Introduction

The impact of digital technologies on labour has become in the past decade a focus of science and technologies studies (STS). The potential effects that a group of integrated technologies – connectivity, Big Data, the increase in computing capacity, forms of machine learning – could have on the quantity of employment and on the quality of working practices in most sectors generate widespread fears and, at times, hopes for profound social change. The rationale used to estimate these effects, in the first stage of research, was primarily based on utilitarian techno-economic categories, that is, oriented to assess (a) the technical feasibility of automation and (b) the cost and, therefore, any competitive advantage that could derive from implementation. Less attention was paid to other important non-techno-economic factors – sociotechnical, cognitive-behavioural, historical and cultural – that constitute the core of the interdisciplinary approach of STS.

In this context, the application of digital technologies and artificial intelligence to medical imaging constitutes an ideal case for this dominant cognitive approach. In a sector that has long been deeply invested in the use of digital technologies, first in preclinical research and then in the therapeutic field, medical imaging has been considered an activity inevitably destined to be improved by new technologies, in terms of the quantity and quality of diagnostic activities, while clinicians and technicians were seen as predestined to be sacrificed on the altar of progress.

Is this accurate? The first experiences of Computer Aided Diagnosis systems from the 1990s onwards showed that the unfolding of these implications is much more complex and multifaceted than the reductionism of rational economic models can represent. The first experiences based on the use of machine-learning systems in work processes that seem ideal for their application have led to interesting but limited results and, above all, these have not become fully institutionalized in healthcare systems.

This chapter intends to exemplify some non-techno-economic factors that could be at the basis of these contradictory results, in order to articulate analytical tools that can be used to study the effects of new technologies on work in healthcare and in other sectors.

Introduction

I begin this chapter with a brief overview of the state of play vis-a-vis immunity-boosting supplements and COVID-19, followed by an overview and analysis of my generative methodological framework. Note that I ground this study in an understanding of health that is based on my previous work and which I define as ‘a co-produced state of idealized expectations, performances, embodiments and patterns of consumption dominated by gendered and raced technophilic knowledge regimes that reproduce regimented and coercive Western standards of health and well-being’ or CICT (Sikka, 2022, 2023). Following a precis of this definition, I apply my ‘auto-ethnographic and rhizomatic socio-material feminist approach to science and technology’ method in four phases, via: (1) a case study-driven overview of Purearth, a UK-based wellness company; (2) a deeper discussion of method; (3) the application of new materialism to the company and its products through the use of an ‘agential cut’; and (4) an auto-ethnographic exegesis through which I chronicle and reflect on my consumption of Purearth’s ‘Immunity Drinks Pack’ over approximately ten days.

Case study: Purearth

Purearth is a London-based wellness company (incorporated in 2012) that sells vegan and organic ‘water kefirs, cleanses, juices, shots and broths’, in recyclable bottles, and whose ‘ostensible mission’ is to ‘help people live healthier lives by using what nature provides us in its most pure and organic form’ (Purearth, 2021). The company is funded primarily through Nexus Investment Ventures, a corporate, venture-capitalist seed fund whose latest funding round raised $447,000 for the company (Crunchbase, 2021; PitchBook, 2021). Its owners are two early to middle age White women, Tenna Anette and Angelina, who have been working in the health and wellness industry as practitioners for a number of years. The company has been written up, and its products reviewed, in such outlets as Country & Town House (Cox, 2020), which called its cleanse ‘one of the most enjoyable restrictive or preset diet plans out there’ Retail Times (Briggs, 2020), Wow Beauty, which invites readers to consume Purearth products and, in doing so, ‘drink their way to gut health’ (Wow Beauty, 2018) and The Telegraph (Howell, 2019), which, in a review, gave its kefir drink a 10/ 10.

Introduction

Citizenship is formally and historically connected to the nation state, even though this has not always been the case (cf Athens’ city-centred democracy). In today's understanding of democracy, however, scientific knowledge and technical expertise intersect with citizens’ ability to hold state power accountable to democratic values. Sheila Jasanoff (2017) describes how the nation state concentrates not only political power but also resources that enable investments in ‘big science’ projects. Based on these concentrations, she asks: if the demos should have a role in the technical framing and resolving of public problems, what analytical resources does STS provide to facilitate such participation? The answer to this question, as suggested by Jasanoff, is that ideas and practices around science and technology – priorities, investments, distribution channels, regulations, and so on – are co-produced with ideas about concerned citizens. Thus, STS scholars should call attention to the fact that practices of collective knowledge-making shape our very understanding of the demos to be served by democracy.

