The Handbook of Science and Technology Studies Part 13 ppt

of that competition (cashed out in terms of patents and testing licenses) both for
patients, their representatives, and clinical practice in the cancer clinic (Parthasarathy,
2003; Bourret, 2005) and for national differences over genetic privacy (Parthasarathy,
2004) and genetic testing cultures (Parthasarathy, 2005; Gibbon, 2002). If the case of
the BRCA1 and 2 genes and breast cancer is to be seen as encapsulating expectations
concerning genetic testing for complex diseases, then as in cystic fibrosis, STS teaches
caution about simplistic assumptions regarding the delivery of such testing. A related
point is made by Nelis (2000) in a comparative study of the management of uncer-
tainty in genetic testing services in the Netherlands and the United Kingdom, where
she argued that the construction of expectations and the management of the future
are shaped by the structure of the local networks.
In focusing on specific technologies (rather than conditions), research has revealed
just how much effort it takes to get a new form of testing or therapy into the clinic
(Martin, 1999; Hedgecoe, 2003; Hedgecoe & Martin, 2003; Hedgecoe, 2004). Partly
this may be because of the tendency of STS research (unlike, say, medical sociology)
to focus on knowledge at the expense of practice, yet even when a clinical interven-
tion has been available for some time, there is still considerable flexibility over how
it is seen in the lab, in the clinic, and by patients (Rapp, 2000). New molecular tech-
niques are incorporated into existing clinical practices rather than sweeping them
aside in a revolution (Nukaga, 2002). The range of conditions explored in this work
and the limitations faced by these technologies when they enter the clinic highlight
the point that very few of the expectations that were used to justify the HGP have
been realized to date, with almost all the new clinical techniques restricted to estab-
lished genetic niches.
REPRESENTATION AND CULTURE OF GENOMICS
It is when debates around genomics leave the lab, clinic, or boardroom and enter the
broader culture and public discourse that they become the most overtly political. In
the case of public understanding of science, the expectations about genomics raised
are different from at other sites. Rather than there being expectations about science
and technology, in the case of PUS, the expectations concern people’s reactions and

behavior toward science and technology. If we view the “deficit model” of PUS as con-
structing typical expectations about how people will react toward genomics, then,
given STS’s historical role in challenging this model and the high profile human genet-
ics has in public debate, we should not be surprised to see work in this area under-
mine and question simplistic beliefs about how the public will respond to genomics.
Perhaps the clearest evidence that within STS the transformational approach to
genomics can be highly critical of developments in science and technology lies in
Dorothy Nelkin’s sustained critique of the way in which modern genetics is portrayed
in the media and popular culture (Nelkin, 1994; Nelkin & Lindee, 1995, 1999). Clearly
written from a position that takes developments in modern genetics as somehow dif-
ferent from what has gone before, Nelkin’s work, and that of other scholars like Abby
826 Adam M. Hedgecoe and Paul A. Martin
Lippman (Lippman, 1994, 1998), can be criticized for lack of historical depth and
methodological problems (Condit, 1999, 2004) but not for political urgency and crit-
ical drive.
Of course, it is perfectly possible to carry out a historically rooted analysis of the
cultural representation of genetics and produce a critical piece of work (Turney, 1998;
Smart, 2003), and overall STS researchers have tended to stay close to the discipline’s
qualitative roots, eschewing the survey approach often used by other social sciences
to study this area (Davison et al., 1997). Of particular note is the extensive work done
by Anne Kerr and colleagues who have used interviews and focus groups to explore
the different ways in which geneticists (Cunningham-Burley & Kerr, 1999; Kerr et al.,
1997, 1998a) and nonscientists (Kerr et al., 1998b,c) view developments in genetics
and associated ethical issues. This rigorous empirical basis has provided a foundation
for a subsequent critique of the way in which some social theorists have engaged with
human genetics (Kerr & Cunningham-Burley, 2000) and developing concepts around
the political life of human genomics (Kerr, 2003a,b,c). A core element of this and other
work (Barns et al., 2000; Irwin, 2001) is to incorporate nonscientist opinion on genet-
ics into discussions about the development of this technology, showing not only that
members of the public are capable of understanding complex scientific concepts but

