In biomedicine, practitioners often treat risk of disease as an illness in itself—suitable for monitoring and intervention. In some cases, increased diagnostics improve health outcomes by detecting problems early. Recently, however, science and technology studies scholars and medical practitioners have noted that the treatment of risk can also lead to unnecessary intervention and possible harm. Despite these findings, it is often hard to see changes in practice. Childbirth serves as an illuminating case because two models of health risk operate simultaneously—in (...) addition to the model valuing frequent intervention, there is another that seeks to mitigate risk by refusing medical surveillance. Based on interviews with birth providers and an analysis of professional documents, this article uses the case of fetal heart rate monitoring in American childbirth to demonstrate how some health providers are framing “intentional non-knowing” as a moral imperative to reduce medical risk. Studying the success and limitations of this “risk counterculture” illuminates how risk societies are changing in response to data suggesting that more information can have hurtful effects. This case integrates well-developed theories of knowledge production with less-developed theories of knowledge nonproduction, leading to a more fruitful discussion of the boundaries of responsible knowledge in risk management. (shrink)

Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements in the informed (...) consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward. (shrink)

In Tyranny of the Gene: Personalized Medicine and Its Threat to Public Health (Knopf, 2023), James Tabery traces the ascendance of personalized or precision medicine in America, arguing that America's emphasis on genetics offers more hype than transformational power. In his examination of the power struggles, social relationships, and technological advances that centered the gene in American health policy, Tabery demonstrates how an intensive focus on genetics draws attention away from both the fundamental causes of health disparities and more‐effective changes (...) that could be made to developmental, physical, and social environments. American policy‐makers, health care institutions, funders, and bioethicists should not let the technological shine and attractive politics of personalized medicine continue to replace the hard but necessary work of addressing sociopolitical causes of disease and illness. (shrink)

A large body of scientific careers literature explores the experiences of underrepresented minorities in STEM fields and why they exit the academic pipeline at various stages. These studies commonly address how to improve racial diversity in science but provide little discussion of why that diversity is important for science research. Feminist science studies scholars, on the other hand, have theorized about the importance of diversity in knowledge production for decades but provide little empirical work on how to address current disparities. (...) My research bridges these literatures by examining how diversity programs in the sciences justify their continued funding, and how these justifications map onto contemporary theories of knowledge production. Do diversity program directors seek to increase diversity in science because of political motives, like equality and justice for racial minorities, or because they believe that racially diverse workforces will produce better science? Based on interviews with federally-funded diversity program directors at universities and archival data from these programs, I find that program directors’ responses can be classified into three categories: diversity is important politically, diversity is important pragmatically, and diversity is important epistemically. About half of the respondents found diversity to be important for the content of scientific knowledge. I argue that studying diversity in scientific knowledge production is different than studying the impacts of diversity in other fields due to current conceptions of scientific objectivity. Scholarship on scientific knowledge production can help diversity program directors and science careers scholars better articulate the need for diversity programming in STEM fields. (shrink)

In modern medicine, health risks are often managed through the collection of health data and subsequent intervention. One of the goals of clinical genetics, for example, is to identify genetic predisposition to disease so that individuals can intervene to prevent potential harms. But recently, some clinicians have suggested that patients should undergo less testing and monitoring in an effort to reduce overdiagnosis and overtreatment. In this paper, I explore how clinicians navigate the tension between identifying real disease risks for their (...) patients with concerns about overdiagnosis and overtreatment. I focus on clinicians ordering genetic testing for inherited cardiovascular diseases. Of the genes determined to be “clinically actionable” by the American College of Medical Genetics and Genomics, half are related to cardiovascular diseases. But, due in part to high levels of uncertainty surrounding cardiovascular genetics, there is still disagreement within the field about how to order and interpret these tests. Based on semi-structured, in-depth interviews with 20 clinicians who order genetic testing for cardiovascular diseases, I find that there is considerable variability in the ways that clinicians determine which types of genetic tests are appropriate for their patients and how they interpret test results. Most importantly, I find that many providers do not presume that more genetic data will lead to better care. Instead, increased genetic data can lead to confusion and inappropriate treatment. This re-valuation of the utility of medical data is crucial for bioethicists to explore, especially as medical fields are sorting through increasing amounts of data. (shrink)