As we saw in the previous chapter, studies undertaken by STS scholars have focused on the relationships between modes of governing and how issues are made public and open to wider debate, how groups of the public are demarcated through the notion of invited and uninvited publics, and how the agency ascribed to invited publics tends to be circumscribed by instrumental motives. In this work, STS scholars frequently touch on one of the unresolved problems in democratic theory. This is about what properly constitutes the people. Yet, any democratic theory is based on an understanding that there is a people, a citizenry that is implicated in governing in indirect or direct ways and can hold government accountable. We discussed such unexplored assumptions in the first chapter of this book, and we referred to these as belonging to a shadow theory of democracy. The shadow is an inevitable companion to unacknowledged contradictions and taken-forgranted assumption within established ideas about democracy. If denied, it is a potential threat, but when openly acknowledged and dealt with, it is a potential resource to democracy.

STS scholars have suggested that citizen engagement with and contestation over science and technology should be understood as having a constitutive role in the development of alternative imaginaries of democracy. Such ideas point to the relations between governing bodies and concerned publics that are transgressing the boundaries of the nation state.

Introduction

Science, in its very basic sense, means knowledge, from the Latin scientia; and democracy, in its very basic sense, means rule of the people, from the Greek demos (people) and kratos (rule). Throughout history, science and democracy have each developed with a keen ability to alter their shape in various contexts. Nevertheless, science has come to denote specific ways of producing knowledge as opposed to others, and democracy has come to be associated with particular modes of governance as opposed to others. The reason why it is impossible not to use the plural in relation to the practice of these two concepts – ways of producing knowledge and modes of governance – is simply that there are multiple versions and ways of doing both science and democracy. Yet science and democracy have taken shape as the grandeurs of modern societies. This suggests that there is something fixed about them: science has become established as the best way of producing knowledge, and democracy has become established as the best mode of governance.

Of course, their grandeur refers to the general ideas and principles that are associated with both science and democracy. Even though these ideas and principles have generated deep thought, lengthy discussion, and many thick books, dominating versions of both science and democracy can be summed up in one word: representation. Scientists represent nature, and elected politicians represent the people. To gain legitimate authority, however, representations and representatives must resonate with the represented. It is this resonance and the relational aspect involved in both science and democracy that distinguish them as particular ways of producing knowledge and particular modes of governance. The principle behind both science and democracy is that authority is not gained through violence and power exercises that ignore objections to the representations if they fail to be ‘fair’, ‘just’, ‘correct’, ‘reasonable’, ‘relevant’, and so on. It is this principle – that the represented can object to representations and that their objections (if assessed as legitimate) will induce relevant changes – that replaces gods (or emperors) and nature as unquestionable authorities, and it is therefore science can provide us with the best knowledge and democracy with the best mode of governance.

Representation, as a term and as an idea, is filled with all sorts of associations and predefined meanings.

This book does two things: it introduces the field of science and technology studies (STS) and discusses science and democracy through an STS approach. This double aim of the book means the book is an introduction to STS with a specific focus.

STS is a lively international and interdisciplinary research field. Despite the heterogeneity of STS as a research field, scholars within STS share some common theoretical grounds. What holds STS together is an understanding of knowledge, especially scientific knowledge, as practice in which actors’ interpretations, judgments, and actions lead to results that can be perceived as robust and true knowledge. The authority of knowledge, or truth, is not something that exists from the beginning, but is the result of processes in which many actors participate. It is these processes of emergence that are of interest to all STS researchers.