also that they can contribute in a meaningful way to debates around the regulation
of these new technologies.
When facing expectations about genomics, public and professional cultures tend to
divide, with the concerns of professionals (both scientific and non-STS-based social
scientists) being rooted in traditional models of the public and technology, with
ethical expectations marginalized and simplistic solutions suggested. To some extent
it might be seen as a failure that the public culture emphasized through STS for so
many years has had such a low profile among practicing scientists, yet whether we
take a transformational or contextual position, the increased presence of genomics in
the press and public discourse seems assured. That STS shows how scientists and
policy-makers who refuse to reorient their expectations in accordance with how the
public reacts engender resistance and even failure (Robins, 2001) provides an oppor-
tunity for work in this area to feed directly into political discussion over how societies
might respond to new technologies. Contextualists might take the opportunity to
highlight the public’s fears of, for example, racialized science (Duster, 2001) while, as
the next section discusses, transformationalists may show how particular groups of
nonexperts adapt and adopt genetic knowledge to serve their own social needs. The
point is less about whether genomics is transformative of wide cultures and publics
but rather that this context presents STS scholars working in this area with a unique
opportunity to engage with public political debate.
CREATION OF NEW GENOMIC IDENTITIES
One of the most influential recent strands of argument in the field of the social studies
of the life sciences concerns ideas of biosociality (Rabinow, 1996a) and biological
Genomics, STS, and the Making of Sociotechnical Futures 827
citizenship. While the origins of these ideas may be see as formally lying outside the
realm of STS, they have shaped much of the debate on the creation of new genomic
identities.
The initial focus of work in this area arose from studies of new reproductive tech-
nologies and the development of genetic testing services for mainly rare monogenic
conditions (Rapp, 1998, 2000). Research has recently started to look at more common

complex disorders. Finkler, drawing on the experience of women who have a heredi-
tary risk of breast cancer, argues that the presentation of research findings has led to
a new genetic determinism, the medicalization of kinship, and changing ideas about
the significance and meaning of kinship (Finkler, 2000; Finkler et al., 2003). In par-
ticular, she shows how the experience of the new genetics can transform a healthy
person into a patient without symptoms and places increasing emphasis on biologi-
cal rather than social determinants of health and illness. However, writing from within
the contextual approach, Kerr has criticized studies of this sort for lacking empirical
evidence and overemphasizing the role of genetics as a consequence of giving too
much weight to the role of biological knowledge in shaping life choices (Kerr, 2004).
In contrast to seeing the new genetics as largely negative in its consequences for an
individual’s sense of self, Novas and Rose argue that knowledge of genetic risk does
not generate fatalism but induces new relations to oneself and one’s future, and a new
set of obligations and biological responsibilities (Novas & Rose, 2000). This in turn is
creating new individual and collective identities such as those embodied in patient
groups for muscular dystrophy or Huntington’s disease. These can challenge ideas of
stigma and exclusion, as well as dominant medical discourses. Rabinow has called this
creation of new subjectivities “biosociality,” as distinct from Foucault’s concept of
biopower in which life and its mechanisms are calculable and this knowledge is used
to discipline both bodies and populations. This perspective is explicitly transforma-
tive, distancing as it does modern genomics from traditional concerns about eugen-
ics. This does not mean that there are not ethical issues, of course, simply that they
are of a new kind (Rose, 2001).
It should be noted that other nonmedical genetic technologies, such as the devel-
opment of genetic ancestry testing, are also creating new forms of collective and indi-
vidual identity (Tutton, 2004; Nash, 2004). Following on from this, it is argued that
the emergence of new identities based on ideas of genetic susceptibility and risk, and
the embodied disciplines and representations of rights and responsibilities that are
being co-constructed through new screening and public health programs, constitute
a new form of biological or genetic citizenship (Rose & Novas, 2004). Through the ful-

fillment of the duties to know and manage genetic risk in order to protect themselves
and their families, individuals are seen as constructing themselves as healthy and
responsible citizens (Petersen, 2002; Polzer et al., 2002). Hovering between these two
positions is work like that of Taussig, Rapp, and Heath, who, in their research on the
“Little People of America” patient group, explore a range of technological interven-
tions (such as surgery or genetic testing) using the concept of “flexible eugenics” to
point out the positive and negative options for self-identity that arise from genetic
828 Adam M. Hedgecoe and Paul A. Martin
technologies (Taussig et al., 2003). Similarly, Callon and Rabeharisoa note a number
of ways in which people resist the imposition of such genomic identities (Callon &
Rabeharisoa, 2004).
Thus, we suggest that while new genetic and genomic knowledge can be seen as
helping constitute distinct new forms of identity, subjectivity, and citizenship, the
extent to which these transformations are happening outside very tightly defined
niches (patient groups for rare genetic diseases) or represent a clear break with the past
remains unclear. As such, we feel that STS scholars ought to display caution with regard
to expectations vis-à-vis genomics’ impact on social identity.
GOVERNANCE OF GENOMICS
Research on the governance and regulation of genomic technologies has been funda-
mentally shaped by earlier work on the ethical, legal, and social issues (ELSIs) raised
during the controversies surrounding the development of recombinant DNA (rDNA)
and biotechnology, and the political response to these concerns. With a few notable
exceptions (Nelkin & Tancredi, 1980, 1994; Duster, 1990), little of this work was from
an STS perspective, most of it having a largely normative agenda that critiqued the
potential hazards and social problems caused by emerging genetic technologies. There
have also been important national differences between the United States and Euro-
pean states in terms of political and institutional responses and also in the type of
scholarship that has been funded in this area. Broadly speaking, U.S. ELSI research has
been dominated by bioethicists and lawyers, while in the United Kingdom social sci-
entists have played the key role. One consequence is a relative lack of U.S. STS studies

