Editor's Note

Abstract

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• Editor's Note
• Quill R. Kukla

This issue of the Kennedy Institute of Ethics Journal offers three articles that encourage readers to think in different ways about how we use and share medical facts and information. Communication and information-sharing in medicine are never value-neutral processes, and there is never an objective answer to what information should be shared or how. What information we have access to, what information we take as relevant, and how we share that information are always vexed issues. This is because medical information is inherently socially charged, value-laden, and uncertain, and sharing it is bound up with norms of privacy, principles of relevance and empirical reasoning, and the complexities of health communication. All three essays in this issue, in taking up these issues, work at the intersection of ethics and social epistemology.

In "The Goals of Medicine: Debate and Disagreements Around Contraceptive Side Effects," Ilvie Prince argues that our framing of the benefits, risks, and side effects of hormonal contraception is shaped by a specific understanding of the purpose and nature of medicine. This framing, she argues, ends up harming people who can become pregnant. While it is common to point out that contraceptive and reproductive health care are distorted by sexism, Prince argues that there are yet deeper distortions at work in our understanding of contraceptive side effects. When the primary goal of medicine is understood as the prevention of disease and dysfunction, narrowly construed, this obscures our ability to properly weigh and articulate the harms of both pregnancy and contraception. Since women are disproportionately the ones who bear the burdens and risks of both reproduction and contraception, this obfuscation has sexist results, as it disproportionately harms women. Prince also argues that once we understand the goals of medicine more broadly, we cannot avoid the uncomfortable fact that doctors must address social harms and benefits—and not just narrowly biological ones—despite the risk that this kind of intervention can serve politically nefarious ends. Prince's rich piece draws on her deep understanding of bioethics, as well as the history and science of reproductive medicine. [End Page vii]

Benjamin Chin-Yee's tightly argued paper—"Generalizations in Clinical Trials: Do Generics Help or Harm?"—digs into the details of the language of health communication and its epistemic and ethical perils. He points out that generalizations in biomedical science (statements about what is generally true) often take the form of generics. Generics are general statements that contain implicit generalizations, but don't actually use quantificational language, such as "Drug A cures condition C" or "People with Disease D have symptom S." This contrasts with explicit quantificational generalizations, like "Drug A usually cures condition C" or "People with Disease D have symptom S 85% of the time." Philosophers of language have shown the ways in which generics are value-laden and potentially ambiguous. Chin-Yee draws on these discussions and demonstrates that generics are both common and potentially misleading in the context of public health communication. He also argues that they smuggle in values that cannot be excavated or critically examined in typical public communication contexts. Although generics have epistemic benefits, he claims that their epistemic harms outweigh these benefits, and he proposes avoiding generics when biomedical scientists are communicating with the public.

Finally, Michiel De Proost, in "Data Solidarity Disrupted: Musings on the Overlooked Role of Mutual Aid in Data-Driven Medicine," takes up an emerging problem at the intersection of ethics and epistemology, namely medical data sharing. Data sharing is important for the advancement of medical knowledge, but it can also be easily exploited by companies or individuals. Typically, De Proost argues, we think of data sharing as something that patients are supposed to do altruistically, to further goals that are not directly their own, such as research or the provision of public services. But this model does little to address problems of exploitation, structural injustice, or elite capture. Instead, De Proost draws on classic anarchist theory, as well as anarchist conceptions of solidarity and mutual aid, in order to suggest a bottom-up model of what data solidarity and sharing might look like. [End Page viii]

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