The research field has several roots, both academic and more social and political. Academically, the scientific theoretical discussion in the wake of Thomas Kuhn's book The Structure of Scientific Revolutions (published in 1962, with an important second edition in 1970) has been central. Questions about paradigms, paradigm conflicts and paradigm changes have had great significance outside the world of research as well. These debates led to a return to the classical sociology of knowledge, which was an important part of the emergence of sociology at the turn of the last century and whose tools could now be used with new energy to understand not only religious beliefs, political ideologies and everyday knowledge (folk beliefs) but also scientific knowledge. Scientific knowledge is not dramatically different from other forms of knowledge, and it can be sociologically understood in the same way: as anchored in a particular context, shaped by time and place, and by different interests and actor strategies. But despite these similarities, scientific knowledge can also be very different from other forms of knowledge.

In this book, we take as our starting point the principle that legitimizes science in modern society and makes it different from other knowledge forms, and this principle is also what science and democracy have in common. The principle shared by science and democracy is that their authority is not gained through violence. Rather their authority is based on the principle that they can always be questioned and revised.

Introduction

Throughout this book, we have discussed a range of challenges and possibilities that arise in relation to science and expertise. These include the boundaries between science and democracy, or more generally between science and politics, and how concerned groups or the general public can be involved in technoscientific issues. It is almost impossible to find areas in life that has not been influenced by technoscientific developments. When the results of science inflict on people's lives and when political decisions and public discussions are framed by scientific expertise, fundamental and classical issues concerning democracy emerge: Who is concerned? Who governs? Who benefits? What negative impacts and uncertainties are to be found? Our focus on scientific knowledge and expertise could be assessed as a limitation in our approach to democracy, however we argue that science and technology developments inevitably shape social order and therefore also impinge on how we can imagine and practice democracy. In this final chapter, we present our view on how STS can contribute to an improved understanding of the interplay between science and democracy.

In the introduction to this book, we referred to the shadow theory of democracy, which points to the hidden assumptions and unexplored premises of democratic theory. These hidden premises can also be thought of as vulnerabilities of todays’ liberal democracies concerning questions such as: Who is the public? Who governs? How can we guarantee that democracy leads to equal outcomes? (Gustavsson 2018). These are termed ‘vulnerabilities’ because they are often assumed to be connected to clear answers. But they seldom are, and they can, therefore, lead to mistrust in the democratic system altogether. They can also pave the way for charismatic leaders that give clear answers to these questions, even though these types of answer do not really exist. The public is not easily demarcated, since those who are concerned by decisions cannot always be identified in the population within a nation state. Moreover, those who govern are far from limited to publicly elected politicians, but include a range of individual and organizational decision makers, and they may have to deal with lock-ins that are difficult to change and hence claim control over.

Introduction

Both science and democracy are based on representation. We have suggested that this means a dividing line is created between those who represent and those who are represented. Concerning science, and expert knowledge more generally, fears are sometimes raised in relation to expert rule. However, this is often an unproblematic, and even a desirable, situation. The desire to hand over certain tasks to experts is especially strong when non-experts have no interest in knowing the details, or would not even be able to learn them, but still need to get things done. This applies to everything from healthcare to plumbing, architecture, and energy production. But sometimes engagement and resistance can be mobilized among citizens because the representation – the delegation to experts – is unsatisfactory. Experts can be wrong and can claim authority on issues that go far beyond their expertise and yet have great influence over the course of events. Citizens can sometimes contribute to better representation since they have other, often more local, experiences than the experts. But above all, citizens, relevant groups, and the general public have an important role to play in judging expertise as credible and relevant, or not.

Participation and its role for democracy is much more complex than a simple dividing line between unquestioned delegation to experts and direct participation of laypeople. It involves parliamentary debate and decision-making, practices of public policy making and administration, issue formation and mobilization in social movements, practices of investigative journalism and media reporting, and so on. This also means that there are potentially many democratic sites at which science and technology issues are communicated, decided on, and practiced (Laurent 2017). It means too that for each issue, we might be able to trace particular ecologies of participation – for instance, particular forms of communication and dialogue, assemblies of concerned groups, types of facilitator for participatory events, and institutionalized ways of managing issues in inclusive or exclusive ways (Chilvers and Kearnes 2016).

This chapter returns to the idea described in Chapter 4 of participation as crucial for good governance, exploring this in more depth and in relation to the idea of co-production. In short, participation is understood as being about co-production of issues and actors. In the next section, we discuss why STS is particularly concerned with the question of participation.

