of knowledge formation that consolidate and authorize the research
findings. In terms of the research being discussed here, we adopted an open-ended strategy focusing
on what is being promoted by people’s engagements with tracking devices, learning, for example,
about the playfulness and creativity people introduce when interacting with them. Another related
research finding, discussed below, confirmed that people actively use self-tracking data for framing
social wholes and entities, giving a new kind of value to their personal realities and everyday
activities. Thus our research design brought us into a field where people interact with personal data
in ways that raise questions about how technologies participate in the formation and reformation of
daily lives.
The making of technological subjectivities
One strand of enthusiasm for personal analytics focuses on its promise to accelerate the goals of
public health by active health risk avoidance (Swan 2009). From this perspective, personal analytics
can be treated as integral to processes that “seek to act upon and instrumentalize the self-regulating
propensities of individuals in order to ally them with socio-political objectives” (Miller and Rose
1990, 28). Research into personal analytics can uncover the heterogeneous strategies and discourses
that position the self-tracker as a responsible citizen, willing and able to take care of his or her
individual happiness and wellbeing. Yet rather than merely confirming a narrative of ‘the response-
able citizen’, it is a fruitful techno-anthropological research strategy for exploring the making of
subjectivities (Foucault 1988). With the goal of examining how self-monitoring is, or might become,
a purposeful activity, we invited research participants to form new kinds of alliances with measuring
devices. For our research purposes, we distinguished between the monitoring embodied in top-down
governance and corporate enterprise initiatives, and self-monitoring as an individualistic practice in
the spirit of the Quantified Self (see Lupton 2014b); the emphasis on the latter meant that we had to
think about the borders and definitions of ‘the individual.’
In the personal analytics market, a prominent perception of the individual is that of a historically
flat, non-reflexive, and rational human being in search of actionable knowledge. Moreover, the focus
tends to be on so-called lead-users, or early-adopters (Pantzar and Ruckenstein 2015; Ruckenstein
2014). By discussing self-tracking from the perspective of volunteers, who typically had a systematic
and disciplined relationship to sports and exercise and a keen interest in self-monitoring technologies,
our research design had an obvious bias.
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We tried to be reflexive about it by clearly spelling out that

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we were examining and describing the perspective of people who wished to become measured,
evaluated, and challenged with data flows. In addition, we paid particular attention to the persuasive
powers and intervention forces inscribed in measuring devices. Certain expectations of normality, in
the form of target rates and preferred measurement results, are inscribed in many of the self-tracking
devices, including the heart-rate variability measurement device
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that we used. Therefore those who
suspected that they might be in ‘poorer than normal’ physical and mental condition – through not
exercising enough, consuming too much alcohol, or experiencing too much stress in their daily lives
– were likely to decline the invitation to participate in our research. This is a reminder that self-
monitoring can be interpreted as emotionally too confrontational, or even depressing, to adopt
(Lupton 2013a, 263). A research bias such as ours does not simply reflect ‘the digital divide’ that
hardens existing economic, political, and social divisions in the ways that people behave with, and in
relation to, technologies; it has consequences for the way in which ‘the technological’ is ontologically
positioned. In this positioning, change is privileged and exaggerated in relation to stability, further
suggesting that ‘the technological’ is continuously transforming and accelerating, while the rest of
the world is at a standstill, or oblivious to the ‘progress’ being made. Ethically this is no minor point,
because it reflects and affects developments of society as a whole (Birkholm 2013, 94).
In order not to take the selected monitoring device at face value, we did not use it in the
conventional way as it is promoted and advertised, but innovatively for our own research purposes.
The monitor generated quantitative data that facilitated investigation into the temporalities of
physiological stress and recovery: in brief, our ongoing inquiry focused on the collective rhythms of
the heart.