in this area.
During the 1980s and early ’90s many of the institutional mechanisms and regula-
tory regimes designed to control early rDNA research and first-generation biotech-
nology products were established, and a number of STS scholars have analyzed their
creation in detail (Bennett et al., 1986; Wright, 1994, 1996; Gottweis, 1995, 1998).
This is important work but, strictly speaking, lies beyond the scope of this chapter. In
contrast, significantly less attention has been given to more recent changes in these
regimes brought about by the turn to genomics and the development of new tech-
nologies, such as genetic screening and gene therapy. In looking at the broad field of
genomics and postgenomics, Gottweis has argued that “. . . the science of genomics is
introducing a number of fundamental transformations in the practice of modern
biology and medicine, in pharmaceutical industry, in society and culture” (Gottweis,
2005: 202). He goes on to suggest that there is a gap between this challenge and offi-
cial policy responses, which might ultimately lead to a crisis of confidence in medical
biotechnology.
The small body of work that examines the governance of genomics in more detail
is mainly United Kingdom–based. Salter and Jones have studied recent changes in the
overall regime governing human genetics in the United Kingdom. In particular, they
have charted the creation of a complex system of statutory regulatory bodies and
Genomics, STS, and the Making of Sociotechnical Futures 829
nonstatutory expert advisory committees. This system was reconfigured following
what was constructed as a major crisis of trust following the public rejection of genet-
ically modified food in the late 1990s and has adopted a discourse of open govern-
ment, based on the language of public engagement and greater transparency, as a
legitimating strategy (Jones & Salter, 2003). In a similar study of the regulation of
human genetics at the EU level, Salter and Jones (2002) have shown that similar pres-
sures have forced policy-makers to engage with a greater range of stakeholders and
publics, as well as placing more emphasis on the role of expert bioethicists in medi-
ating disputes. An important recent addition to the literature is Jasanoff’s three
country comparison of the governance and regulation (including informal forms such

as bioethics) of biotechnology, which provides an important basis for future STS work
in this area (Jasanoff, 2005).
There have also been studies of the governance of specific genomic and genetic tech-
nologies, including genetic databases (Martin, 2001; Petersen, 2005) and genetic testing
(Martin & Frost, 2003) in the United Kingdom, as well as a comparative U.S./U.K.
study of genetic privacy (Parthasarathy, 2004). In particular, these have shown how
specific innovations are co-constructed with regulatory regimes and how they are
shaped by local political, cultural, and institutional factors. Considerable attention has
been paid to exploring the new forms of governance and public engagement that seem
to have become associated with genetics and biotechnology in the United Kingdom
over the last decade (Tutton et al., 2005; Kerr, 2004; Purdue, 1999). This research sug-
gests that, while important changes have occurred in the way in which the public is
constructed and engaged by policy-makers, established power relations continue to be
reproduced. Furthermore, the narratives of choice and responsibility that are a
common hallmark of policy discussions in this area are seen to frame the problems
associated with new genetic technologies in ways that shift attention away from
broader questions of social priorities and the goals of scientific research (Kerr, 2003c).
Furthermore, Anne Kerr argues that it is premature to talk about a new form of genetic
citizenship, as many questions remain unanswered about how the new rights and
responsibilities of different actors are defined and exercised in practice (Kerr, 2003a).
It therefore appears that while genomics has been associated with some significant
changes to institutional arrangements governing biotechnology, it has not prompted
a completely new regime. Additional important drivers of change can be identified,
including loss of public trust, and this has led to new policy discourses and experi-
ments in public engagement. The difficulty in breaking down established divisions of
expertise and institutional barriers casts doubt over the idea that we are seeing new
forms of citizenship emerge.
CONCLUSION
Through a review of the STS literature on genomics the aim of this chapter was to
answer two broad questions: What sociotechnical expectations and transformations

are being associated with the rise of genomics? What is seen as new and specific to
830 Adam M. Hedgecoe and Paul A. Martin
genomics, and what is believed to be the extent of sociotechnical change? As we might
expect from a discipline that teaches us to question the apparently straightforward facts
presented by science, work on STS forces us to challenge the assumptions that under-
pin even such obvious questions. To some extent the presence of a strong contextual
perspective in STS scholarship, questioning claims about the transformational impact
of genomics, raises doubts not just about the wording of these two questions but about
the nature of this chapter itself. As STSers, our natural instinct may well be to assume
novelty on the part of scientific and technological developments, in terms of both
technical change and social and ethical impact. Yet the discipline’s strong links to the
history of science provide a conduit through which contextual assumptions can flow,
challenging the automatic belief that every technological development implies a revo-
lution. We accept that our own backgrounds mean that the contributions of sociolo-
gists are perhaps overemphasized, but we feel that the picture of STS scholarship
painted in this chapter should be broadly recognizable to people working in this field.
As noted earlier, the point of this chapter is not to adjudicate between these differ-
ent ways of looking at genomics. The richness of debate, variety of case studies, and
rigor of research in this area stems in part from the existence of these different ways
of seeing the same material. Rather, we would like to agree with Taussig, Rapp, and
Heath and suggest that, with regard to the social implications of genomics, “a working
knowledge of the political history of eugenics gives us reason for pessimism of the
intellect, but an ethnographic perspective on the openness of these practices may give
some cause for optimism of the will” (Taussig et al., 2003: 72–73). Taking a broader
approach, Andrew Webster links the perceived novelty of genomics within larger social
trends, namely, the more “liquid” nature of modern society, with its flexible bound-
aries and wide range of possible new configurations. One effect of such a context is
to move away from the idea of “genomics as intrinsically and necessarily transfor-
mative . . . allow[ing] us to turn our attention to the ways in which genomics research
is or could be articulated in society to close off or open up ‘possibilities’” (Webster,