Introduction

As an interlude, this chapter is an effort to connect, bridge, and provide an overlap between the other two parts of this book: Separation and Coproduction. In this work, we complicate the picture of a clear division between science and politics. Our focus is on science and politics as two separate activities with their own institutions and practices, but we also turn to the question of how the interplay between science and politics is understood in terms of overlaps and connections.

Better communication, increased proximity, or more interaction while maintaining an arm’s-length distance – there are many expressions of how science and politics connect and should be connected; and from the science side, they can be summarized as an ambition to make science relevant to policy, to make it close to politics but not too close (Gieryn 1995: 435, referring to Jasanoff 1990). In other words, policy-relevant research involves a balancing act between separation and integration (Sundqvist et al 2015, 2018). According to this view, research must be sufficiently separate to maintain its autonomy, but integrated enough to be socially relevant. This ambition entails a critique of an overly strong division, but also points out the risks that one side will take command of the other. From this perspective, a scientization of politics and a politicization of science are both highly undesirable and considered as risks. There is thus a need for a proper distance between science and politics.

To be fair, we must say that several of the approaches and perspectives presented in Chapter 3 devote a great deal of effort to understanding the interplay between science and politics. Collins and Evans’ third wave suggests such a ‘balanced’ solution. This also applies to Habermas’ pragmatism as well as to Nelkin's aim of understanding scientific experts as part of a political context and, from there, sorting out the conditions for expert work.

However, the aim of chapters 2 and 3 was to account for a division between science and politics and the approaches that focus on this, including suggestions from some scholars that one side should dominate the other. Here, Plato's allegory of the cave is archetypal, as it is based on a strong division but also on a desired dominance of knowledge over politics. This allegory is echoed in delegative democracy, the linear model of knowledge, and the deficit model.

Introduction

This chapter goes deeper into the complex relation between science and democracy. Previous chapters discussed how science and politics are separate and that one elite (scientific experts) is delegated the power to represent nature (as knowledge objects) and another elite (decision makers, not only elected politicians but broadly speaking) is delegated the power to represent the people. This double delegation (delegative democracy) is based on a distinction between what is represented and who can represent. These two forms of representation divide the world into the two domains of knowledge and politics and, in addition, create a sharp division between those who are in power (the two elites) and those who are not (the ignorant mass). However, these separate domains are also interlinked, and as we have seen earlier, the boundaries between them and their authority and legitimacy can always be questioned and change over time. The separation between science and democracy, between representatives and represented, is a joint product. One of the most important ideas within STS research is that knowledge and social order are intertwined or, as it is often expressed, co-produced (Jasanoff 2004b).

Science and democracy are not independent from each other. Democracies legitimize and back up decisions and reforms with expert knowledge, and an uneven distribution of knowledge and education in a society is seen as a democracy problem (Sismondo 2010: 80). Governing requires knowledge, and science is intermingled with power. Science and democracy may be the result of a joint process, but they are often presented as separate, which has consequences for how practices are performed and leads to what they have in common being concealed. Knowledge is understood and presented as being independent of social order and power, especially in the scientific community. Researchers have a professional interest in keeping sharp distinctions between scientific knowledge and other types of knowledge as well as sharp distinctions between scientific knowledge and political interests (Gieryn 1983). At the same time, researchers also have an interest in getting attention from outsiders and they want their results to be used outside of the research community. This duality, which we have discussed previously, implies the wish of researchers to have, simultaneously, distance and closeness to politics.

Introduction

Science and democracy have emerged as important institutions in modern Western societies. But what do we mean when we say that a society is ‘modern’? Among other things, modernity means that the world is understood in the light of scientific knowledge instead of traditional knowledge and religious beliefs. Scientific knowledge takes precedence over other forms of knowledge and becomes the yardstick from which other knowledge claims are judged. This situation becomes an important part of the characterization of modernity (Beck 1992: Chapter 7).

That science is superior to other forms of knowledge in modern society is only valid on a rather basic level. However, we are expected to accept that the earth was not created in seven days, that all living things consist of one or more cells, and that the dropped coffee cup falls to the ground due to gravity. The limit, or the boundary, of what issues can legitimately be answered from a scientific point of view can never be strictly formulated. Does climate change have human causes? Has extreme weather become more common due to a higher global average temperature? Is a global climate tax the best measure for reducing greenhouse gas emissions? Do we all need to change our individual lifestyles due to climate change? Where in the climate discussion does science end and politics start, and is climate change mitigation a scientific issue at all?