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In terms of the qualitative approach, the self-monitoring experiment explored the value of
personal data. Techno-anthropological research needs to pay careful attention to the ways in which
technologies guide and engage people, but also fail to engage them; incompetence and ignorance in
relation to deploying technologies productively is an important reminder of the work and care that
technologies require (Oudshoorn and Pinch 2003). A focus on failures, on technologies that no longer
find users, and on devices and applications that are used only in the short-term, highlights the
asymmetries and tensions between people and technology that can further clarify the vagaries and
uncertainties of technologically saturated everyday lives (Suchman 2007; Scheldeman 2010), thereby
enabling the documentation of technology-averse and technology-hostile behaviour. Based on our
research experiences, it is not surprising that some people resist self-tracking or, having once tried it,
are disenchanted or bored by the practice. Tracking devices offer data streams, but these do not
necessarily find any kind of meaningful space, support, or context in people’s lives. Self-monitoring
might also be fiercely resisted as a response to ‘the neoliberal agenda’ and the optimization goals

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inscribed in it. A familiar example of this kind of work is the optimization of group performance –
for instance in a sports team or work place where tracking technologies are increasingly being used
for streamlining performance and making it more transparent and legible for those in management
positions (Viseu and Suchman 2010, 170). Acknowledgment of the strong opposition to, but also the
emotional appeal of, personal analytics, allows exploration of the emotional range of involvements,
personal qualities, and competencies that self-tracking requires and promotes. This is an important
area for researching alignments of ‘the techno’ and ‘the anthro,’ because it opens windows onto a
more in-depth and nuanced analysis of how technologies operate to produce subjectivities, bodies,
and selves, meanwhile participating in the reproduction of power relations.
The intensely personal and social life of data
A further direction for techno-anthropological collaborations suggested by our empirical research lies
in the tracing of how people’s knowing of who they are and want to become is enhanced and made
possible by engagements with technological devices, applications, and infrastructures. This direction
can be empirically investigated by taking advantage of self-tracking technologies in auto-
ethnographic projects that aim to describe and unpack individual bodies, minds, and lives. We
included the latter data sources in our self-tracking experiment by encouraging our research
participants to write a detailed journal of their daily activities during the self-monitoring period,
providing a more contextual account of what quantitative personal data, based on certain algorithms,
could reveal about themselves.
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This aspect of the research design was an intentional effort to
counteract the fact that data, metrics, and algorithms are typically represented as clean and contained,
far removed from the messiness and uncertainties of bodies, minds, and daily lives (Mol 2008; Nafus
2014): we wanted to offer room for research participants to explore alternative ways of constructing
knowledge.
After the monitoring period, the participants received an illustrated report that represented their
stress and recovery measurements. Together with the physiological data, journal entries offered
detailed, first-hand observations which the participants could review, thereby assisting them to reflect
on their daily activities, behavior, and physiological reactions during the study period. For example,
at one stage one of the participants accompanied her young child to a routine operation in a hospital,
spending the day there She was surprised by how little stress she appeared to have experienced, based
on her heart-rate variability measurement, because she had recorded in her journal how anxious she
had been: periodically during the day she had had difficulties concentrating and even breathing, and

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yet, according to the measurement device, she was recovering physiologically at those exact times.
During our discussion, she wondered what to make of this contradiction.
When personal data is used in this kind of experiment, it does not have value or meaning in itself;
rather, it becomes part of the processes of sense making. When people contemplate the value that
they allocate to the curves depicting stress and physiological recovery, they might have to consider
whether they trust the factual evidence offered by the measuring device, or rather their own subjective
experience; the conclusion might be deeply personal, even idiosyncratic (Nafus and Sherman 2014;
Anderson et al. 2009). In another example, one of the research participants detected physiological
recovery in her heart-rate variability chart while she was in a meeting with a co-worker. In a later
interview she explained why this particular finding was so important for her: “We were equal in that
situation: thinking things through.” For an ambitious worker, used to managing alone, this was a
revelation that she wanted to cherish. Moments of physiological recovery during the working day
discovered from the tracking data gain a new kind of value by suggesting a particular relationship to
one’s co-workers; in this case the physiological recovery translated into equality and shared
motivation.
By indicating the ways in which people deal with personal data, auto-ethnographic engagements
can further the techno-anthropological project of seeking critical understanding of the meaning and
value of data that can represent and reframe ‘the personal,’ or ‘life,’ and, by so doing, allow a project
of evaluation and reevaluation of different types of data. Value-making is integral to the processes of
becoming a person, suggesting that rather than seeing the person as a bounded subject-entity with a
prefixed ontology, the constant movement of becoming a person is more interesting in terms of
research. In the context of personal analytics, this becoming can be defined as an inner will -- or the
taking control of processes and events -- a force that energizes people in relation to self-tracking
devices and personal data. Self-tracking becomes a meaningful practice when it offers importance,
belonging, or direction for the future. Engagements with self-tracking devices support various kinds
of notions of what is, or could be, personally valuable and worth promoting (Ruckenstein 2014).
