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Self-tracking is becoming a prominent and ubiquitous feature in contemporary practices of health and wellness management. Over the last few years, we have witnessed a rapid development in digital tracking devices, apps and platforms, together with the emergence of health movements such as the Quantified Self. As the world is becoming increasingly ruled by metrics and data, we are becoming ever more reliant on technologies of tracking and measurement to manage and evaluate various spheres of our lives including work, leisure, performance, and health. This chapter begins with a brief outline of some of the key theoretical approaches that have been informing the scholarly debates on the rise of self-tracking. The chapter then moves on to discuss at length the findings of an international survey study conducted by the author with users of self-tracking technologies to discuss the ways in which they perceive and experience these practices, and the various rationales behind their adoption of self-tracking in the first place. The chapter also addresses participants’ attitudes towards issues of privacy and data sharing and protection which seem to be dominated by a lack of concern regarding the use and sharing of self-tracking data with third parties. Some of the overarching sentiments vis-à-vis these issues can be roughly categorised according to feelings of ‘trust’ towards companies and how they handle data, a sense of ‘resignation’ in the face of what is perceived as an all-encompassing and ubiquitous data use, feelings of ‘self-insignificance’ which translates into the belief that one’s data is of no value to others, and the familiar expression of ‘the innocent have nothing to hide’. Overall, this chapter highlights the benefits and risks of self-tracking practices as experienced and articulated by the participants, while providing a critical reflection on the rise of personal metrics and the culture of measurement and quantification.

Metrics, data, algorithms and numbers play an unmistakably powerful role in today’s society. Over the years, their use and function have expanded to cover almost every sphere of everyday life so much so that it can be argued that we are now living in a ‘metric culture’, a term indicating at once the growing cultural interest in numbers and a culture that is increasingly shaped by numbers, as Beer (2016) also argues. At the same time, metric culture is not only about numbers and numbers alone, but also links to issues of power and control, to questions of value and agency and to expressions of self and identity. Self-tracking practices are indeed a manifestation of this metric culture and a testimony to how measurement, quantification, documentation and datafication have all become important tropes for managing life and the living in contemporary society. In this introductory chapter, I provide a general contextualisation of the topic of this edited collection along with an overview of the different chapters and their key arguments.

This chapter provides a historical contextualisation of health tracking and public health communication from the post-World War Two development of the welfare state, through the birth of neoliberalism, until today’s individualising practices of digital health tracking and quantification of bodies. Through an examination of these three phases of public health quantification of bodies, encompassing the socio-economic, cultural and political shifts since 1948, combined with the development and wide adoption of digital health and self-quantifying technologies, this chapter traces the changing landscape and the dramatic implications this has had for shifting who is responsible for maintaining ‘good’ health. This chapter illustrates how neoliberal free market principles have reigned over UK public health discourse for many decades, seeing health as no longer binary to illness, but as a practice of individual self-quantification and self-care. In turn, the chapter explores how the quantification and health tracking of bodies has become a dominant discourse in public health promotion, as well as individual citizenship and patient practices. This discourse still exists pervasively as we move into the digital society of the 2020s, through the Covid-19 pandemic and beyond; with public health strategies internationally promoting the use of digital health tools in our everyday, further positioning citizens as entrepreneurial subjects, adopting extensive technological measures in an attempt to measure and ‘optimise’ health, normalising the everyday quantification of bodies.

Drawing on ethnographic observations of diabetes (self-)management in French-speaking Switzerland and semi-structured interviews with healthcare practitioners, people living with diabetes and their relatives, the chapter aims at shedding light on self-tracking practices of people living with diabetes. It explores the ways people with diabetes measure and learn to recognise body symptoms of hypo- and hyperglycaemia through self-quantification, and act consequently. In particular, the chapter investigates recent medical devices – continuous and flash glucose monitoring systems – that reconfigure the work of health providers and self-care practices. It shows the self-monitoring practices and the resulting self-awareness people living with diabetes develop in interaction with technology and caregivers in order to undertake embodied actions. By pointing out that new technologies have facilitated the access to personal body information and the sharing of it, self-monitoring is also questioned as a form of surveillance, opening up issues of power and control over patients’ behaviours. With regard to this, the chapter illustrates that, occasionally, people with diabetes resist ‘docility’ through micro-powers at the level of everyday life by refusing to engage in their use and by developing personal strategies or ‘tactics’.