2005: 237).
What is clear is that much STS scholarship, of whatever kind, maintains a skeptical
stance toward scientific claims about genomics, justifying this position with detailed
and closely argued empirical studies. The expectations raised at the launch of the
Human Genome Project have yet to be realized in any significant sense in the clinic,
and it is far from certain that the impact of genomics on industry or personal iden-
tity will stretch as far as some commentators claim. That said, in certain of the domains
outlined above, particularly those relating to the production of new scientific knowl-
edge, genomics has proved to be transformational. Perhaps what we need now is an
understanding of why it is that expectations about genomics are being realized in
some areas and not in others.
Note
1. Tony Blair, MP, “Science Matters,” speech to the Royal Society, April 10, 2002.
Genomics, STS, and the Making of Sociotechnical Futures 831
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Genomics, STS, and the Making of Sociotechnical Futures 839
At a recent meeting on nanotechnology, a speaker described the following scenario.
A person opens a pill bottle to take a daily dose of medication. In doing so, biosen-
sors on the container transmit information about the person’s biochemical status to
the primary physician, and an inventory of remaining medication is reported to sup-
pliers. Health status and other information is then relayed back to the person’s Black-
Berry,
1
stimulating him or her to follow recommendations to purchase goods, change
daily patterns, or if nothing more, be aware of his or her body’s condition on a daily
(or more frequent) basis.
Discussions of medical technologies are often freighted with such fantastical future
scenarios, but one need not go that far to see how intimately connected biomedicine
is with other domains of life and labor. In fact, it is rare to pick up a newspaper, listen
to workplace conversations, or watch entertainment without some reference to
medical technology in one of its myriad forms. Medical technologies permeate all
aspects of human experience from birth to death, whether one is healthy, disabled,
or ill. In addition to diagnosing disorder and replacing bodily function, medical tech-
nologies can compile and disseminate information about bodies, monitor physical and
mental states, ameliorate or create new forms of suffering, or make people “better than
well.” Technological systems and the information they provide also affect family and
work life, regulate individuals and societies using medically derived norms, and par-
ticipate in the selection and application of resources to certain groups (and not others).
The medical shaping of social identity is thus a significant aspect of medical devices,
diagnostic tools, and data dissemination that deserves analysis.
The scenario is a good tool for considering what comprises medical technologies and
how tightly connected they have become with other aspects of daily life, commerce,

and governance. Medical technologies can be defined as the various devices, instru-
ments, and therapies used for diagnostic, therapeutic, rehabilitative, preventive, or
experimental purposes as well as the practices and procedures associated with them. Yet
there are conceptualizations of users, of the nature of illness and susceptibility, and of
the relations among technologies and the body that animate emerging technologies
and create certain kinds of connections in interaction with institutional and technical
means. What sort of medical technological system was this scientist imagining? What
33 Emerging Medical Technologies
Linda F. Hogle
contributions by clinical practitioners, political authorities, insurers, population health
planners, or industrial developers and suppliers of goods and services might lead to this
particular assembly of medical-biological, communications, and engineering tech-
nologies, and what new knowledge and entities might emerge as a result?
The diversity and extension of technologies into many domains presents a chal-
lenge to those who would analyze the field as a set of techniques, knowledge forms,
and practices. While it is impossible to cover all technologies, uses, historical prece-
dents, and contemporary dilemmas, this chapter uses representative work from the
social and historical study of medicine to illustrate key themes and approaches to
studying medical technologies.
The chapter is organized into three parts. The first deals with the centrality of tech-
nologies in diagnosis, that is, the determination of the nature and cause of disease.
Diagnostic and research data from instruments are essential to such determinations
but are in constant interaction with systems of expertise, theories, and the institutions
in which they exist. Rather than passively supplying information, technologies may
change what constitutes evidence of both the presence of disorder and of the utility
of certain therapeutic approaches. Medical technologies, in conjunction with concepts
of disease, can categorize individuals into culturally constructed states of normality or
pathology and have become a central part of decision-making about managing health
problems in certain ways, including prognosis and decisions about which therapies to
use. Diagnoses can determine treatments (how and where people will or will not be