For techno-anthropological research endeavors, the intensely personal and social life of data offers
an expanding area of investigation that ties in with how specific monitoring devices, and the data they
generate, shape assumptions of knowing, further linking to research on how data are used in the
construction of knowledge spaces (Ruppert, Law, and Savage 2013). From this perspective, the study
of personal analytics connects with the efforts of governments and commercial enterprises to gather

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large amounts of population-wide data, ‘big data,’ that can be aggregated and fed back to people in
the form of observation, guidance, and personalized services. People’s behavior and movements are
abstracted by separating them into various data flows and then reassembling them to be analyzed and
targeted for intervention (Haggerty and Ericson 2000). In knowing capitalism, personal analytics can
be seen, therefore, as an infinite source of raw material for governments and companies, but also as
a countermovement that aims to know and make visible the uses, purposes, and politics of data
(Klauser and Albrechtslund 2014). With its aim of social responsibility the latter task fits comfortably
into a techno-anthropological agenda that aims to offer guidelines for future societal trajectories and
the kinds of conceptions and practices of datafied lives that should be promoted.
The self-tracker, biohacker and activist
In participatory research, ‘talk’ – what people say and how it is transmitted – provides important
evidence of what people are interested in and see as worth promoting (Urban 2001). During free-
floating conversations in the course of the research project, the authority of the data received engaged
attention: many participants were fascinated by the possibility of seeing, knowing, proving, and doing
things with them. Despite the shortcomings and limitations of data generated by self-tracking devices,
people tend to trust, and get excited about, visualized data (Ruckenstein 2014; Cohn 2010). This is
linked to the ‘objective’ aspect of self-tracking: monitoring produces ‘hard facts,’ including numerical
evidence and statistics (Lupton 2013b, 27; Oxlund 2012). Yet numbers have qualities: measurement
tools and devices not only register facts, but rework their value (Anderson et al. 2009). While the
individualistic and instrumental nature of monitoring devices – including daily or weekly target levels
and health recommendations – can be critiqued, for techno-anthropological purposes the greatest
potential of personal analytics might still be identified in terms of collective and political aims, largely
because of the cultural power vested in numbers. Some research participants speculated, for example,
on how self-tracking devices could be harnessed to more communally-minded projects. When made
to resonate with value projects in which whole communities are engaged, self-monitoring data can be
framed as instrumental, or even emancipatory, in terms of sharpening and strengthening those
initiatives.
The idea of using personal data for various kinds of social and political aims links personal
analytics to the field of biohacking (Delfanti 2013). As with personal analytics, biohacking promotes
a wealth of practices; it mixes rebellion and openness, antiestablishment critique and techno-utopian
transformation. Essential to the mix is the active, inventive, and explorative role of the hacker.
Normative notions about health and performance optimization are sidelined by an emphasis on the

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practical and creative capacities that the involvements with personal data generate (Roberts 2012). In
this sense, personal analytics bears some resemblance to biohacking, in that the aim of the former
might be to explore, unsettle, and transform: a powerful aspect of the personal data generated by self-
tracking devices is the possibility to transcend and bypass familiar ways of approaching bodies and
lives. Some participants in our study described how they had begun to imagine ways in which they
could use the data for extending and promoting their ideas and aims. Art experts and enthusiasts, for
instance, discussed research designs that would allow them to prove statistically and visually the
health benefits provided by these activities.
From this perspective self-tracking technologies become a resource for raising new kinds of
questions and perspectives for inspection. One of the research participants was excited about the
possibility of using self-tracking devices for pedagogical purposes: real-time biofeedback could teach
people how to meditate. In particular, he wanted to experiment with tracking devices during group
meditation, because that would produce a more holistic perspective on the practice. Other participants
imagined how tracking technologies could cast light on people’s connections to one other and to the
environment; they envisioned how personal analytics could develop towards a more group-centered
focus on everyday analytics. This would mean not only sharing knowledge and findings on personal
data with friends and acquaintances, but also creating and strengthening activist undertakings and the
communities that grow up around them: an orchestra might use heart-rate variability measurement to
see if its musicians are physiologically in tune; a group of urban activists could demonstrate
physiological stress levels in different areas of the city. Depending on the context, the self-monitoring
data available for circulation can act as validation, authorization, or inspiration. Self-monitoring
offers the possibility of circulating data that impact on food safety, energy consumption, and air
pollution, for example. By using personal data streams the self-tracker can move between different
dimensions and categorizations of life; experiment with body, mind, and matter; and overcome the
preset and the normative in order to learn something new.