The debate concerning the Quantified-Self Movement (QS) has been extremely polarised. As Tamar Sharon has pointed out, each aspect of the lifestyle promoted by Gary Wolf and Kevin Kelly has provoked opposite reactions, generating a debate that revolves around some basic conceptual dichotomies: empowerment versus surveillance, self-awareness versus reductionism, and personalised healthcare versus disintegration of public assistance (Sharon, 2017). The aim of this chapter is to provide a critique of QS, namely an assessment of its limits and its (technological and social) conditions of possibility. In particular, the author’s analysis will focus on the relationship between technology and subjectivity, and its main theoretical framework will be Michel Foucault’s research on the notion of ‘care for the self’ (Foucault, 1986, 2005). Quantification is an essential and unescapable aspect of our present technological environment. The devices that make our onlife (Floridi, 2014) possible are connected with a complex technological system made of GPSs, satellites, computers, and networks. Health is no longer managed through a distinct set of practices within the limits of a well-defined space (the hospital or the ambulatory), but it rather becomes a dataset integrated into a system where all aspects of life (health, law, leisure, work, social relations) are treated and managed simultaneously. This technological condition implies a new form of cognitive and practical delegation (Ippolita, 2016; Morozov, 2013), which makes the very notion of ‘self-tracking’ at least problematic. Individuals do not track themselves anymore: on the contrary, they are tracked by prosthetic extensions of their own bodies. This, however, does not mean that they do nothing. Our digital devices require a specific set of practices, a determinate way of life. The author will argue that these practices are the product of design, understood as a specific way of conceiving and organising the interaction between subject and technical object (Flusser, 1999). Through our technological environment, design reshapes the social and political function of bodies, their interaction and the set of practices connected to them (Bratton, 2015; Dyer, 2016; Vial, 2014). Automated quantification is an aspect of our designed user experience. As such, this chapter discusses design as a key element to understand the role of quantification in our digital milieu. It analyses the QS movement as a specific way of responding to our new technological condition. The main research question will be the following: is QS to be regarded as a simple acceptance of a new form of delegated – and thus alienated – subjectivity, or is it a kind of practice that allows the subject to overcome his passivity, and to take part in the process through which quantification is designed and managed? Is it possible to understand QS as a technology of the self (Foucault, 1988, 2005)?

Most scholarly and governmental discussions about artificial intelligence (AI) today focus on a country’s technological competitiveness and try to identify how this supposedly new technological capability will improve productivity. Some discussions look at AI ethics. But AI is more than a technological advancement. It is a social question and requires philosophical inquiry. The producers of AI who are software engineers and designers, and software users who are human resource professionals and managers, unconsciously as well as consciously project direct forms of intelligence onto machines themselves, without considering in any depth the practical implications of this when weighed against human actual or perceived intelligences. Neither do they think about the relations of production that are required for the development and production of AI and its capabilities, where data-producing human workers are expected not only to accept the intelligences of machines, now called ‘smart machines’, but also to endure particularly difficult working conditions for bodies and minds in the process of creating and expanding the datasets that are required for the development of AI itself. This chapter asks, who is the smart worker today and how does she contribute to AI through her quantified, but embodied labour?

Investments in the technologies of borders and their securitisation continue to be a focal point for many governments across the globe. This paper is concerned with a particular example of such technologies, namely, “Big Data” analytics. In the past two years, the technology of Big Data has gained a remarkable popularity within a variety of sectors, ranging from business and government to scientific and research fields. While Big Data techniques are often extolled as the next frontier for innovation and productivity, they are also raising many ethical and political issues. The aim of this paper is to consider some of these issues and provide a critical reflection on the implications of using Big Data for the governance of borders.

The author draws on the example of the new Big Data solution recently developed by IBM for the Australian Customs and Border Protection Service. The system, which relies on data collected from Passenger Name Records, aims to facilitate and automate mechanisms of profiling enable the identification of “high-risk” travellers. It is argued that the use of such Big Data techniques risks augmenting the function and intensity of borders.

The main concerns addressed here revolve around three key elements, namely, the problem of categorisation, the projective and predictive nature of Big Data techniques and their approach to the future and the implications of Big Data on understandings and practices of identity.

By exploring these issues, the paper aims to contribute to the debates on the impact of information and communications technology-based surveillance in border management.