These questions illustrate that it is not obvious what questions science can answer and when science should have priority over other kinds of knowledge. The boundaries between science, values, and political assessments are not sharp in these kinds of issue complex (Hulme 2009). Many issues in relation to topics like climate change are both understood and managed by a mix of scientific knowledge and political assessment. Climate change would not be an issue at all if there was not an underlying value-based assessment that it is of interest to protect planet earth for future generations of human beings.

Modernity and its strong focus on scientific knowledge can be understood from the notion of separation. The anthropologist and STS scholar Bruno Latour (1993) characterizes modernity as a separation of nature (non-humans) from society (humans). This division is fundamental to modern societies and has led to a sharp division between science and politics. In the modern, enlightened society, both science and democracy are highly valued.

Introduction

In this chapter, we continue the presentation of ideas about science and politics as separate. While the previous chapter focused on separation as part of wider societal changes and presented thinkers who demonstrate a clear separation, some of which also support the idea of strictly separate domains, this chapter focuses on approaches that discuss how science and politics can and should relate to each other, while simultaneously acknowledging that separation exists. Many of the scholars discussed in the chapter study what happens when science and politics meet.

We first present the view that the increased importance of scientific knowledge for political decision-making has led to stronger demands for scientific consensus. For scientific experts to effectively impact on and influence political decisions, their knowledge base must be generally accepted among other scientists. We then describe the linear model, which is based on the idea that knowledge precedes action. The deficit model follows from the linear model and implies that the public is characterized by knowledge deficits, which can be remedied with education and reliable information. We then present Jürgen Habermas’ seminal pragmatic model as a way to manage the gap between science and politics, and also the technocratic tendencies in modern society based on the increasing dominance of expert knowledge.

In the two final sections of this chapter, we introduce classical STS research on what happens when scientific experts become involved in political decision-making processes. Dorothy Nelkin's studies serve as an important example. Nelkin's conclusion is that politics frames the work of experts and how expert knowledge is used, and thereby expertise is reduced to a tool in managing political conflicts. Thereafter, we present Harry Collins and Robert Evans’ characterization of the first, second, and third wave of STS research. In their approach, presented as the third wave, a clear separation between science and politics, and between experts and non-experts, is defended from the explicit aim of avoiding both technocracy (relying too much on knowledge) and populism (relying too little on knowledge).

Scientific consensus and autonomous experts

Peter Haas, a political scientist well known for the notion of epistemic communities, has for a long time studied international environmental governance and under what circumstances expert knowledge can gain political significance.

John Gould’s father was a gardener. A very, very good one – good enough to be head of the Royal Gardens at Windsor. John apprenticed, too, becoming a gardener in his own right at Ripley Castle, Yorkshire, in 1825. As good as he was at flowers and trees, birds became young John Gould’s true passion early in life. Like John Edmonstone, John Gould (1804–1881) adopted Charles Waterton’s preservation techniques that kept taxidermied bird feathers crisp and vibrant for decades (some still exist in museums today), and he began to employ the technique to make extra cash. He sold preserved birds and their eggs to fancy Eton schoolboys near his father’s work. His collecting side-hustle soon landed him a professional post: curator and preserver of the new Zoological Society of London. They paid him £100 a year, a respectable sum for an uneducated son of a gardener, though not enough to make him Charles Darwin’s social equal (Darwin initially received a £400 annual allowance from his father plus £10,000 as a wedding present).

Darwin claimed that On the Origin of Species, or the Preservation of Favoured Races in the Struggle for Life was only an “abstract” of that much longer book he had begun to write in 1856, after his irreverent meeting with J. D. Hooker, T. H. Huxley, and T. V. Wollaston, and Lyell’s exasperated encouragement in May. But he never completed that larger book. Instead, he worked on plants and pigeons and collected information through surveys from other naturalists and professional specimen hunters like Alfred Russel Wallace for the better part of a decade.