Insights produced through participatory and ethnographic research offer Techno-Anthropology,
if aimed at the responsible alignments of people and technology, the possibility of learning how
emerging technology can strengthen developments that people see as worth pursuing. The fact that
societal programs tend to treat digital devices, algorithms, and numbers as neutral, apolitical, and
unbiased means that people might be willing to rely on data to a much greater degree than on their
embodied experiences (Lupton 2013a, 27). On the other hand, this means that algorithms and numbers
can be harnessed to promoting social and political causes: if people trust data more than their firsthand

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experience, experience needs to be datafied in order for it to become trustworthy. Once initiated into
personal analytics, self-trackers can use data flows in order to discover and support various kinds of
practices and aims. By assisting in this project, self-tracking can offer methodological support for
techno-anthropological endeavors: numbers, data, and metrics can be used to represent research
findings, but also as a way to connect, to learn, and to develop new kinds of initiatives by making
techno-engagements more transparent and by making space for joint epistemic work. From this
perspective, the tools of personal analytics can open new routes for public engagement: self-tracking
can become a means of communicating and negotiating technoscientific interests and aims.
Studying the multi-human
In order to appreciate a form of personal analytics that does not merely aim at optimizing,
constraining, and commodifying bodies, minds, and lives, but also at opening opportunities for other
kinds of personal and collective projects, the discussion so far has identified and explored a plethora
of practices and possible projects that interconnect with personal analytics. Advanced technologies
are enabling and encouraging developments whereby people and technologies co-construct their
futures. As digital devices are written into people’s bodies and daily reactions, the line between the
organic and the non-organic is permanently blurred, and life itself becomes more contested:
technology becomes part of the reorganization of the organic and non-organic (Stiegler 1998, 85).
Capitalism is an integral part of these processes in that it paves the way for the personal analytics
market and caters to a potential customer, the self-tracker, who is curious and knowledge-seeking.
The self-tracker theorizes about life, and then models it based on data streams, whether these streams
concern financial accounting, food choices, or physical exercise. Seen this way, the personal analytics
market promotes the idea of individuals becoming organizers and creators of their own lives.
The intertwining of advanced technology and capitalism suggests that there is no reduction of
humanity in sight but, rather, that the future may witness the production of a ‘superhuman,’ an
everyday cyborg, with the purchasing power and skills to manipulate and become inspired by life and
its conditions of existence (Scheldeman 2010, 139). Technologies have historically been used for
human enhancement and optimization, but never before have they tested, and pushed, the limits of
human ability as directly as they are doing today (Birkholm 2013, 104). This line of argument
suggests that a certain kind of expansion of life is possible for those who have access to technology
and can use it in a way that enables them to fulfill this goal. Yet without appropriate resources, skills,
or aims, technologies incapacitate, disable, and even make us less human: instead of the virtuous
superhuman, we witness the reduced human. In other words, technologies shape assumptions and

14
promises of life and the future, connecting techno-anthropological research to the way in which
specific devices, algorithms, and platforms are part of processes in which the human is extended,
reduced, inspired, and overpowered. From the perspective of Techno-Anthropology this means that
it is essential to include in the research tool kit the question: What is human? This question then needs
to be empirically revisited in terms of the alignment of ‘the techno’ and ‘the anthro’ in the
phenomenon under observation, suggesting a ‘multi-human’ era, where ‘the human’ is not a stable
point of reference but, like life itself, subject to constant change and contestation. It is thus important
to strengthen the notion of Techno-Anthropology as an empirical site for exploration and
experimentation, wherein technology-saturated lives are advanced and reflected upon in a responsible
and context-specific manner.
Conclusions
The seductive and adaptive nature of capitalism and the technology market suggests that there is no
‘outside’ or ‘innocence’ in terms of Techno-Anthropology, which means that one needs a realistic, if
not cynical, assessment of the political and economic interests and aims that are being channeled
through research funding and university strategies. In the current research environment, funding
bodies are encouraging the involvement of market players in academic research by promising that
they will benefit from research findings and become more competitive in the global marketplace.