treated) and prognosis (probabilities and what is to be done). For these reasons, STS
researchers have become interested in new forms of subjectivity as technologies affect
peoples’ lives and work in tangible ways.
The drive toward ever more specific connections of causal mechanisms to illness
stimulates a desire for more evidence about which interventions work and under what
conditions. The second section deals with testing and evaluating emerging technolo-
gies, as this is the phase that links the analysis of diagnosis to therapy. Testing pro-
duces various forms of knowledge. Greater volumes of data and specific kinds of proofs
are demanded in order to make the link between mechanism, disease, and therapy
and to reduce the variability of practices and products thought to create inefficien-
cies. New products must also be tested to pass regulatory oversight and financial
review, as the state, private payers, and other authorities have a stake in decisions
about availability and costs of health services. The kinds of evidence sought (predic-
tive, classificatory, economic) are looped back to pragmatic problems of testing,
because the definitions, protocol design, and interpretations of results may frame
medical problems in particular ways. At the same time, products are reconfigured
through early interactions with potential users and those who have something at stake
in the introduction of new technologies or in preventing their use.
The final section deals with technological modifications to the body, including ther-
apeutic, aesthetic, and life-extending ones. While medicine has been thought to be
about repair, restoration, and the alleviation of suffering, other goals (such as longer
life, the elimination of traits perceived to be disabling to individuals and society, the
842 Linda F. Hogle
expression of individuality and for some a search for perfection) are increasingly
involved, in some cases aligning technologies with identity politics. To see how
humans and technologies constitute each other, a number of works in STS explore the
expectations, categorizations, hopes, and desires embedded in such emerging tech-
nologies and the ways they are deployed.
Selected examples of STS work illustrate various approaches to these themes, and a
discussion of recent innovations, in particular, regenerative medicine, will illustrate

emerging forms of technological systems that will have broad implications for bio-
logical and social life in contemporary global economies. Other chapters in this
volume deal with specific technologies including organ transplantation and genetic
tests (chapter 34), genetic and reproductive technologies (chapter 32), imaging
(chapter 13), and pharmaceuticals (chapter 29), and these topics are only touched
upon here.
2
WAYS OF KNOWING: DIAGNOSIS, DISEASE CLASSIFICATION, AND TECHNOLOGIES
In a seminal paper on what he calls the “tyranny of diagnosis,” Charles Rosenberg
draws attention to the pivotal role of diagnosis and the ways it has been reconfigured
as medicine becomes more technical, specialized, and bureaucratized. He argues that
agreed-upon disease categories based on assumptions of ontologically real and specific
disease entities have become the core organizing principle in medicine (Rosenberg,
2002). The codification of concepts into bureaucratic systems then becomes the way
to control costs, manage deviance, and legitimate certain sick roles (but not others).
Ultimately, the resulting taken-for-granted categorizations of patients and disorders
structure clinical and patient practices. Integral parts of the way knowledge is pro-
duced and standardized are the various instruments, techniques, information, and
communication systems collectively called medical technologies.
Apparatuses can be used to extract information with which to establish a body’s bio-
logical and social status, monitor it over time and circumstances, and report the find-
ings to various types of experts across widespread networks. From this information,
large databases can be created with which to define health and illness, reformulate
categories of normal and abnormal, make judgments about individuals and popula-
tions, provide predictors of risk, and then plan future services and technologies. In
this way, assumptions about deservedness, capability, and behaviors are built in to
both the technologies and interpretation of data they produce.
Diagnosis, broadly understood, has been studied in STS work by a variety of
approaches. The following discussion groups these into historical studies of specific
technologies; constructivist, actor-network, and assemblage analyses; studies of clas-

sification and standardization processes; and emerging forms of subjectivity.
Technology Histories
Historians have shown how medical technologies often emerge from their original use
as research tools and how the development of diagnostic instruments was connected
Emerging Medical Technologies 843
with theories about disease and bodily function (Marks, 1993). In an era of interest in
the mechanical properties of the body, for example, the thermometer was developed
to measure temperature changes and the sphygmomanometer to measure the pressure
of blood flow to test the heart’s pumping efficiency (Porter, 2001). Yet developments
of instruments in turn profoundly affected theories of the body and disease. Most
notably, microscopy changed what was presumed to be true about cells and their struc-
ture. As optical and histological techniques improved, the enhanced ability to observe
tissues linked knowledge about anatomy and physiology (Davis, 1981).
Marks (1993) advocates the study of medical technologies by looking at the “life
histories” of medical machines. This approach enables understanding the particular
skills and techniques that develop around particular instruments. Tracing the role of
patients and various users in the design and deployment of specific technologies
reveals the multiple origin stories that bear on a technology’s biography. However
approached, historical studies are critical to understanding the interplay between
instruments, theories of disease, and biological and social responses.
Technology, Organization, and the Medical-Industrial Complex
Some authors have extended the study of particular instruments to make visible the
ways that work and medical work spaces are affected. For example, equipment such
as diagnostic imaging requires specific skills, leading to the development of new pro-
fessional groups, and costly, large-scale equipment often necessitates architectural
changes and clinical facilities with the capacity and expertise to handle it. Sophisti-
cated diagnostics may then be bundled with related services at centralized, often urban
locales (Barley, 1988; Blume, 1992; Howell, 1995). Others expand analyses to include
the broader informational, organizational, economic, and political systems in which
technologies exist, trying to capture power relations in terms of how technologies will