Techno-anthropological projects need to intervene here in order to ask whether this is a valid goal: in
the long run, research with no promises of immediate financial productivity might be socially and
economically more rewarding simply because it aims for a deeper understanding of long-term effects
and trajectories, rather than simply taking for granted the current state of affairs. Consequently,
reflexive and critical accounts of researchers’ involvements with technology companies, including
the developers and promoters of their wares, are of great interest for techno-anthropological research,
because they can illuminate the commercial, political, and ethical underpinnings of research
endeavors and promote down-to-earth perspectives on how technology companies – in the course of
affecting and shaping people’s daily lives and futures – interpret, design, and aim to produce those
lives (Cefkin 2010).
Our research experiences have taught us that interest-free investigation of contemporary
technological development does not exist but, concurrently, that it is imperative to study this
development anyway, because of the complex ways it intertwines future promises, corporate interests,
technological advancements, everyday practices, and emotional reactions. Techno-Anthropology
should not only offer practical support, or ‘good fits’ between ‘the anthro’ and ‘the techno,’ but ask

15
fundamental questions about human life. This brings the discussion back from the general to the
particular field of technological development which has been discussed here: personal analytics. Self-
monitoring devices and applications are only successful in their incorporation into people’s bodies,
minds, and lives if they promote emotional and practical engagements that allow and make room for
processes of knowing and becoming. By focusing on the ways in which self-tracking tools might be
departing from dominant practices and health-related goals, the mundane, non-normative, and playful
aspects of personal analytics can be brought to the fore. Self-monitoring and the data thus provided
offer access to human aspiration and practice in fields of health, art, education, employment,
environmentalism, gaming, and entertainment, among many others. The inspiration to engage in self-
tracking comes from a similarly diverse range of sources. One of the main strengths of techno-
anthropological inquiry is its multistability, a quality which facilitates exploration of the phenomenon
under study from complementary perspectives.
With its vigilant eye on emerging technologies, Techno-Anthropology is well suited to promoting
the understanding of cutting-edge technological developments and their links to broader currents of
contemporary societies. The study of personal analytics can focus on conceptualizations of the body
and the individual in digital culture; it illustrates attempts to control and optimize uncertainties in life;
it promotes the understanding of the emotional, social, and practical value of data; it raises questions
about capitalist tendencies. Techno-anthropological research ventures into a complex terrain wherein
a range of agendas dictates various approaches to different aspects of the ‘techno’ and ‘the anthro.’
Rather than promising unambiguous and direct answers, Techno-Anthropology offers empirical and
methodological support for mapping fields that are complex, uncertain, and constantly on the move,
while its approaches provide a site for epistemic work aimed at developing concepts, modes of
interaction, and directions for future research into the impact of technology on the human lifeworld.
Acknowledgements
We thank Vincent Ialenti for excellent comments on an earlier draft of this article, and Veera
Mustonen for contributing to the self-tracking study. The research and writing of this article were
supported by the SalWe Research Program for Mind and Body and the Digital Health Revolution
program, funded by Tekes, the Finnish Funding Agency for Innovation.

16
References
Anderson, Ken, Dawn Nafus, Tye Rattenbury, and Ryan Aipperspach. 2009. "Numbers Have
Qualities Too: Experiences with Ethno‐Mining." Ethnographic Praxis in Industry Conference
Proceedings (1): 123-40.
Arvidsson, Adam. 2005. "Brands: A Critical Perspective." Journal of Consumer Culture 5 (2): 235-
58.
Arvidsson, Adam. 2009. "The Ethical Economy: Towards a Post-Capitalist Theory of Value."
Capital & Class 33 (1): 13-29.
Birkholm, Klavs. 2013. "Human Enhancement as Techno-Anthropology Par Excellance." In What is
Techno-Anthropology?, ed. Tom Børsen and Lars Botin, 91-116. Aalborg: Aalborg University
Press.
Børsen, Tom, and Lars Botin. 2013a. "Hybridity and Social Responsibility. In Techno-Anthropology
and Engineering Education." In Proceedings from the 41th SEFI Conference, 16-20 September
2013, Leuven, Belgium, ed. Lucio Froyen. Leuven: SEFI: European Association for Engineering
Education.
Børsen, Tom, and Lars Botin, eds. 2013b. What is Techno-Anthropology? Aalborg: Aalborg
University Press.