be used and by whom. Stanley Reiser in particular drew attention to the situation of
technology within more general problems related to the medical-industrial complex.
His landmark book, Medicine and the Reign of Technology, was a significant contribu-
tion during a time of alarming health care cost increases (Reiser, 1978).
Another key work in this vein was Nelkin and Tancredi’s Dangerous Diagnostics
(1989). Writing about the explosion of diagnostic tests, the authors exposed the con-
nection of tests to reimbursement patterns from insurance plans. Payers, interested in
limiting costs, may either create an imperative to use tests (as in the screening of
potential policy holders for costly diseases or when a high reimbursement rate creates
financial incentives for physicians to test many patients) or may restrict access to
costly tests (sophisticated studies may be ordered when inexpensive lab tests are incon-
clusive, but may or may not aid in diagnosis). Insurers desire diagnostic data to esti-
mate life spans and employers to estimate productivity and limit liability.
In a remarkable example of the linkage of state economic interests, the medical
industry, and the diagnosis of disease, Plough (1986) demonstrated how concepts of
cost-benefit and clinical efficiency were built into medical definitions in the newly
created disease category of end-stage renal disease (ESRD). Essentially, the high costs
844 Linda F. Hogle
of chronic illness through the mid-twentieth century became the lens through which
the complex physiology of kidney and other organ failure were viewed. Ultimately,
treatment options were narrowed to dialysis rather than other possible therapeutic
options, in large part because of intensive lobbying by manufacturers of the new tech-
nology. Plough’s work exemplifies a shift to understanding technologies as being con-
stituted by interactions among various elements at differing levels, rather than as
having a unidirectional impact “upon” society.
Social Constructions, Material Practices, and Assemblages
The move in STS more generally toward social construction of technology examined
the social nature of the way truth claims are made and facts are stabilized. This led a
number of researchers to revisit the content of specific artifacts, rather than their use
alone. Other constructivists took more of a systems approach, examining artifacts

within their institutional environments, which helped link close-in studies of specific
technologies to more macro-level views (Bijker et al., 1987). Edward Yoxen’s (1990)
study of ultrasound’s development into a key diagnostic tool is an example. The move
from a nonmedical domain (the military) to medicine, and its ultimate use for diag-
nosing problems in fluid-filled areas of the body, required consensus among diverse
groups of clinical medical, engineering, and physics professionals and negotiation
across professional, technical, and institutional domains about appropriate applica-
tions. Also, the images were difficult to interpret for clinical users accustomed to chem-
ical or radiological data. Perceptual blocks from some potential users could be
ameliorated by making the images simpler and easier to read, but this was possible
only at the expense of technical complexity. Image data were thus produced not
simply as a matter of theoretical science or accurate reproductions of bodily interiors
but as a compromise and a result of a series of tradeoffs between reliability and ease
of interpretation necessary to make the technology usable in the clinic.
An extension of social studies was actor-network theory, which took seriously both
human and nonhuman actors as having a form of agency. Technologies are not passive
in this view; rather, they actively intervene in the situations in which they are put to
use. Annemarie Mol (2000) illustrates by showing that self-measurement devices for
glucose do more than allow for the measurement of preexisting facts. Instead, they
alter the value of the facts by changing the target of treatment (more frequent mea-
surements report glucose levels on a different, higher curve than the previous nor-
mative ideal). This in turn ratchets down the level of blood glucose deemed to be
acceptable. The device made to detect abnormal blood sugar alters what counts as
abnormal, Mol argues, creating a type of nonhuman agency.
Social constructivist perspectives are often criticized as placing too much emphasis
on social determinants, with insufficient consideration of possible agendas built into
technology design and deployment or of the kinds of knowledge being produced.
Actor-network studies are criticized because they tend to focus on managers and elite
experts in technological domains, with insufficient attention to those who may be
less visible but yet are affected by the technology. Using a “social worlds” approach,

Emerging Medical Technologies 845
Clarke and Montini (1993) point out that there may be actors downstream who may
not be directly involved in networks of innovation but are certainly implicated in
assumptions and decisions being made on their behalf (see the following section).
Another approach to analyzing medical technologies is to consider how the material
practices of doing research and clinical work constitute medical knowledge. That is,
the cell culture techniques, methods of quantifying and visualizing biological phe-
nomena, and other routine activities in the lab may, for example, affect the way disease
models are formulated or how life forms get defined. Similarly, practices involved in
categorizing pathologies, handling data, establishing testing or treatment protocols,
and determining where patients will be treated (and by whom) are all linked
to assumptions about health, illness, and appropriate care (Casper & Berg, 1995;
Pickering, 1992).
Observing material practices shows how tools may be made to be the “right tools
for the job” (Clarke & Fujimura, 1998). The process of “making it right” may occur
even after the technology has been introduced into routine use, as in the case of the
Pap smear (Casper & Clarke, 1998). A number of tinkering strategies, including chang-
ing definitions and techniques, were required by pathologists, clinicians, public health
officials, and others before the technique became accepted as a diagnostic screening
tool for cancer. The coordinating and negotiating activities that take place across dis-
ciplines and domains have become a key to understanding innovation and knowledge
production. In her work on cancer researchers, Fujimura (1987) argued that the work
of articulation and alignment in order to gain agreement and stabilize facts is what
makes problems “doable.”
Alignment of interests, theories, and techniques may affect acceptance, rejection,
or routinization of a technology, but so may political exigencies, cultural values, or
ethical concerns. Legal concerns, values about life extension, or political issues related
to the termination of particular lives may become the dominant factor in the deter-
minations of dead, dying, or salvageable life, trumping network alignments or even
evidence of a technology’s efficacy (Kaufman & Morgan, 2005; Timmermans, 2002).

A number of recent works reflect on cultural influences on technologies, healing tra-
ditions in various cultures, and power relationships in the clinic and lab that are
important contributions to STS literature on technology (Brown & Webster, 2004; Lock
et al., 2000).
Another important aspect of studying diagnosis is the way facts are stabilized.
Cambrosio and Keating, among others, demonstrated the subtle ways that medical
knowledge is constituted through nomenclature, tacit knowledge, and procedural
rituals (1992). For knowledge to be durable, data must be made to be intelligible. Oth-
erwise it has little clinical utility. Test results must also be able to be compared across
patients and conditions. Yet protocols to collect and interpret information are based
on criteria that are often arbitrary and site-specific and may be limited by capabilities
of local expertise. Nevertheless, data have to be intelligible to have clinical utility. Burri
and Dumit (chapter 13 in this volume) describe difficulties of interpreting data in
imaging technologies, which are particularly problematic. Visual records produced by
846 Linda F. Hogle
computerized tomography, ultrasound, PET scanners, and magnetic resonance
imaging are not photographic captures of reality but mathematically constructed rep-
resentations of structures or metabolic functions. Image interpretation requires con-
siderable skill and agreement on what the images really show as well as
cross-referencing to other ways of mapping anatomy (see also Cartwright, 1995;
Dumit, 2004; Prasad, 2005).
Computerized medical decision-making tools were meant to streamline decision-
making at the bedside and increase objectivity by comparing patient information to
reference databases and standardized care plans. Although these tools operate on sup-
posedly stabilized facts about diagnoses, other social assumptions about patients and
their disorders get built into the systems, as demonstrated ethnographically by Berg
(1997) and Forsythe (1996). Although information systems were developed as data
interpretation tools to aid in classifying ailments and rationalizing variant and costly
practices, they function in multiple roles, including reordering work patterns in the
clinic, changing the content of bedside work, and in some cases, reifying power dis-

parities between patients and caregivers.
Blending some ideas from constructivist and network perspectives, a number of
researchers view technologies as an assemblage of machines, knowledges, practices,
people, histories, and futures. This framing enables a different understanding of the
embeddedness and potential power of medicine in our everyday lives. The innovation
of the polymerase chain reaction (PCR) for example, illustrates how a concept (the
manipulation of genetic material) led to a technique (the ability to identify and
amplify DNA), which itself was transformed into a form of knowledge production that
has profoundly influenced cultural change in science and in popular understandings
of biological life (Rabinow, 1996). Analyzing such transformations sheds light on the
emerging forces that animate predictions such as those which opened this chapter.
Keating and Cambrosio successfully illustrate key points about heterogeneity of
practices and settings, coordination, and standardization in their extensive study of
practices in immunology laboratories. Their recent work is concerned less with
laboratory-level phenomena and the production of local knowledge than with inter-
laboratory traffic, with attention to the configuration of instruments, people, methods,
concepts, and substances that traverse domains of biology and medicine, science and
technology, and disciplines within biomedical sciences (Keating & Cambrosio, 2003).
They argue that the existence of such networks is necessary for the establishment of
classifications from which diagnoses and prognoses are made. The authors call such
networks “biomedical platforms.” Platforms are more than passive infrastructural or
coordinating activities, however. They generate new kinds of biomedical entities that
sometimes slip between clinically or laboratory-based definitions of pathology and
make networks possible. In this way, the authors distinguish platforms from social or
technical networks (theory-methods packages or actor networks).
Using the example of leukemias and lymphomas, diseases that target the immune
system, the authors observed local patterns of interpretation that emerged when
new techniques and types of expertise were grafted onto existing practices and
Emerging Medical Technologies 847
organization of work. For example, in the United States it is visually oriented patholo-