Boyd, Danah, and Kate Crawford. 2012. "Critical Questions for Big Data: Provocations for a Cultural,
Technological, and Scholarly Phenomenon." Information, Communication & Society 15 (5):
662-79.
Cefkin, Melissa, ed. 2010. Ethnography and the Corporate Encounter: Reflections on Research in
and of Corporations. Studies in Public and Applied Anthropology. Vol. 5. New York: Berghahn
Books.
Cohn, Simon. 2010. "Picturing the Brain Inside, Revealing the Illness Outside: A Comparison of the
Different Meanings Attributed to Brain Scans by Scientists and Patients." In Technologized
Images, Technologized Bodies, ed. Jeanette Edwards, Penny Harvey, and Peter Wade, 65-84.
New York: Berghahn Books.
Delfanti, Alessandro. 2013. Biohackers: The Politics of Open Science. London: Pluto Press.
Edwards, Jeanette, Penelope Harvey, and Peter Wade. 2010. "Technologized Images, Technologized
Bodies." In Technologized Images, Technologized Bodies, ed. Jeanette Edwards, Penelope
Harvey, and Peter Wade, 1-35. New York: Berghahn Books.
Elgaard Jensen, Torben. 2013. "Techno Anthropology - a New Move in Science and Technology
Studies." STS Encounters 5. http://www.dasts.dk/wp-content/uploads/2013/03/Torben-Elgaard-
Jensen-2013-Techno-Anthropology.pdf
Feenberg, Andrew. 1991. Critical Theory of Technology. New York: Oxford University Press.
Foucault, Michel. 1988. "Technologies of the Self." In A Seminar with Michel Foucault, ed. Luther
H. Martin, Huck Gutman, and Patrick H. Hutton, 16-49. Massaschusetts: University of
Massachusetts Press.
Goetz, Thomas. 2011. "The Feedback Loop: How Technology Has Turned an Age-Old Concept into
an Exciting New Strategy for Changing Human Behavior", Wired July, 126-133, 162.
Haggerty, Kevin D., and Richard V. Ericson. 2000. "The Surveillant Assemblage", British Journal
of Sociology 51 (4): 605-622.
Ingold, Tim. 2000. The Perception of the Environment: Essays on Livelihood, Dwelling and Skill.
London: Routledge.
Irwin, Stacey. 2005. "Technological Other/Quasi Other: Reflection on Lived Experience."Human
Studies 28 (4): 453-67.

17
Klauser, Francisco R., and Anders Albrechtslund. 2014. "From Self-tracking to Smart Urban
Infrastructures: Towards an Interdisciplinary Research Agenda on Big Data." Surveillance &
Society 12 (2): 273-86.
Lupton, Deborah. 2013a. "The Digitally Engaged Patient: Self-Monitoring and Self-Care in the
Digital Health Era." Social Theory and Health 11 (3): 256-70.
Lupton, Deborah. 2013b. "Understanding the Human Machine [Commentary]." IEEE Technology
and Society Magazine 32 (4): 25-30.
Lupton, Deborah. 2014a. "Quantified Sex: A Critical Analysis of Sexual and Reproductive Self-
Tracking apps." Culture, Health and Sexuality 17 (4): 440-53.
Lupton, Deborah. 2014b. "Self-tracking Modes: Reflexive Self-Monitoring and Data Practices."
Available at http://dx.doi.org/10.2139/ssrn.2483549
Miller, Peter, and Nikolas Rose. 1990. "Governing Economic Life." Economy and Society 19 (1): 1-
31.
Mol, Annemarie. 2008. The Logic of Care: Health and the Problem of Patient Choice. London:
Routledge.
Nafus, Dawn. 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, Dawn, and Jamie 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).
Available at http://ijoc.org/index.php/ijoc/article/view/2170
Oxlund, Bjarne. 2012. "Living by Numbers: The Dynamic Interplay of Asymptomatic Conditions
and Low Cost Measurement Technologies in the Cases of Two Women in the Danish Provinces.”
Suomen Antropologi: Journal of the Finnish Anthropological Society 37 (3): 42-56.
Oudshoorn, Nelly, and Trevor Pinch, eds. 2003. How Users Matter: the Co-Construction of Users
and Technology. Cambridge, Mass: The MIT Press.
Pantzar, Mika, and Minna Ruckenstein. 2015. "The Heart of Everyday Analytics: Emotional, Material
and Practical Extensions in Self-Tracking Market." Consumption, Markets and Culture 18 (1):
92-109.