gists who are in charge of the labs, whereas in France it is medical biologists, accustomed
to mathematically derived measures. This made a difference in the scoring of cell
markers and, hence, which markers were seen to be clinically relevant. In turn, this had
an effect on attempts to create classification systems with which to diagnose, categorize,
and give prognoses for diseases. But classifications change with new data collected from
additional patients, and they do more than simply order information. Classifications
themselves, then, are tools leading to new knowledge about disease entities.
Classification and Standardization
Classifying patients and diseases involves processes of standardization, which are also
critical for making protocols and instruments work across locales. The less visible work
of standards setting is where cultural forms, power relations, and gate-keeping are
established in ways that not only enable work to proceed across incommensurate
models and data sets but also legitimate particular ways of thinking about disease
(Bowker & Star, 1999).
Standardization activities were central in the transformation of healing practices
into scientific, technological medicine. By the mid-nineteenth century, efforts had
been made to increase the reliability of clinical judgments that previously had been
made by observation of bodily signs and by the physician’s senses of touch, smell,
and sight. Newly introduced instruments provided quantifiable measurements of
bodily function, visualizations of bodily interiors, and graphic representations of rela-
tionships over time and across subjects.
The quantification of information from and about patients’ bodies was meant to
provide an objective snapshot of bodily conditions but also served to create indica-
tors of pathological mechanisms that were thought to be linked to identifiable disease
entities. Whereas diseases had earlier been seen as idiosyncratic with multiple possi-
ble causes, concepts of disease categories could now be understood apart from partic-
ular bodies and circumstances (Rosenberg, 2002). Furthermore, data from instruments
could be more easily aggregated in ways that could also be used to govern popula-
tions. Foucault’s (1974) notion of biopower has been influential in this regard. By the
nineteenth century, statistics and other administrative means were employed to survey

and analyze populations and plan state programs for health and welfare. As life itself
became an object of political scrutiny and intervention, both individual bodies and
populations could be subjugated through techniques that included the constant mon-
itoring, testing, and improving of the self (Foucault, 1978; see also Rabinow, 1992;
Turner, 1996).
On the one hand, the increasing specificity of diagnosis matched by ever more tar-
geted tests (whether or not interventions are available) appears to make medicine more
oriented to individuals, while on the other hand, informational technologies enable
data to become more abstracted at the level of populations. Modern biomedicine seeks
to see, chemically analyze, or otherwise detect changes in individuals’ bodies down
to the genetic and molecular levels, and considerable investments have been made in
848 Linda F. Hogle
making or adapting tools to do so. At the same time, the data are pooled both to make
claims about causal links and to generate standardized, rationalized care plans applic-
able to large groups.
The effort to standardize clinical practice guidelines involves increased scientific
review of new and old therapies to produce comparable, quantifiable proofs of effi-
cacy. This concept, known as evidence-based medicine and public health, has been a
powerful trend in health policy, influencing trials of new therapies, payment patterns,
and clinical decision-making. Although the intent is to promote best practices for
making decisions about patients, current models and proofs often do not take into
account the many political, cultural, and behavioral realities that affect interactions
among patients, physicians, the health care system, and the environment. At the same
time, the way evidence about bodily conditions and medical therapies is produced
says much about the mutual penetration of research, industry, the clinic, and the state.
Techniques of biopower can be seen today in the connections between formal
medical classification systems and the state system. In their study of the International
Classification of Disease (ICD) system, Bowker and Star (1999) outline the links
between medical and other welfare systems in which the state has a central role. The
authors suggest that an elaborate information system that collects data on many

aspects of human life on an ongoing basis and can be mined for a variety of purposes
is essential to the state’s interest in the health and well-being of citizens, which are
also concerns for the good of the state. The result can be improved quality of clinical
decision-making, cost savings, and healthier citizens, but it also means increased sur-
veillance and the potential for discrimination for those in- or out-of-category.
Still, there are tensions between attempts to standardize, normalize, and unify
bodies and technological practices and the diversity that bodies display under varying
conditions, as the set of studies by Berg and Mol (1998) illustrates. The authors argue
that diseases and the technologies used to diagnose and ameliorate them are not a
single thing to be understood, but rather they become different kinds of objects
through material and social practices. Such studies focus on the stories that are
told about medical-scientific objects in diverse environments to show how norms get
established.
Subjectivity, Identity, and Emerging Medical Technologies
Using diagnostic technologies to name and classify diseases not only provides a means
for generalizing across populations, time, and locales but also provides a rationale for
justifying giving or withholding treatments and labeling individuals and groups as
being ill, aberrant, or “at risk.” Diagnostic technologies and classifications thus alter
human experiences and subjectivity. Along with theories about the body and its well-
being, technologies can serve to sort individuals into groups and reorder social rela-
tionships on the basis of classifications. One example comes from Biehl, Coutinho,
and Outeiro’s study of HIV/AIDS testing in Brazil (2001). Counterintuitively, the
people who most requested testing (and repeated testing) were those who were
seronegative. The authors argue that testing capitalized on anxiety in target healthy
Emerging Medical Technologies 849