Rabinow, Paul. 2009. Anthropos Today: Reflections on Modern Equipment. Princeton: Princeton
University Press.
Roberts, Seth. 2012. "The Reception of My Self-Experimentation." Journal of Business Research 65
(7): 1060-66.
Ruckenstein, Minna. 2014. "Visualized and Interacted life: Personal Analytics and Engagements with
Data Doubles." Societies 4 (1): 68-84.
Ruppert, Evelyn, John Law, and Mike Savage. 2013. "Reassembling Social Science Methods: The
Challenge of Digital Devices." Theory, Culture & Society 30 (4): 22-46.
Scheldeman, Griet. 2010. "Technokids? Insulin Pumps Incorporated in Young People’s Bodies and
Lives." In Technologized Images, Technologized Bodies, ed. Jeanette Edwards, Penelope
Harvey, and Peter Wade, 137-60. New York: Berghahn Books.
Strathern, Marilyn. 1992. After Nature: English Kinship in the Late Twentieth Century. Cambridge:
Cambrigde University Press.
Suchman, Lucille Alice. 2007. Human-Machine Reconfigurations: Plans and Situated Actions.
Cambridge: Cambridge University Press.
Swan, Melanie. 2009. "Emerging Patient-Driven Health Care Models: An Examination of Health
Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking."
International Journal of Environmental Research and Public Health 2: 492-525.
Swan, Melanie. 2012a. "Health 2050: The Realization of Personalized Medicine through
Crowdsourcing, the Quantified Self, and the Participatory Biocitizen." Journal of Personalized
Medicine 2 (3): 93-118.

18
Swan, Melanie. 2012b. "Sensor Mania! The Internet of Things, Wearable Computing, Objective
Metrics, and the Quantified Self 2.0." Journal of Sensor & Actuator Networks 1 (3): 217-53.
Stiegler, Bernard. 1998. Technics and Time: The Fault of Epimetheus (Vol. 1). Stanford: Stanford
University Press.
Thrift, Nigel. 2005. Knowing Capitalism. London: Sage.
Thrift, Nigel. 2006. "Re-Inventing Invention: New Tendencies in Capitalist Commodification."
Economy and Society 35 (2): 279-306.
Turner, Fred. 2006. From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network,
and the Rise of Digital Utopianism. Chicago: University of Chicago Press.
Urban, Greg. 2001. Metaculture: How Culture Moves Through the World. Minneapolis: University
of Minnesota Press.
Viseu, Ana, and Lucy Suchman. 2010. "Wearable Augmentations: Imaginaries of the Informed
Body." In Technologized Images, Technologized Bodies, ed. Jeanette Edwards, Penelope
Harvey, and Peter Wade, 161-84. New York: Berghahn Books.
Wellner, Galit. 2014. "The Quasi-Face of the Cell Phone: Rethinking Alterity and Screens." Human
Studies 37: 299-316.
1
The ‘we’ refers to a multidisciplinary research group at the National Consumer Research Centre, Helsinki (a
collaborative effort by Veera Mustonen, Mika Pantzar and Minna Ruckenstein).
2
One of the main protagonists of personal analytics has been Wired, a magazine published since 1993 which reports on
how technology shapes cultural, economic and political understandings and future outlooks (Turner 2006). We are
currently finalizing a manuscript that focuses on how the discourse in Wired models and theorizes the self and, in doing
so, makes space for, and expands, the Quantified Self the market for self-tracking devices and applications.
3
In spring 2012 we collected an extensive body of material composed of both quantitative and qualitative self-tracking
data.
4
See also “The Conclusions,” issued by the European Council on 24/25 October 2013, which state that “Europe must
boost digital, data-driven innovation across all sectors of the economy” and that strategic technologies such as “big
data” are important enablers for productivity.
http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/139197.pdf.
Accessed March 24, 2014.
5
The participatory research design and what it taught us about personal analytics is discussed elsewhere (Ruckenstein
2014).
6
For more information on the heart-rate variability device, see http://www.firstbeat.com/
7
Quantitative analysis of physiological temporalities will be reported as soon as we have contextualized our findings.
8
We did not suggest that the participants of our research needed to expose private and intimate thoughts and behaviors
for inspection; they could freely decide whether they wanted to share their diaries with us (see Ruckenstein 2014).